But that’s not even the main thing.

His actual task and role (let’s not get into motivation) is to build an infrastructure around immortal vampires so they can interact with the modern world (surviving and satisfying their bloody and social thirst), and for the modern world to interact with them in return.

He’s not a vampire (though he desperately wants to be!) and no longer quite an ordinary human either. He exists between two worlds, and that’s why he’s the only one who can build something that works in both.

The vampires think he serves them. In reality, he’s the only reason they function in the modern world at all.

Expert organizations — research institutes, think tanks, cultural institutions — are not populated by vampires. Mostly. But they have their own version of Guillermo.

A person between the world of expertise and the world of communication, between what the organization knows and how that knowledge can exist on the outside.

And I’m one of them. I’m one of the Guillermos.

What does Guillermo actually do?

In the film and the series, Guillermo is a quiet, downtrodden figure. But me and professionals like me — we’re different Guillermos.

We’re Guillermos who chose this role consciously. The role is between experts, researchers, scientists, the communications department, the PR people, and the audiences.

So what does Guillermo do in our organization—an organization focused on the expert side of integrating Russian-speaking residents in Finland? An organization that, on the one hand, produces research, expertise, recommendations, and solutions for the Finnish state and public institutions — to help them better understand who Russian language speakers in Finland actually are, in all their complexity — and, on the other hand, runs projects and initiatives that support onboarding and integration into Finnish society.

For example, Guillermo builds a media platform — an actual media outlet for a linguistic minority — not as a standalone project, but as part of a system to support research and return research back to the very audience it’s about.

Then, Guillermo, together with the experts, builds a system for publishing interactive research reports instead of endless PDFs — to improve indexing and depth of engagement and to position the organization as an innovative expert structure.

Guillermo, catching his breath, spends several years connecting the organization’s websites for different target audiences into a coherent whole and helps launch three newsletters in different languages.

And Guillermo doesn’t stop there — he builds out an events system that fits within the organization’s broader communications, designed to engage both institutions and the general public.

And then he connects all of it.

What does Guillermo's work look like inside the organization?

On the one hand, his job is to bring experts into this new world. Not just explain where things go and how the CMS works, but to actually influence the structure of the final knowledge products, their format, sometimes their tone and language.

On the other hand, constant work with the people responsible for communications: helping them get to grips with new tools, developing channels, and building processes together.

And everywhere, Guillermo is a little bit of an impostor. And everywhere there is friction.

His mission is to exist between systems that would otherwise struggle to talk to each other, to create the kind of project, technical, and communications infrastructure where the knowledge and expertise of the vampires experts and researchers doesn’t just exist, but becomes accessible and travels.

Through channels, formats, platforms, and languages. All of it, so it can be engaging, accessible, and useful.

Guillermo is a servant. A servant of the goals and mission of an expert organization that wants its accumulated knowledge to actually make a difference.

The Seven Principles of Guillermo — seven principles for building infrastructure

1. Learning goes both ways

This position requires constant movement in both directions. Guillermo doesn’t just show up with nice slides explaining how everything should work from now on — he also spends hours explaining how the new CMS works, why the newsletter exists, and how the newsletter actually functions.

And at the same time, he is deep in the other direction: learning how the research is structured, how partner organizations operate, what the expertise actually produces.

Guillermo is a citizen of two worlds. And in both of them he’s, well... Guillermo.

2. Challenge and being challenged are part of the job

People always push back on Guillermo. And rightly so.

He disrupts established workflows and asks uncomfortable questions. What are you planning to do with this PDF? How are you planning to reach people from immigrant backgrounds with teenagers at home? What do we do with the data showing low levels of trust in Finnish media among people with immigrant backgrounds?

And then there are the other kind: why is the conference title three lines long if nobody’s going to read it, why does communications get brought in after the fact instead of before, can we let go of a little bit of expert control if that’s what it takes for anyone to actually hear us?

It’s constant advocacy, argumentation, legitimisation. And sometimes Guillermo is wrong. When that happens, he accepts it — and rebuilds. Being open to challenge in both directions isn’t a vulnerability.

It’s just part of Guillermo’s life.

3. Collecting signals from everyone

The expert owns the expertise. The communications person arranges communications. The audience deals with whatever actually reaches them.

Guillermo’s job is to collect signals from everyone: what the audience is saying, what the stakeholders think, what the researchers and experts are struggling with and hoping for, and what isn’t working on the communications side. Collecting that data, analyzing it, synthesizing it. Guillermo needs to be good at this.

4. Consistency

The strongest temptation in this position is to constantly change things. New tool, new format, new approach.

Guillermo has to know that changes don’t work immediately, that any new elements of infrastructure need time. A newsletter needs months to find its audience. A CMS needs six months to become a habit. To understand whether something is working, you have to give it time.

5. Translate, don’t lecture

The quickest way to kill a conversation is to speak in technical language. Sometimes, the only way to explain how channels and platforms connect is to draw it on a piece of paper. Not because colleagues don’t understand — but because abstraction doesn’t work when what’s needed is a decision. Guillermo’s job is to translate, not to educate.

6. Protecting everyone from everyone

The contractor building your website speaks their own language, usually calibrated for entirely different clients — business, all of that. The expert speaks their own language. Management speaks the language of strategy, deadlines, and budgets.

And here Guillermo’s job isn’t just to translate and connect — it’s to protect the organization’s interests in front of the contractor, protect the contractor from the organization’s chaos, and make sure the actual content doesn’t get lost somewhere in the middle.

7. Building legitimacy — permanently

Nobody is going to explain on Guillermo’s behalf why he’s needed. Eventually, everyone will accept it and believe in it. But at the beginning, the experts see someone who overcomplicates their process and flattens their expertise by forcing it into templates. The communications people see a tech person sticking their nose where it doesn’t belong. The IT specialists think he’s a strange and not particularly sharp marketer. Management sees a line item without an obvious result tomorrow.

Legitimacy in this position isn’t given — it’s built constantly, through results, through the language Guillermo uses to describe his own work, through the ability to show the connection between what he does and what the organization actually cares about. This isn’t self-promotion. It’s the condition for the function’s survival.

Final thought

Did it seem like Guillermo was a therapeutic device — a way to make it easier to talk about the in-between nature of this role without it getting too personal? You weren’t imagining it.

This role often has no name. It’s hard to find a professional community around it; there are almost no professional events for it, and no ready-made job description is available anywhere. But it exists, and it needs to exist — in every expert organization that is trying to make its knowledge go somewhere and change something.

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Keep chewing until nothing remains but a recognizable, safe paste.

This assumption that audiences can’t handle complexity lives inside most organizations that work with knowledge and expertise. And it shapes everything: the communication strategy, the formats, the tone, and the language.

False Foundations

This assumption replicates itself endlessly. Here are a few titles of articles, posts, and YouTube videos I’ve come across:

• “Simplify Your Language: Effective Communication Skills”.

• “Tips for Simplifying Content Communication”.

• “The Power of Simplicity in Communications”.

And there’s even a theoretical backbone for all this — the Knowledge Deficit Model.

The idea that people are skeptical of science, expertise, and new knowledge simply because they don’t know enough.

In its extreme form, this doesn’t just give knowledge producers a comfortable position of authority; it assumes that, by simplifying, we graciously allow the audience (fragile and limited as they are) to finally begin to understand something.

By the way, there is no evidence that this model is actually true.

There is, however, evidence that simplification actively harms sophisticated readers. And if we allow for the possibility that smart people exist in our audiences too 😉 — then the goal isn’t “make it simpler.”

We need to make it relevant to a specific level of understanding. Which means: different for different people.

Because communication isn’t the transfer of knowledge. It’s the creation of a condition in which a person wants to (and can) do something with that knowledge.

From the Field

Complex content isn’t just about science.

Years ago, when I was working with cultural institutions, we had an idea: let’s make a big festival of contemporary poetry. Really big. Really contemporary. I lost count of how many times I heard — man, this is too niche, too strange, nobody’s coming to contemporary poetry.

And? A one-day festival. Five thousand people. Offline. Not Coachella. But also not Bieber on the stage.

Another example. We run a media project about Finnish culture and society for the Russian language minority in Finland — helping people navigate integration into Finnish society.

The format: longreads only. Topics like “The Concept of Love in the Work of Tove Jansson,” “The Finnish Sense of Humor,” “Parliamentarism in Finland,” “Inclusion in Theatre,” and “Psychotherapy in Your Native Language.” Most of the articles are written by experts, not professional journalists. Only longreads. Sometimes without images 😎.

Thousands of email subscribers. Interactive articles with a lot of responses. People read and engage, writing feedback and comments.

We organized open discussions of research, a one-day lecture festival for 3,000 visitors, and academic and professional conferences with open, free access to the general public. And we keep acting surprised - why are people interested in complex topics, why are the rooms full, why do real discussions actually happen?

How to communicate complexity?

1. Build familiar and engaging infrastructure

I believe that what repels audiences isn’t complexity, it is the “I don’t know how to be here” feeling.

So the challenge isn’t to simplify the content, but to make it feel like somewhere the audience has already been. I’m talking about form and the interface of knowledge.

With the contemporary poetry festival, we didn’t experiment with avant-garde formats or innovative participation models. We gave it a familiar shape of a big music festival. Big stage, large screens with video art, food court, lounge areas. We promoted it like a music festival — posters with names (often unknown to people), poets’ faces, social media, backstage reels, etc.

With the longreads, we built a familiar interface of a modern media outlet. Not cutting-edge e-zine design, not typographic experimentation. Clear UX, predictable navigation. Everything so that reading about the “concept of belonging” (of all things) felt natural and comfortable.

Complex content in a familiar container.

2. Engagement and pipeline of interaction

Audiences have no problem discussing the future design of their city or the results of a recent research project — if it’s a real dialogue with a real possibility to participate. I write about this in the context of public events here.

We should think of communication not as a single act, but as a system, a pipeline of repetitions, multiple touchpoints, and participation. We need room for long-lasting conversation, to tell different stories around our expertise. And our audience needs room to think, discuss, disagree, and decide.

We all sit on our thoughts before posting a comment under an article. Our audience deserves the same freedom.

This works both offline and online: give people space to think before the event (newsletters, surveys, social media), give them depth when they arrive (presentations, materials, context), and give them a real chance to be heard (discussions, group work, Q&A).

3. Explain, don’t simplify

There’s a difference between simplifying and explaining. If simplifying removes complexity, explaining makes it accessible.

Use complex terms — but define them. Ask difficult questions — but give people time and space to think. Expect sophisticated feedback from our audience.

Online, this means: links to sources and further reading, interactive formats, explanatory cards that break down specific concepts, and separate materials that unpack complex elements in depth.

We should not protect our audience from complexity, but build the conditions in which people can meet it.

One final thought

I’m sure you have your own examples and ideas to add — the comments are open.

But here’s my closing thought for all of us working in knowledge communication: treat our audience as capable. They are smart. They can handle complexity.

Our job isn’t to simplify from a comfortable position on a high hill. It’s to accept that our real task is to build systems of knowledge distribution and engagement that are genuinely inviting. Inviting to dialogue. Inviting to interaction. Inviting to knowledge itself.

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Most panel discussions at conferences are designed like a fashion show. You’ve been there (at conferences, of course) so you know the picture.

There’s a stage where something interesting is happening. There’s an audience watching. The line between them is clear and almost impossible to cross. You can look. You can react - clap, smirk, doze off. But influence what’s happening? No chance.

And this isn’t just on the organizers (that part is obvious, it’s just easier to build it that way). The speakers are complicit too — happily talking to each other while the audience sits there, checked out or scrolling their phones.

Recently, I was at a conference on journalism and media trust. I sat through several panel discussions and public talks where the speakers (sharp suits, impressive credentials) spent an hour and a half talking to each other. And from where I sat, they seemed to be enjoying it. Which is sad.

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What’s wrong? Pretty much everything

No engagement

Most panels, research presentations, and public engagement events are designed for one-way communication. Information flows from the stage to the room. There’s no challenge to what’s being said, no pushback, no real friction. Without dialogue, nothing develops (not the ideas, not the audience, not the experts themselves).

The same experts, the same perspectives

Talking about journalism? Here are four media professionals on stage. Which means, in all likelihood, four roughly similar takes on the same problem.

One-off by design

The quality of participation comes through practice. One event doesn’t build anything. People need repeated exposure to a format before they know how to use it. A single panel discussion doesn’t teach an audience how to engage. Running public dialogues connected to our own research activities, we’ve seen it directly: the format gets better, and so does the depth of participation — from event to event, on both sides of the room.

Moderation as control

At best, moderators manage time and keep things on topic. That’s not moderation — that’s traffic management. Real moderation creates conditions for participation, brings different voices into the room, and holds space for productive discomfort.

What works?

Expert diversity

The choice of experts is not just filling slots with names and titles. It’s a decision that shapes what kind of conversation you’re going to have. Four professionals from the same field will most likely give you four versions of the same worldview.

Real diversity means different forms of expertise, not just different opinions. If you’re discussing immigration, don’t just bring researchers and policy people. Bring a government official, a human rights lawyer, a journalist, and a teacher working with children with immigrant backgrounds.

Each of them knows something the others don’t, and that’s what makes the conversation impossible to predict, which is exactly the point.

One more thing worth building in deliberately: a lived experience speaker, someone who has been through it. A person with direct personal experience of the topic brings a category of knowledge that no amount of research can replicate. And they often say the thing that shifts the entire conversation.

Moderation as participation design

A moderator is not an extra expert. And definitely not the star of the evening.

I’ve seen public talks where a well-prepared moderator spent twelve minutes on an opening statement and asked questions as if the microphone was their personal stage. That’s not moderation. That’s a panel with one more panelist who controls the mic.

Moderation is a function; its job is to create conditions that allow different people to speak. A good moderator ensures participation, enforces the rules of engagement, limits those who dominate, and keeps everyone in the room feeling safe.

Rules and formats

Give speakers enough time to establish positions and create some tension, but no more than half the total time. At least the second half belongs to the room and dialogue. This is when the audience is ready: they’ve heard enough to have questions, disagreements, or something to add. That’s the moment to open it up.

A few formats that help:

Erätauko / Time out dialogue: a Finnish dialogue method built on a simple but radical premise: the goal is not agreement, it’s understanding. Participants speak in turn, without interrupting or trying to convince each other. There’s no debate, no winning. The method is specifically designed to invite people who don’t usually take part in conversations, which makes it particularly useful when you want the audience to speak. Works well as a structured closing segment where the room speaks on equal terms with the experts.

Chatham House Rule: what’s said in the room can be shared, but not attributed to anyone. Frees up both speakers and the audience. People say things they wouldn’t say on the record.

Articulate your rules: whatever format, tool, or rules you choose, the moderator needs to explain them clearly to everyone in the room. The rules are better not just announced but also displayed on screen and/or printed on cards left on the chairs. And the rules need to be enforced. Ignoring them undermines the format, the event, and the organizers.

Venue and setup

The physical space sets the rules of participation. Experts on a stage elevated above the room make one thing clear before anyone speaks: some are here to talk, others to watch. The space dictates the roles.

Remove the stage. A stage is a symbol of power. Can’t remove it? Choose a venue where the stage doesn’t rise above the audience.

Theatre-style seating works poorly. A semicircle around the speakers works better. People in the room should be able to see not only the speakers but also each other.

The goal in all of these is the same: everyone in the room should feel like a participant in something, not a spectator at something. That feeling is also produced by the physical environment. Where people sit, whether they can see each other, and whether there’s a clear hierarchy built into the layout.

One more thing that’s easy to underestimate: venue quality signals to everyone that the conversation matters. Good speakers are more willing to show up and then to talk about where they showed up. And the audience arrives already feeling that what’s about to happen is worth their attention. That’s not vanity. That’s the infrastructure of dialogue and commitment.

A few more things that matter

Don’t close the loop: The conversation doesn’t end when people leave the room. Send a follow-up: a short summary, key themes that came up, and a feedback poll.

Build a series, not an event: Participation is a skill. It develops through repetition. A single public talk doesn’t teach an audience and speakers how to engage. The second event in a series is always better than the first. People know what to expect, they come with questions already forming, they trust the space and you a little more. If you’re serious about engagement, you’re serious about continuity.

Feed people! Brains need fuel. Sound trivial? Food and drink before or during an event changes the social dynamics of the room - people talk to each other, the atmosphere loosens, and the threshold for participation drops. It’s one of the cheapest and most reliable tools available.

Photography and a way out: Tell people at the start that photos will be taken. Then give those who don’t want to be photographed a sticker - something visible they can wear so that whoever is selecting photos afterward knows not to include them. No awkward conversations, no opt-out forms. Just a simple system that respects people’s choices without making it a production.

Your event is not a final destination

A well-designed public event is worth more than the hour it takes. But only if you treat what happens before and after as part of the event itself.

Before the event, don’t just announce it. Build context. Use your channels (social media, newsletters, blog posts, whatever you have) to introduce the topic, present the speakers, and show different angles of the question you’re going to explore. Give people something to think about before they walk in the door.

After the event, a post with photos and thank-yous is not enough. Write something substantive — not a recap of how well everything went (we can leave that energy for LinkedIn for now), but something that carries the conversation forward. The sharpest questions that came up. The things that didn’t get answered. The tension that stayed in the room. Publish it, send it, talk about it.

This is how a single event becomes part of something larger.

Every touchpoint before and after reinforces the same conversation, reaches the same audience through different moments, and builds the kind of familiarity that turns a passive audience into actual participants. Done right, your public talk doesn’t just generate knowledge and experience in the room, but pulls the right people into an ongoing dialogue between your organization and the people it’s trying to reach and engage.

Let's talk about engagement in the process of producing new knowledge, expertise, and research.

Mr. Burns: Where did I go wrong? I made all the right moves, didn’t I?

Burns’ Underlings: Yes, sir. Absolutely.

Mr. Burns: Oh, I see it now — you’re nothing but a bunch of yes-men. I was making all the wrong moves, and you were too gutless to tell me!

Burns’ Underlings: Yes, sir. Absolutely. Every move the wrong one.

What About Unsafe Engagement?

We are comfortable with peer review. Some of us are even ready for critical discussion within our professional community. But when it comes to real public communication — reaching different audiences, going beyond the familiar circle — we often prefer not to take the risk.

And honestly, why would we? Comfortable formats are comfortable. Friendly audiences are friendly. We are, after all, experts — and we more or less share the same assumptions and the same ethics of discussion. And if we can add a few glowing comments from the last event to the annual report (alongside the pleasant numbers of attendees) — that’s a win.

We like engaged people. Engaged people of a certain, agreeable type. We don’t like cynics. We don’t like those who push back, question our conclusions, methods, or framing. We don’t like people who don’t trust us.

But real engagement means being willing to be questioned and to hear something you didn’t want to hear. To get the questions your colleagues would never ask (because they don’t see it from that perspective, or because it’s simply not polite or acceptable in a professional setting).

We say we want engagement. Then we design everything to avoid being challenged.

Difficult audiences, difficult questions, difficult relationships

A comfortable audience (the one most of our engagement methods and metrics are built around) does not test our expertise, your methods, your organization, or your expertise.

Willingness to engage publicly with a difficult audience, with uncomfortable opponents, with critics gives (or at least can give) quite a lot:

• It tests whether our knowledge actually holds up. Peer approval confirms what we already believe, but a skeptical audience finds the gaps we stopped seeing.

• It forces clarity. We can’t hide behind professional jargon when the person across from you doesn’t share your assumptions. If you can’t explain it to someone who disagrees, you probably don’t understand it as well as you think.

• It gives you questions your colleagues would never ask. People outside your field work from a different set of assumptions.

• It filters for real value. Having to explain why your work matters turns out to be a surprisingly effective way of figuring out whether it actually does.

• It builds real credibility. Anyone can present to a friendly room. Being challenged in public (and holding your ground, or changing your mind) is what actually earns trust.

• It generates feedback you can use. Applause tells you nothing. Pushback tells you where the friction is, what’s missing, and what landed wrong.

• It expands your reach, because comfortable audiences are already yours.

We are the ones who radicalize the feedback

In 9 out of 10 cases, the harsh question from the audience, the uncomfortable comment under your research announcement, the pushback you didn’t expect — these are not a sign that your audience is dangerous. They are a sign that your audience has no other way to be heard.

It is an infrastructure problem.

Here is what working with sensitive content looks like in practice. We conduct research on immigration and integration, focusing on questions of trust in institutions and attitudes toward difficult social and political topics. And we build engagement infrastructure around it: public events before the research begins, interactive articles with space for extended commentary, presentation events after publication in formats that invite real dialogue, including public talks with both researchers and community members. Not once has anything extraordinary happened. There was dialogue. Sometimes disagreement. Sometimes difficult questions. Always within reasonable bounds. And always useful.

What we found is simple: when people have no channels for critical feedback, or only sometimes radicalize in form.

When you build a system of multiple touchpoints and formats, difficult questions find space.

Our fear of difficult audiences is a consequence of our own short-sightedness. We treat engagement as a one-off event rather than a system. We turn the single annual public event or the occasional post into a space where people can finally say what they think — and then we’re surprised when it gets loud.

There are no difficult audiences or topics that are too sensitive (in 9 out of 10 cases). There are only weak engagement approaches - unsystematic, done for the sake of ticking a box.

Formats and principles to be challenged

Our engagement efforts should follow the pipeline of knowledge production and use (for a deeper look at what that pipeline looks like — Building Platforms for the Full Lifecycle of Knowledge):

Before: Engaging your audience before you produce anything helps you tune your assumptions, surface blind spots early, and often build legitimacy from the start:

• Public discussions of research questions and research design, hypotheses, and goals before the study begins

• Focus groups and community consultations with target audiences

• Open calls for input: what questions matter to people, what they want to understand

• Pilot formats: testing framing (and sometimes language) with real audiences before publishing

During: Bringing audiences into the production process is uncomfortable. It is also useful. It stress-tests your thinking while there is still time to act on the feedback.

• Interim publications and updates on the process

• Interactive formats that invite response at key moments — surveys, open questions, structured feedback

• Consultations with community representatives or critics during drafting

• Verification sessions: sharing preliminary findings with non-expert audiences to test clarity and relevance

After: This is not the end of the process, but the preparation and the beginning of the next knowledge production cycle. And that is exactly how it should be treated. The photos and numbers in the final report are a nice bonus.

• Public presentations of results in a dialogue format. Structured dialogue methodologies (such as Timeout) offer a useful model: equal participation, experience-based discussion, and encounter between different perspectives.

• Public talks combining expert voices with representatives of the general audience/community audiences being studied

• Interactive reports and articles with space for extended public commentary

• Structured feedback collection: what landed, what didn’t, what was missing

• And, please, turn on your comment threads.

And then feeding that feedback back into the next production cycle as an input.

A few principles across all three stages

Regularity reduces radicalization. When people have one channel and one moment to be heard, they use it loudly. When there is a system of multiple touchpoints, the pressure is distributed, and the feedback form becomes constructive.

Different formats for different audiences. A public talk works for one group. An interactive article works for another. A structured survey works for a third. There is no universal format for engagement — only formats that fit or don’t fit a specific audience and moment.

Repetition is not redundancy. The same finding, communicated in three different formats to three different audiences, is not the same act repeated. It is translated and packed.

Moderate. And invest in it. Bring in a professional moderator for public discussions. Build transparent, clearly announced moderation rules into your comment sections. Engagement is not about letting everything go. It is a managed and open process.

So, what now?

We are not Mr. Burns. We don’t have trapdoors above a pit of hounds for inconvenient visitors. And our audiences are not the Simpsons — not a captive crowd with nowhere else to go.

At the same time, I’m not calling for naivety either.

I’m calling for openness. For not being afraid. And for building an actual engagement system — not a series of rare, often forced attempts that disappoint us precisely because they are rare and forced.

A single annual public event is not engagement. An occasional post with comments turned off is not engagement. A report sent to people who already agree with you is not engagement.

Build the infrastructure and the system. Make it regular. Make it multi-format and multi-touch. Make it open to people who will not simply nod.

The cynics, the critics, the uncomfortable questions — they are not the problem. They are the signal that your knowledge is reaching somewhere new. And challenged.

And that’s the point. Yep?

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Imagine yourself as a supervillain. Not a sad underachiever like Voldemort, who couldn’t even take over a school, but someone like Palpatine or Sauron. What do they have in common (besides obvious mental health issues and a love for lightning, fire, and vaguely phallic symbols — lightsabers and very, very large towers)?

They approached things systemically. They built infrastructures instead of chasing some scrawny teenager around.

So when we talk about how to make knowledge and expertise more accessible, more engaging, and actually impactful, we’re not going to chase the boy with a scar (his time will come when we get to content, language, and all that — in some other piece).

Instead, let’s talk about systemic and infrastructural solutions that can help organizations, sectors, expert institutions, and universities work with new knowledge and audiences more effectively and deliberately.

In his article The Research Industry Faces Its Innovator’s Dilemma, Ibukun Taiwo writes:

Essentially, knowledge creation centers must evolve into knowledge sharing and decision-support entities. Their future relevance depends on whether they can become high-leverage distribution and decision infrastructure. This means treating Packaging, Distribution, Adoption, and Consumption not as afterthoughts, but as design problems, each requiring its own logic, incentives, and skill sets. Often this won’t look elegant. It will look like stitching pieces together until ideas actually move and decisions shift. But that is how change happens in the real world.

I fully agree with this. And this applies regardless of the audience or the type of impact we are talking about.

Whether the audience is policymakers and decision-makers, funding organizations making allocation decisions, or broader public audiences, the challenge remains the same: not just producing knowledge, but making it move to where it can change something.

The lifecycle of knowledge (if you care about more than just producing it)

If we look at any piece of knowledge or expertise, it doesn’t just appear and exist. It moves through a series of stages:

A lifecycle of knowledge begins with production — the creation of new knowledge (research, insights, and expertise). This knowledge is then translated: interpreted, broken down, reframed, and grounded in context and experience so that it becomes understandable and related for different audiences.

From there, it moves into delivery, where it is structured and distributed through appropriate channels, formats, and moments of use. Engagement follows, as people interact with it: recognizing its relevance, connecting it to their own reality, and understanding what it might change.

Then the application stage - when knowledge enters decisions, processes, projects, and actions.

Then feedback stage - as a complex return of experience: what individuals tried and struggled with, how institutions used (or failed to use) the knowledge, what constraints made application difficult, how ideas were adapted or reinterpreted, where they failed, and what unexpected effects appeared.

This feedback feeds into renewal — refining, expanding, or challenging the original knowledge and starting the cycle again.

Platform-based approach

Let’s first define what a platform means in this context.

A platform is an operational system that carries knowledge through its full lifecycle — from production to translation, delivery and engagement, to application, feedback, and continuous renewal.

It is a system that combines several elements:

1. Infrastructure: The underlying systems that make knowledge persistent, accessible, and connected: digital platforms (websites, databases, repositories), content management systems, and so on.

2. Processes. The ways knowledge is created, translated, distributed, and updated over time: research and knowledge production workflows, translation and adaptation pipelines, feedback collection, and iteration cycles

3. Formats. The forms through which knowledge is shaped and delivered to different audiences: reports, articles, explainers, visualizations, toolkits, templates, events…

4. Interactions. The ways people engage with knowledge and with each other around it: discussions and comments, surveys and interactive content, collaborative work (e.g. workshops, co-creation)

All these elements are connected through three principles:

1. Alignment. All elements (knowledge production itself, the content derived from it for different audiences, formats, events, tools, and more) are aligned around a shared strategic focus.

2. Differentiation. Knowledge is not delivered as a single stream, but translated and structured for different audiences. Different entry points, formats, and infrastructure elements are designed for different groups (professionals, institutions, policymakers, and broader publics).

3. Integration. Infrastructure and the rest of the ecosystem are not separate layers. Content, engagement, tools, and applications are connected, creating a continuous environment rather than a set of isolated outputs.

A platform-based approach is a practical response to a core challenge of modern knowledge industries: reaching relevant audiences and becoming part of their decisions and actions.

Types of platforms

There are platform-based solutions that cover parts of this lifecycle, and that alone is a significant achievement, requiring substantial effort and coordination.

1. Knowledge Production Platforms, where knowledge is created and circulates within expert communities

Platforms that accelerate the production of knowledge and make it accessible within professional communities, effectively covering the Production phase and partially the Feedback phase. Here are some examples:

ArXiv. An open-access repository for preprints in physics, mathematics, computer science, and related fields. ArXiv accelerates the production and circulation of knowledge before formal publication.

SSRN. A global repository for early-stage research in social sciences, economics, law, and the humanities. It enables rapid dissemination of working papers and ideas, allowing knowledge to circulate, be discussed, and evolve within expert networks before formal institutional validation.

And of course, ResearchGate and GitHub.

2. Translation Platforms, where knowledge becomes understandable

Platforms that break down complexity, adapt knowledge for different audiences, and construct (or support the construction of) narratives. They operate primarily across the Translation and Delivery phases.

Our World in Data. A platform that transforms academic research and datasets into accessible explanations and interactive visualizations on global issues. OWID translates complex data into structured narratives and visual formats, making it understandable and usable for media, policymakers, and the public.

The Conversation. A publishing platform where academics write for a general audience, supported by editorial teams.

Vox / McKinsey Global Institute. Editorial platforms and research units focused on explainers, deep dives, and synthesis of complex topics. They take fragmented or technical knowledge and turn it into coherent narratives, helping audiences understand not just what is happening, but why it matters.

3. Engagement and Feedback Platforms, where knowledge meets its audience and is reshaped through interaction

Platforms that create interaction, enable participation, and generate feedback. These are ecosystems where the audience is no longer just a recipient of knowledge, but becomes a contributor through discussion, problem-solving, and distributed input. They primarily operate in the Engagement and Feedback phases.

Zooniverse. A citizen science platform where volunteers help researchers process and classify large datasets. Engagement here is not just interaction; it contributes to research outcomes.

Culturalist.fi. A media and engagement platform within a research-driven expert organization, combining content, events, and interactive formats for a general audience (Russian-speaking immigrants in Finland). Included here as a first-hand case: developed and operated within Cultura Foundation, where I am directly involved in building and evolving the platform.

4. Application Platforms, where knowledge becomes actionable

Platforms that turn knowledge into tools, embed it into workflows, and directly influence decisions. They operate primarily in the Application phase. Party-affiliated think tanks may operate closer to the application layer, especially when they are directly involved in policy design and decision-making processes.

Cochrane Library. A collection of systematic reviews and evidence summaries used in healthcare decision-making.

Climate-ADAPT. A platform supporting climate adaptation planning across Europe, providing data, case studies, and decision-support resources.

Platform of the full cycle — utopia or strategy?

Can you build a platform with infrastructure, processes, formats, channels, and projects around it that actually covers the full lifecycle of knowledge within one organization (or, if you’re feeling ambitious, an entire field)?

Maybe. Hard to say. If you’ve seen it done properly, I’d like to see it.

But in practice, that’s not how it works. No one builds the full system at once. It’s always iterative. Most organizations already operate somewhere in this lifecycle. You don’t “launch a platform”, you build and connect parts of the cycle, adding missing layers over time.

In many organizations, the first part already works: production → translation → delivery.

Research is produced, turned into content, and distributed through platforms and channels. Editorial practices adapt knowledge for different audiences. Formats evolve. Collaborations extend reach.

The next step is delivery → engagement. Knowledge needs to become interactive. This includes interactive content, events as conversations, community or panels development, co-design formats, and feedback loops. Different audiences require different formats. There is no single “engagement layer”.

The hardest transition is engagement → application. To move forward, knowledge needs to become usable: tools, playbooks, frameworks. It needs to enter real contexts through working groups, partnerships, and direct work with organizations, institutions, and policy-makers.

Finally, feedback, and the key is not just collecting it, but integrating it back into research, workflows, and decisions.

Let’s wrap this up

First, I promise this is the last piece of this size. But it felt important to articulate the framework behind a platform-based approach.

We’re not Voldemorts obsessing over what kind of wood our wand is made of. If we want anything resembling systemic development, we need to think and act strategically.

That means being a bit more like Palpatine (without getting carried away, and remembering it took him years to build anything), and like Sauron — building systems: infrastructures, collaborations, side projects, and initiatives, all connected by one thing — a drive for influence and change.

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This piece is inspired by ’s article “Public Engagement Is Good for Your Research” and by my own experience working inside knowledge-driven organisations, where research, expertise, and real-world practice constantly intersect.

“Every profession is a conspiracy against the laity.”

— George Bernard Shaw

Working in an expert organisation - one that is involved in both research and real field practice - attending conferences, reading reports, and talking to colleagues, I often find myself in a loop of cross-validation and professional biases that reinforce each other.

The development of any expertise (from research to practice) accumulates not only knowledge, but also “isotopes” of bias - stable residues of experience, feedback, and professional frameworks that over time settle into the way we think and operate. With constant exposure (and without mechanisms to remove them), they accumulate and begin to change the structure of the system itself, triggering an erosion of expertise.

The way we design research or expertise, interpret data, write reports, and make decisions across academia, think tanks, NGOs, the public sector, and advisory work — all of it carries the imprint of accumulated biases and biased practices.

In research, it shows up in how we frame questions and interpret results. In consulting, in how we structure problems and recommend solutions. In NGOs and policy work, in how we define what matters and what gets ignored.

Today, we’ll set aside the broader conversation about critical thinking (and even expert ethics) and focus instead on systemic causes.

Six Drivers of Expertise Erosion

1. Self-sealing expertise production

The process of producing new knowledge and expertise often seems to rest on a basic assumption: the producer of knowledge (the researcher, expert, consultant) already operates at a level above the surrounding reality. Above the client, the audience, and the field being studied. After all, that’s the reason I am the expert, the one entrusted to carry out this important task: research, analysis, the search for truth.

At the end of the day, I’m the expert.

From the top of this ivory tower (some higher, some lower), we - consciously or not - tend to look at what’s in front of us from above and are often busy keeping outsiders away from both the process and its results.

How many scientific or expert conferences do you know that are designed not only for professional communities and stakeholders, but also for a broader audience?

How many researchers are willing and actually do engage in public talks, presentations, and dialogue beyond academic or expert circles, intentionally investing in engaging communities or the general public?

This approach is exactly what locks us into a loop of validation, making us forget that:

“People outside the university often see things that people inside it miss, not because they are smarter, but because they are working from a different set of assumptions.” — , Public Engagement Is Good for Your Research

This statement applies far beyond academia - to experts, consultants, public service managers, policy practitioners… pretty much anywhere.

2. External forces

In this section, I bring together the forces and constraints that surround an expert, a researcher, or any knowledge factory and systematically shape the kinds of knowledge produced.

This is not about direct control (although that exists, too). It’s about something more subtle:

which types of knowledge are rewarded and which are not.

Career incentives

If we try to formulate this seemingly obvious factor more clearly, it would sound something like this: in the knowledge and expertise industries — perhaps more than anywhere else (with the possible exception of politics) — alignment with policies and strategies, established norms and traditions, and overall value fit often has a stronger impact on careers than quality or actual impact.

Promotion, publication, and recognition are not distributed in a vacuum. They pass through a filter: alignment with dominant frames.

As a result, careers become dependent on reproducing the existing frame rather than expanding it. And the knowledge system starts chasing its own tail, reproducing itself and slowing down renewal.

Funding and market logic

Accepted and recognisable narratives (along with expected outcomes ) are often a more reliable way to secure funding or clients than unconventional approaches, new questions, or non-standard solutions.

This applies both to grant funding (thematic open calls, funders with their own agendas) and to commercial expert and research work, where clients and the market begin to shape the “rules”, the “topics”, and sometimes even the expected conclusions.

As a result, the scope becomes constrained by what is considered fundable, acceptable, and legible.

Closed stakeholder loops

In many fields, our decisions, interpretations, and even the agenda itself are shaped within a relatively small circle of actors: funders, policy-makers, leading experts, institutions, and boards.

They are the ones who define the questions, validate the answers, and translate results into decisions.

Rarely are communities or the general public invited to this table. And when they are, it is often as sources of information to be used, not as participants in the process.

The system of knowledge and expertise production is not just influenced by stakeholders; it is defined by a relatively closed circle of them. And new knowledge is most often validated by this same circle, rather than by reality itself.

As a result, knowledge production is not pushed outward, but pulled back into familiar patterns.

3. Efficiency trap of expertise

Expertise is often perceived as the result of successful experience. Once we have proven (at least to ourselves) the validity and value of our work, our research, or our solutions, we begin to lower the level of challenge we apply to ourselves, to our methods, to our own expertise.

We return to the same approaches, assumptions, and solutions that once worked, repeating them again and again, while the world around us keeps changing.

What once made us fast, effective, and “right” can, with each repetition, become less relevant, less connected to reality, and increasingly tied to our own internal frame of reference.

Each cycle without reflection, without challenge, without adjustment moves us further in the same direction — toward gradual blindness, and toward expertise becoming sealed within the biases created by its own past success.

4. Path dependency and overfitting

The efficiency trap is reinforced by another systemic factor: dependence on the past. Past research, the expertise we’ve applied, and the solutions that once worked all shape the models we use today. They influence how we define problems, what questions we ask, and what we consider worth investigating.

As a result, new knowledge is often produced in a way that confirms what we already know or believe we know.

This is where the idea of overfitting becomes useful.

In machine learning, overfitting describes a situation when a forecaster tries to make their prediction model (or hypothesis) perfectly match past data (Philip Tetlock), and it becomes less useful for understanding the future.

The same dynamic appears in research, consulting, and policymaking. Instead of evidence challenging our assumptions, evidence increasingly confirms what we are already invested in believing.

And the further we move along this path, the easier it becomes to prove ourselves right rather than to question whether we are.

5. Formats and practices shape knowledge

Let’s look at what a typical “output” actually looks like in practice: • a publication • a PDF report on a website • a presentation at a professional conference

If you have the time, energy, or support from a communications team, you might go a bit further: • a few interviews or expert comments in professional media • a blog post that turns into social media content

And if you really push it, maybe a public event.

Familiar formats don’t just limit engagement and impact; they predefine what can be said and how: the same structures, the same types of conclusions, the same ways of framing and phrasing. The same approach reproduces itself within established infrastructural boundaries.

Why does this remain unchanged? Because “this is how it’s done.” Because these formats are funded. Because they are legible to us — the expert community. They are easier to approve, easier to sell.

We produce knowledge and package it into formats that are not neutral. Over time, these formats become a framework in themselves, defining what can appear at all and keeping us within a familiar comfort zone.

Conclusion and What Comes Next

Expertise erosion happens through the reproduction of the same patterns and formats and through the absence of infrastructure for renewal, reflection, and intentional engagement.

Yes, we can point to critical thinking, ethics, the ambition to be more open-minded, maybe even write a few more blog posts for your organisation’s Facebook page.

But what interests me is something else: what structures, practices, and formats do we need so that knowledge stays alive, keeps evolving, and actually reaches the place it was meant for. The real world.

More on this — in next week’s piece.

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You know, Dumbledore always annoyed me a bit.

A carrier of ultimate wisdom, deep knowledge, and the most important secrets across seven books and eight films - and not once did he manage to actually explain any of it in a way that led to conscious action. Manipulating a child doesn’t count!

His problem (besides the whole manipulative mindset, which isn’t today’s topic) is simple: he couldn’t translate knowledge. He couldn’t explain things in a way that even Harry (already exhausted from messy, unstructured school learning) could actually understand and relate to.

And Harry (we assume) is his key audience. The one whose decisions and actions Dumbledore supposedly wants to influence.

Most of the knowledge we produce never becomes anything

Dumbledore reminds me of most companies and organisations built around knowledge and expertise.

We run research (academic or applied), we formulate our expertise, we build projects based on new knowledge, and launch initiatives meant to create change — inside a business, within an organisation, or in the outside world.

And we expect them to work.

This happens across expert organisations, research institutions, and knowledge-intensive businesses — anyone who, in one way or another, produces new knowledge.

It gets published, shared, sometimes even discussed, but rarely used. And even more rarely does it lead to the kind of change it was supposed to create.

Very often, new knowledge simply doesn’t reach the people it was meant for, doesn’t inform decisions, and doesn’t lead to change in organisations, in industries, or in society.

I’ve been working close to this gap for years (across research, media, and public initiatives). And the more I see it, the clearer it becomes: the problem is not knowledge itself. It’s everything around it.

In the end, every respectable organisation, research institute, or consulting company has a special section on a website, filled with an endless graveyard of long, multi-page PDFs.

And I want to explore, together with you, what makes knowledge actually usable when everything around it is unstable, incomplete, and under pressure.

The PDF Graveyard and Vague Explanations

There’s a whole class of explanations we fall back on when new knowledge (solid research, real expertise, something genuinely valuable) goes unnoticed and leads nowhere:

And my personal favourite (perfectly phrased despair!):

This is a real line I once heard in a conversation with a former colleague!

We tell ourselves we just need to “explain better” or “get more reach.” But communication (at least in this simplified sense of polishing texts and chasing visibility) is not the problem. Or only a very small part of it.

When you work in resource-constrained environments, in small teams, this becomes even more visible.

We invest time and effort into producing knowledge, often assuming (arrogantly, and short-sightedly), that the mere fact that it is useful, important, and uploaded as a PDF on a website is already enough.

Or, at least, that's what happens next is no longer our responsibility.

Make it different

Let’s pause the broader idea of knowledge translation for a moment and talk about a few core principles I see (and try to implement in practice) that are necessary for knowledge, research results, and collective or individual expertise to become not just more accessible, but understandable and usable for target audiences.

1. Repetition is Your New Magic

We often talk about clarity. Much less often, about the fact that any knowledge, expertise, or complex information requires repetition and consistency.

If a better explanation were enough, most of this would already work.

Anything complex should be formulated simply: in one sentence — great. In two — still great. In a short, clear paragraph — also fine.

And it is exactly this paragraph that needs to be communicated everywhere, constantly, repeating it almost word for word for each target audience.

Without getting distracted by details, complexity, or our constant urge to add something more (you will always have a chance to expand later — but only when the person, the audience, moves further along the funnel of understanding and working with the information).

A large sociological study? One sentence — what the study is about. Second — the key finding. Third — what it means for your target audience and what value it brings.

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2. Build the Infrastructure

Defining and building the desired infrastructure, especially when you are not a large organisation, your technical capacity is limited, and your funding is limited.

But building infrastructure is a highly adaptive process that requires, first of all, strategic thinking and a systemic approach. In the end, you can always move in iterations.

In an expert organisation I’m involved with, we’ve been building an infrastructure over several years that includes:

• A dedicated media platform for one of the target audiences.

• An email newsletter of this media to build community and ensure delivery.

• Databases and their integration into media for feedback, surveys, and interactive formats (without which it is almost impossible to properly “absorb” complex knowledge, which requires reflection and dialogue).

• A system for publishing interactive reports online, with data visualisation and better indexability. And it is just easier to read!

Our investments of time, effort, and money were distributed over several years, moving step by step from one channel to another, developing solutions and connecting them.

3. Be Ready for the Long Journey

We allow ourselves not to understand, not to notice, not to accept something the first time. Allow the same for your audience.

And also allow yourself two things:

• not to rush and to be systematic

• your “new” knowledge to live longer

Building a systemic approach, infrastructure, giving time for translation and dissemination — all of this takes time. But the result is worth it: audience engagement, your knowledge being used as a basis for decisions, new funding, new clients, and a strong reputation.

This is a marathon, not a sprint.

4. Brand your knowledge

Any new knowledge (research results, expertise, etc.) is a product that should have its own target audience, value proposition, and language — including visual language.

Define the target audience of your knowledge. Is it experts? Experts and a broader audience? Decision-makers? Potential investors? A scientific or expert community?

Give it language (and different language for different audiences)!

This is a separate big topic — branding knowledge and expertise — and it deserves more than one article. But you can start already now: for example, by stopping the use of generic infographics made with Notebook LM (I really hate it!).

It doesn’t simplify perception. It is not unique. It does not differentiate you or your knowledge. It reduces its value and trust.

Don’t Be Dumbledore. Act Like Gandalf.

We all live in a world overloaded with knowledge and information (let’s ignore its average quality for a moment). Around us is an extremely competitive attention market.

And even if you are a small expert organisation, a consulting agency, or an underfunded research organisation, you still have a chance to create more impact if you start approaching this systematically.

Not just what happens during the research, but what must happen after, once you have that PDF with results or a new framework for your potential client.

Be like Gandalf — proactive, engaged, with a clear purpose, clarity in communication, and consistent effort.

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“Show me the meaning of being lonely. Is this the feeling I need to walk with?”

Backstreet Boys

Making things work? You might be very lonely

Leadership, solo entrepreneurship, solo building, and creative work are incredibly romanticized.

Look how inspiring Paulo looks, the artist spending many days alone in his studio. And Sophia, the programmer who doesn’t leave the house for weeks, hunched over in the glow of the screen, creating something important that will change the world. Jack, the leader of a small and ambitious team (of course united by one big goal!), working late, and then at night, at home, when his loved ones are already asleep (as always, they fell asleep before he came back), he still can’t sleep, thinking through the day that has passed and the day that is coming. And even Alex, working in a small NGO, tightly united like never before, keeps throwing himself into new challenges again and again.

These are the images we see in movies, books, and LinkedIn posts.

But very often, too often, behind all these images there is a long, dark shadow of loneliness. Personal and professional.

I think about this as someone who has worked in small teams for many years and regularly encounters this state, both in others and in myself.

This text is not a psychological study. It is rather an attempt to name and explore a phenomenon that we rarely discuss. And, of course, it is an invitation to a dialogue.

What kind of loneliness are we talking about?

When we talk about professional loneliness, we often mix several different experiences together. In reality, this loneliness appears in several different forms and contexts.

1. Lack of social and emotional connection

This is the loneliness of support. An emotional emptiness that often follows the person who carries things forward, when someone lacks recognition, attention, trust, and a simple human reaction to what is happening.

When there is no one to talk to about things that don’t work. When afterwork is a dull formality. When no one says “well done” when you actually did well. When no one asks, “What happened?” when something did happen.

We can organize as many team-building (I hate that word!) activities as we want, but real connections are built through trust. They are built through attention, not through bowling, excursions, or, heaven forbid, a personality-types workshop (I once attended one. It was terrible).

The loneliness of responsibility

This is the loneliness of the person responsible for decisions, responsible for trade-offs, consequences, and for reflecting on all of it.

The loneliness of someone who often has no one to discuss their choices with, no one to share their doubts with, or to safely express their fears (because leaders don’t get scared, leaders lead the way, right?).

The loneliness of being different

When you are simply different in the team. With a different experience. Different sensitivities. You react differently. You don’t fit into the rituals.

You might be an immigrant in a team of locals, the only female in a team, a humanities person in a team of engineers, or an IT professional working in a museum. You might be an introvert in a team of extroverts. I could keep listing examples forever.

2. Lack of professional companionship

This is my “favorite” kind of loneliness.

In recent years, I’ve been building infrastructure for research, communication, and media work at a nonprofit expert organization. And try to guess in one attempt: can I really discuss what I do with anyone?

I can discuss my colleagues’ needs and tasks with them. With contractors, I can discuss how we plan to implement certain solutions.

But most of the decisions I make myself. My colleagues are talented and real experts. But in different areas. What I do is mostly a black box for them. I connect their needs with the technical possibilities we can find in the outside world. And that is a very lonely path.

Here as well, we can identify at least a few different forms.

The loneliness of expertise

When you carry unique expertise in a team (for example, a tech specialist in a non-tech team), you are, by definition, alone. Who do you discuss possible solutions with? Who challenges your choice, who offers an alternative? Who teaches you, damn it? I’m not seventeen, of course, but just like everyone else, I want to learn and grow.

And this is a serious problem: without an external “mirror,” a person makes decisions alone, receives no feedback, begins to doubt themselves, or, conversely, loses their critical sense.

The loneliness of the generalist

Generalists are often lonely in any team and very often end up in professional isolation. Quite often, their functions and responsibilities revolve around them because of their generalist nature. The full cycle often sits on their shoulders, and you simply end up alone because… well, no one really needs to be involved, right?

You are responsible for several domains, your specialization doesn’t match the narrower specialization of your colleagues, and no one fully understands what exactly you do. The result? No professional dialogue, difficult feedback, no intellectual sparring.

You are part of the team. You are functionally integrated (because you are a node), but you are still alone.

This is a classic setup for generalists across industries, but it becomes even sharper in NGOs, cultural institutions, and small teams.

The loneliness of the solo builder

The most obvious form of professional loneliness. Entrepreneur? Freelancer? Independent author? You are incredibly free, but often incredibly lonely. This is the price of freedom: decisions made in a vacuum, without a mirror or sparring. Your decisions and trade-offs are only yours. No one says, “Dude, this is nonsense!” No one says, “Dude, this is fire, don’t stop!” No one says, “Damn, let’s do this together!”

3. Loneliness created by organizational culture

Sometimes loneliness is created by the organizational culture itself when it is not acceptable to talk about doubts, mistakes are seen as weakness, discussion of problems is replaced by demonstrations of confidence, and admitting fatigue or overload is considered unprofessional.

In such an environment, people begin to hide the real difficulties of their work, conversations become superficial, and professional doubts remain unspoken.

When an organization's culture does not allow for vulnerability or honest discussion of difficulties, professional loneliness becomes the norm.

People continue to work together, but they stop thinking together.

Workplace loneliness and social isolation

In the work The Emotional Labour of Boundary Spanning, the authors (Catherine Needham, Sharon Mastracci, and Catherine Mangan) emphasize that workplace loneliness is not the same as social isolation.

You can work in a large team, even in an open space, and still experience professional loneliness. Because it is driven, first of all, by the absence of meaningful professional connections: no one truly understands you, you have no one to discuss complex challenges and tasks with, and there is no sense of professional belonging or alignment.

Loneliness as a symptom of burnout. And a growing trend

This sad journey is easy to see: you feel loneliness, engagement decreases, emotional exhaustion appears (without emotional, social, and professional support) and… burnout.

Moreover, we can see that the problem is becoming more and more relevant due to several factors:

• the rise of remote work

• high specialization

• the growth of project-based work (and project work, by its nature, does not support long-term engagement)

On top of that, the trend toward small teams also contributes to the problem.

There is a paradox of small teams: often, they are socially very close and connected, but professionally very fragmented. One person handles marketing, one handles product, one handles partnerships, one handles operations… alone, without a “professional peer”.

Generalists are in danger!

A generalist is almost an incubator of loneliness. First, their role is poorly understood. Second, they (we!) almost have no professional community.

A specialist can say: I am a product manager, I am a UX designer, I am a data scientist — and find conferences, books, LinkedIn groups, communities, mentors.

A generalist describes themselves and… very often it is a unique description that doesn’t place you in any community. Hell, at nine out of ten professional conferences, I feel like an impostor.

So, what next?

For small teams, generalists, and solo builders in almost any industry, there is almost no professional support. There are almost no simple, safe, and accessible spaces where people with a similar reality can talk honestly with each other.

The classic solutions (training programs, courses, development programs) do not solve this problem. They provide knowledge, tools, and sometimes even inspiration. But they almost never provide intellectual and human support, and the possibility of a meaningful exchange of experience with the context in mind.

I feel that support in this environment should be built around several interconnected dimensions.

Recognition

First, a person needs to see and name their situation. This is quite a challenge. To understand that what they are experiencing is not personal incompetence and not an individual weakness, but the structural reality of small teams and working solo: mixed roles, blurred responsibility, the absence of a mirror, lack of support, constant pressure to do everything at once, and the absence of slack.

Recognition is the moment when you realize: “I’m not broken. I see the problem, it is structural, and I’m not alone with it.”

Understanding

The next step is to understand what exactly is happening. Why does professional loneliness appear?

Why generalists often burn out. Why is it so difficult in small teams to receive feedback, to grow, and to see your trajectory?

Understanding is an attempt to build a map of what is going on, to see the mechanisms that usually remain invisible.

Craft

But understanding alone is not enough. At some point, the question appears: what can be done in practice?

How to organize work with limited resources. How to protect your role. How to talk with managers or with the team. How to build a career if you are a generalist. How to look for support and how to give it.

Craft is shared practice: advice, frameworks, working methods, and approaches that help you move forward.

Infrastructure and Space

And finally, all of this is almost impossible without infrastructure.

By infrastructure I mean not only technology, but also tools, formats, and spaces that make conversation, exchange of experience, and collective thinking possible.

These can be small products, tools, or communities — anything that helps people not remain alone with their reality.

Final advice

In a way, this essay is my attempt at recognition. And for now, I only have two simple takeaways:

• Share your experience of professional loneliness and your experience of dealing with it. You can start with a comment under this article. Or send me a private message or an email. Sharing is caring.

• Listen to Backstreet Boys!

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No frameworks today. Let's talk about God (stay with me here 😅) and why I refuse to chase perfection.

They say God created everything in seven days.

Very short and intense sprint, I would say. No iterations, no focus groups, and I suppose not a long planning. This is what you get!

(Okay, fine, there was a flood. But that was version 2.0! )

You can debate the creator’s intentions, the methods, the decisions, or the existence of the creator altogether. But what is hard to argue with is that God was definitely not a perfectionist. Just open the news feed…

It’s created. It’s running. It works (somehow), doesn’t it? That’s all that matters.

Yet here we are, overthinking every single step. We tell ourselves the Substack post has to be epic (after all, such smart, high-level people will be reading it!). No room for mistakes.

Every job interview feels like a final shot. Zero mistakes allowed. Everything has to be flawless.

Every event - absolutely perfect!

I don’t want to play this game.

What do I believe?

I believe that a text with three mistakes, but on time, is better than a perfect text that never came out.

I believe that a corporate newsletter sent with a typo and a broken link is not a catastrophe. Especially if every new newsletter brings you traffic, event registrations, and great open and click rates.

I believe it’s impossible to run an event without some screw-ups. It just doesn’t happen. So your sound guy went on a bender because of family drama, a heavy rainstorm in a hot July flooded the venue, and your artist arrived with a huge bruise on half his face (all three are real cases)!

All we can do is keep creating our imperfect things and try to make them better each time. I mean, even God didn’t exactly nail it with EVEN Version 2.0.

As the character of Will Ferrell, Cam Brady, once said:
“In my lifetime, I have made over 100,000 phone calls and maybe 1,000 of them are obscene! That’s a very small percentage.”

Remember:

Only the one who does not make phone calls never says anything obscene on the phone!

If you’ve read this to the end, thank you!

If you disagree, feel something important is missing, or have anything on your mind, I’d love to hear it in the comments.

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This text is an experiment — an attempt to understand what happens when management frameworks built for large organizations are applied to small teams: teams with no spare resources, no buffer roles, and very little room for error.

Small teams in a world of big models, frameworks, and approaches are like slightly lost fairy-tale Moomins, who have somehow wandered into Elon Musk’s world, where everything is oversized, not built for humans, all about performance, achievement, and structures and capacity you simply don’t have (and sometimes, thankfully, don’t need).

And when it comes to goal-setting and measurable results, on top of approaches that are not properly adapted for small teams, you also get the whole package of performativity culture, hustle rhetoric, motivational bloggers, and the American (sorry!) Dream thrown in.

As you may have already guessed (which is not strictly necessary when a text begins with fairy creatures and, heaven help us, Musk), we’re going to talk about OKR.

If you don’t know who Moomins are, you absolutely must get acquainted with one of Finland’s main cultural treasures), and if you don’t know who Elon Musk is… it’s fine, and don’t need to know, just spend your time with the Moomins instead.

I’m sure you’re already familiar with OKR, but if not, here’s a very short introduction:

OKR (Objectives and Key Results) is one of the most popular frameworks for setting and tracking goals. So far, nothing too complicated, right?

An Objective defines what you want to achieve. It should be meaningful, concrete, and ideally inspiring. A good Objective provides direction and clarity.

Key Results are a deconstruction of the Objective. They answer the question: “How will we measure progress toward that Objective?” They must be specific, time-bound, and measurable. A Key Result is either achieved or not achieved. No other options here.

Objectives can live longer (sometimes across multiple cycles) while Key Results evolve as the work progresses. When the Key Results are achieved, the Objective is considered achieved.

In this article, I won’t go deep into how to set OKRs within the framework or explore all its variations. I’ll skip that lesson (perhaps we’ll return to it in another piece) and focus specifically on small teams.

For the most curious readers, I recommend Google’s excellent “Set goals with OKRs” guide.

OKR in Large vs Small Teams: Key Differences

If you’re subscribed to Make It Work, you know that I’m obsessed with small teams and tend to look at everything through their lens, so we simply have to start with a conversation about the difference between small and large teams in the context of setting and tracking OKRs.

1. Slack and Slackness

When thinking about OKRs, it’s important to remember one key difference:

• In large organizations, OKRs broadly manage the allocation of slack.

• In small teams, it manages scarcity: of attention, people, money, and technical infrastructure.

In large organizations, OKRs often serve as a mechanism for reallocating excess resources. There is usually slack that allows the organization to invest in growth.

In such a system, the core question sounds like this:

“Where should we direct it (our slack) to accelerate growth?”

OKRs serve as a way to focus ambition and resources and to align which initiatives will receive those resources.

In small teams, the situation is the opposite. Slack is minimal or entirely absent, and operational load almost always exceeds the team’s actual capacity. Here, OKRs do not distribute abundance; they are forced to protect limited attention and energy, creating necessary focus from what little exists.

2. Fewer Objectives and Key Results

If you had six departments, an R&D unit, and several strong senior leaders — go ahead, play with OKRs however you like. But in a small team, it’s irresponsible to create five Objectives, each exploding into multiple Key Results. You simply cannot afford it.

You’re already living in a permanent scarcity loop, with all the unpleasant side effects. For example, Cognitive Tunneling (when your mind focuses only on what’s right in front of you). Why add an entirely new set of priorities on top of that?

In small teams, it’s rational to choose 1–2 Objectives and 2–3 Key Results for each.

Because tracking itself costs energy, resources, and time.

Read more about scarcity effects in small teams ↓

3. Shorter Cycle

Classic OKRs typically operate on a quarterly cycle, and sometimes even a semiannual one. Even if you’re an NGO with annual funding and plans, setting annual or half-yearly OKRs is a luxury you simply can’t afford. I know those November meetings too well — when everyone is reviewing the numbers and suddenly realizes that roughly 70% of what was promised still needs to happen in the remaining two months.

Even a quarter is too long when there is no stable product, no consistent demand, no dedicated strategy function. In three months, the context, the hypothesis, the team, and the priorities can all shift.

Your cycle cannot exceed your ability to predict the environment.

Small teams are often very fast, but their collective memory is rarely institutionalized: no decision logs, no established processes, no documented prioritization principles. This means we quickly forget our actual focus.

That’s why, depending on your context, an OKR cycle — from defining the Objective and 2–3 Key Results to the final decision (continue/adjust/stop) — should last 4 to 6 weeks max. Tracking iterations should happen every 1–2 weeks.

One of the key purposes of such a cycle is to shorten the distance between intention, action, and reality (your results).

4. Capacity Gate

Even though the term Capacity Gate sounds like the name of a boring Netflix sci-fi movie hero (an orphan, half-cyborg with empathy, searching for his creator), it is actually one of the most important questions a small team can ask itself:

Do we realistically have the capacity for this OKR?

There’s no need to over-explain or over-advocate here. If you lead a small team, you already know what this means, and you probably don’t want to wander back into the sleepy valley of unachievable goals.

A proper Capacity Gate forces you to pause before committing and ask the second question:

What are we consciously giving up for the sake of this OKR?

Because in small teams, nothing new comes for free.

Every Objective consumes attention, time, and energy that must be taken from somewhere else. It is important to understand and reflect on what we are willing to give up in order to achieve our goals. We need to be intentional about it and monitor the accumulation of problems caused by trade-offs, revisiting them with each cycle.

It is a safeguard against the hidden accumulation of organizational debt.

What else to Remember When Setting OKRs in small teams

1. Avoid Activity Key Results.

If your KR sounds like “conduct,” “create,” “launch,” or “develop,” it is almost always an action, not a result.

Actions are tasks. Key Results are measurable changes that result from those actions.

Instead of “Conduct 5 interviews,” better say: “≥3 recurring problems identified within the target audience.”

Instead of “Launch a new landing page,” say: “Landing page conversion rate ≥ 8%.”

The difference is simple: activity creates the feeling of progress (and action). Outcome shows whether progress actually happened.

2. Don’t Stretch Too Much

A stretch OKR is an ambitious goal that is intentionally set above a comfortable level of achievability.

The roots of this approach (and its built-in ambition) lead back, of course, to the shiny offices of mega-corporations that “grew out of garages.”

In the Intel/Google version, Stretch means:

• A goal with roughly a 60–70% probability of achievement.

• If you hit 100%, the goal was too modest.

• Partial achievement is not considered a failure.

Stretch is meant to stimulate growth and push teams out of inertia.

In large companies, stretch is a growth tool, an ambitious way of deploying organizational slack.

In small teams, it must be used very carefully, or replaced altogether with an exploration logic aimed at reducing uncertainty rather than maximizing performance. Otherwise, stretch OKRs can lead to chronic underachievement (and declining motivation), burnout, and even metric manipulation.

I’m not arguing against ambition. I’m just reminding us about reality.

3. Rituals without Religion

As my mother used to say, “Danil, just don’t get fanatical.”

Don’t turn OKR into a religion, a grand engine, or a heroic motivator. Especially at the setup stage.

Keep it simple:

• One (or two) collective sessions of 60–90 minutes to set the OKRs

• 15-minute weekly review

• 30–45 minutes for a retrospective during or at the end of the cycle

4. Owners and the Gatekeeper

Who formulates OKRs?

At the creation stage, in a small team, developing the Objective should ideally be a collective effort. Collective discussion creates alignment and commitment.

What about Key Results?

I suggest that the owners (the people who will handle the hands-on work required to deliver these results) first formulate their own version. Then — discussion, refinement if needed, and formal agreement.

Who is responsible for OKRs afterwards?

The owner is responsible for progress toward the Key Result. Not for doing everything personally, but for driving it forward, monitoring it, escalating issues, and ensuring it does not disappear in operational noise.

Ownership must belong to the person who can meaningfully influence the outcome.

The Gatekeeper (usually the team lead) is the Objective holder.

The Gatekeeper role is to ensure:

• clarity of formulation,

• alignment with the Objective,

• realism,

• and a proper capacity check.

The Gatekeeper safeguards the system's integrity.

When You Don’t Need OKRs

OKR is not mandatory. It’s just a tool, and sometimes the most mature decision is not to use it.

You probably don’t need OKRs if:

• Your team is smaller than three people, and alignment happens naturally through constant communication.

• You don’t have reliable data, because Key Results without measurement quickly turn into performance theater.

• There is no stable direction yet, and clarity matters more than metrics.

• The team cannot sustain basic discipline. If weekly check-ins already fail, OKR won’t fix culture.

Sometimes frameworks can wait.

Choose. Adapt. Reflect.

Frameworks are not neutral. They carry the assumptions of the environments they were born in.

OKR was shaped in companies with scale, slack, and layers of structure. I keep repeating that small teams are not simply an early stage of growth — they could be a different species.

A small team may one day have the opportunity to choose growth, scale, and the evolutionary path toward becoming one of the “big players.” Or it may not. Or it may choose to remain small and continue developing on its own terms.

And in that sense, the OKR framework (like many others) needs to be rethought, adapted, and, at times, simplified.

If OKRs help you think clearly and make deliberate decisions — keep them. If it adds pressure without clarity — let it go.

Be an ambitious, reflective, and conscious small team of Moomins — choosing your own path and walking toward the goals you set. And don’t be afraid to revise them.

That is the real strength of small teams: the ability to rethink, reflect quickly, and evolve iteratively.

If you’ve read this to the end, thank you!

If you disagree, feel something important is missing, or have anything on your mind, I’d love to hear it in the comments.

Leave a comment

Related articles ↓

This text is an experiment. It's my first try to understand what happens when management frameworks built for large organizations are applied to small teams (teams with no spare resources, no buffer roles, and very little room for error).

Today, I’m looking at one of the strongest job design models developed at Harvard Business School by Robert Simons and asking a simple question:

Where does this model work and where does it fall short in small teams and early-stage organizations, and how can it be adapted?

Fair warning: this is a damn long article. Part of me wants to apologize for that, but then again, we can’t just live on coaching reels!

What is the Job Design Model by Robert Simons

As I was taught in a university course on formal logic, before reasoning about something complex, it helps to first agree on the terms. Let’s try to do that briefly and, as much as possible, without drifting into corporate heresy.

So, job design by Robert Simons (Harvard Business School) is generally obvious: it is the process of structuring job components to enhance employee satisfaction and organizational effectiveness.

Four spans of job design

“Hard” spans:

Two “hard” spans (span of control and span of accountability), focus on the traditional dimensions of job design, determined and described in job descriptions, organization charts, and performance measurement systems.

1. Span of Control — what you “control.” This is what you can manage directly, without someone else’s “yes.”

2. Span of Accountability — the level of complexity of the outcome you are responsible for. Is it a simple and unambiguous result, or a multidimensional one with conflicting goals and trade-offs?

“Soft” spans

Two “soft” spans (span of influence and span of support) is about more abstract and less measurable aspects: levels of interaction and helpfulness among employees.

1. Span of Support — the kind of support you can realistically rely on when things get stuck.

2. Span of Influence — the ability to achieve results through other people and systems that do not report to you.

   

I, forgive me for this, created a small widget to illustrate the model as Robert Simons describes it. You can also play with it via the link.

If something breaks, I’ll share the GitHub access so you can fix it, because at that point I definitely won’t be able to 🙂

Entrepreneurial gap and the balance

We won’t dive into every detail of the framework (those who want the full picture can always pay for the HBS online course), but we will focus on two things that matter for the rest of this discussion:

1. The entrepreneurial gap

It is the result of a designed mismatch: the span of accountability is wide, while the span of control is narrow. This gap is intentionally created to force employees to innovate and to influence those who control the resources they need in order to get results.

2. Balanced job design

Balanced design (in my simplified reading of Simons) means structural coherence across all four dimensions of a role.

In other words, the demands of the role and the capabilities of the role exist in the same logical space.

Traditionally, leaders tried to design roles so that responsibility (span of accountability) matched authority (span of control), because for a job to succeed, supply must equal demand.

My widget (based on the logic of Job Design Optimization Tool JDOT developed at HBS) lets you explore this balance by running the so-called X-test: the line connecting accountability and support should intersect with the line connecting control and influence (are you still here?).

If we want innovation and dynamism, we also need an entrepreneurial gap, as shown in the widget.

So far, so good.

Now let’s put the book aside, shake off the corporate haze, look around at the eight people on your team, and try to understand how all of this actually works where we are.

If this sparks your interest, you can read more on the Harvard Business School Online website. 

Okay, but how does this work when there are eight of you?

The model is the same, but it behaves very differently in large organizations and in small teams. Why?

1. The room to adjust any span is different and much smaller

✦︎ Span of Control

In large organizations, this span ranges from 1 (almost no control) to 10 (maximum control). It is based on the slack that large organizations have. Control adjustment is not unlimited, of course, but it is structurally available by design.

In small teams, the span of control is structurally narrow and less adjustable, and this is dictated by the very nature of small teams: resources are scarce, most roles do not own a budget, people can’t hire or pause work independently, scope can’t be changed without negotiation, and decision rights are shared rather than held individually

In large organizations, the span of control can range from 1 to 10, while in small teams it typically ranges from 1 to 5.

✦︎ Span of Accountability

In large organizations, a person’s span of accountability can be wide or narrow depending on their function, position, and place in the hierarchy.

For example, an executive’s performance may hinge on the organization’s market value or long-term growth, while a social media specialist is often accountable for much narrower measures, such as the number of posts, engagement rate, or reach.

When a role is expected to be creative and innovative, it must involve frequent trade-offs. This means holding people accountable for broader outcomes, not just narrowly defined outputs.

In small teams, things work very differently.

People often perform multiple roles at once, and each role can imply a different span of accountability (designer in the morning, strategist by the evening).

Small teams are almost destined to have wide spans of accountability, because responsibility is rarely tied to a single function. More often, it is tied to a piece of reality. In a small team, it is nearly impossible to break responsibility down in a way that meaningfully narrows the span of accountability.

In small teams, the span of accountability realistically ranges from 5 to 10 (don’t forget, this is not a precise measurement, of course. Think of it as a relative scale and a diagnostic exercise, not a ruler).

✦ Span of Influence

In large organizations, this span can range from 1 (which is rare, but the night guard at your warehouse might genuinely sit at a strict one) to 10.

In small teams, however, the span of influence is almost always wide by default because specialization is limited, resources are shared, and almost any meaningful work cuts across multiple roles.

Here, influence is not an optional skill you occasionally use; it is the primary way work gets done.

For the purposes of this discussion, we can assume that in small teams, the span of influence should range from 5 to 10.

✦ Span of Support

According to Simons, organizations with wide spans of support share four key attributes:

• Pride and purpose: Employees who are inspired by the organization’s mission are more likely to help others achieve shared goals.

• Group identity: Selective hiring makes people feel part of a distinct group, fostering camaraderie and a willingness to support one another.

• Trust: People must feel safe being vulnerable and asking for help.

• Fairness and equity: Employees are more willing to support others when recognition and rewards are perceived as fair.

In large (and healthy) organizations, the span of support is institutionalized and distributed across managers, formal processes, HR, coaching, and other systems. Support is relatively predictable and does not depend on a single person.

In small teams, however, the span of support is usually personal rather than institutional. There is no HR buffer, no spare manager, and no system to absorb overload. Support depends on direct access to the founder or team lead, informal norms of helping, psychological safety in admitting uncertainty, and a shared willingness to pause and rethink priorities together.

In small teams, the span of support compensates for almost everything the team can’t provide structurally and therefore should realistically range from 5 to 10.

I also made (someone please stop me!) a widget for modeling job design in small teams — you can try it out via the link.

2. The room to adjust any span is different and much smaller

From everything said above (yes, this text did get long): in large organizations, the entrepreneurial gap is usually an intentional choice. Two key spans (accountability and control) are deliberately misaligned to create it, while the other two (support and influence) are adjusted, where possible, to compensate. It is a design decision.

But what about small teams?

The entrepreneurial gap in small teams is not a feature. It’s a built-in constraint.

In small teams, control is structurally narrow by default, while accountability is almost always wide. This makes the entrepreneurial gap far less adjustable and often much larger than intended.

In small teams, people are not “encouraged to think like entrepreneurs”. They are forced to, because there is no alternative.

Conclusions and lessons (finally!)

1. Control can’t be expanded. Support!

In a small team, you almost always can’t suddenly add budget, hire people, delegate “downwards,” or create buffers and slack.

You can’t just jump over the entrepreneurial gap. Here, we need wings, and those wings can only be Support.

2. Accountability can’t be removed, but it can be clarified

In small teams, accountability is almost always wide: Patrick is responsible for marketing (whatever that means), Laura for the product (good luck, Laura!), Maxim sits on sales (Patrick, move over, it’s the same bench!), and so on.

When accountability is wide, metrics must be honest, not “ambitious,” taking constraints and dependencies into account.

A bad example (Patrick, why are you on the windowsill?!):

“You’re responsible for growth, but the budget is zero, the product can’t be touched, and the team is busy.”

A fair example (get down, Patrick!):

“Your area is hypotheses, experiments, and signals. Growth is a collective responsibility.”

Accountability remains, but it no longer becomes a moral trap.

3. The entrepreneurial gap can’t and shouldn’t be closed. But it can be made passable.

In a small team, almost always, accountability > control. And our task is to help the team get across this gap without losses. This is where Influence and Support must take center stage.

Influence must be fast and legitimate. If moving a task forward requires three meetings, personal charisma, or catching someone at the right moment, influence is effectively blocked, and the entrepreneurial gap becomes toxic.

Support must be practical and accessible. It is not a value or a declaration. It is the ability to actually get help at the right moment.

4. Leadership is role design, not slogans

“Be proactive.” “Take ownership.” “Think like an entrepreneur.”

In large teams, this might sometimes work in one way or another (though plenty of things don’t work there either). But in small teams, this approach is a symptom of unresolved design gaps.

And those gaps need to be addressed structurally. You can start by playing with my widgets 😄

Classic widget

Widget for small teams

If you’ve read this to the end, thank you!

If you disagree, feel something important is missing, or have anything on your mind, I’d love to hear it in the comments.

Leave a comment

Accepting the obvious

A few years ago, we were developing our organization’s strategy. The goal was not just to produce a strategy “as a document,” but to create a tool that would help the organization survive and grow in a radically changed environment.

I was sent to study. It was an online strategy course at Harvard Business School (of course, online — we are not Google)!

Big, crazy smart, crazy-crazy ambitious. Theory, cases, peer-to-peer sessions. It was exciting and challenging. Like opening a window into the biiiig world.

And then you return to your own context and suddenly realize that all this knowledge… is not about you.

It’s like assembling a wardrobe using a 150-page IKEA manual, but 90% of the parts are missing, and the remaining ten percent belong to a completely different piece of furniture. 

And then…. you go through all the stages.

• Shock and denial. “No, I just didn’t fully get it. I need to reread it. More sessions. More sticky notes.”

• Anger. “I hate corporate education! Why does nobody say that the real life of small teams is different?”

• Bargaining. “Okay, maybe I just need to figure out which parts are useful, and which ones are clearly designed for very big, very “adult” companies run by very, very-very serious people.”

• Grief. “F**k it! This is pointless! Nothing works. The frameworks don’t work. I’m just bad at this.”

And only then — acceptance.

It is important to understand:

Most small projects, initiatives, teams, organizations, or businesses are not “early stages of something big.”

They are a different species. A parallel branch of evolution.

That means we need a different education. Education and knowledge for small teams, resource-scarce initiatives, ten-person nonprofits, and for people who want to become leaders and grow in exactly this context.

Traps, Gap, and a bit of Slack

There are several reasons behind this gap between what the education industry offers and what small teams actually need.

1. Scale trap

Most leadership advice, courses, and programs assume management through layers. You have roles, departments, and processes. And you are taught to manage those layers and mediators.

But in small teams, there are almost no layers!

Most advice we get from courses only looks behavioral (“delegate,” “coach,” “set OKRs”), but in reality, it is structural.

For example, one of the most popular ideas in courses, books, and yes, on Substack too: “Leaders should be strategists, not executors!”

Sounds applicable? Try dropping your share of operational work in a six-person team.

Or this one: “Build a leadership pipeline.”

Sure. In a nine-person team, the pipeline usually looks like this: “One person is holding everything together, and two others are on the verge of quitting.”

At that point, it stops being inspiration and starts feeling like mockery.

Especially when Bezos’s “two-pizza team” rule is not a rule for you. It’s already the absolute maximum of what’s possible.

2. The “Slack” Gap

Many change and innovation frameworks are built on the idea of organizational slack—surplus time, people, money, and expertise that can absorb inefficiencies during periods of change.

We are told:

“Spend 20% of your time on innovation,” or “Run a three-day strategic offsite.”

But we don’t have that slack. Every hour spent on Harvard-style strategizing is an hour when work that brings money or real outcomes right now does not get done.

We are offered tools for optimization, while small teams need tools for growth survival.

3. Expectation trap

You complete a course. You read the book. You feel energized. And new expectations appear! Expectations of a new version of yourself, and of the environment around you, which now somehow should match all those cases you “lived through” during the course.

But in terms of resources, you are still the same. And the surrounding reality is the same, too.

It’s like giving Kai from The Snow Queen shards of ice with the letters S H I T on them and asking him to assemble the word “Eternity.”

Yes, consciousness shapes being to some extent (sorry, Karl), but not that much.

The result is often the same: you may become more knowledgeable, but more often you simply become more unhappy.

4. The specialization trap

In large teams, the efficiency of a leader (and of the team) is often achieved through narrowing the scope of responsibilities.

Small teams survive through hybridity.

You can’t “delegate marketing” when you don’t have a marketing director. That’s it.

You are the CEO. You also write the copy. You also pay the bills.

5. The time horizon trap

My favorite one!

Classic strategy teaches you to look three, five, ten years ahead. Sustainable competitive advantage and all that.

For us (small teams), “long-term” often means the next quarter.

Applying long-term planning tools (like complex scenario analysis) to an organization facing a cash gap next month is like choosing curtain designs in a burning house.

7. Causation trap

Business courses are almost always causation-based:

goals → plan → resources → execution.

In our reality, resources appear only after something actually works. It’s a kind of bricolage, for god’s sake!

I’ve written more about bricolage as a managerial state of mind in a separate post, if you want to go deeper.

6. Follow the Money!

Small teams don’t pay.

Who at Harvard or Bocconi School of Management needs your fifty dollars for a course? Those “small” online courses priced at two thousand dollars are just a flashlight at the entrance of an MBA sales funnel.

The entire body of knowledge is created for the paying client. And it is not us.

Once, I attended a training on security and AI. We were told that it is absolutely critical to have a department responsible for data security. A department!

In a ten-person team, that “department” is a morning slot in someone’s calendar.

That training is clearly something they roll out for their regular clients. And we… yes, once again, we are not them. And yes, we’ve made a mistake in choosing this training provider. And yes, they didn’t adjust anything.

Four Shifts: A Learning Manifesto for Small Teams

I may have painted a pretty grim picture. But let’s get out of this lonely tunnel of despair (layered with even more despair) for a moment. What do we actually need? We need just four fundamental shifts.

Shift 1: From Content Consumption to Contextual Connection

Traditional education sells content. But today, content is a commodity. You can Google anything in three seconds, and ChatGPT or Gemini will explain it to you with examples for free.

What you cannot Google is how to apply that model in your specific context, when Patrick, your accountant, is about to quit, your day already feels 32 hours long, and Susan, your lead project manager, has just burnt out after a six-week sprint.

You need a similar context and comparable experience.

That is why education for people and teams like us should be Cohort-Based and Peer-Driven.

In the world of small teams, an “expert” is not a professor who studied markets back in 2010 or the Chief of Marketing of Amazon who decided to teach. An expert is a fellow founder, team lead, fundraiser, or marketer who solved your current problem in a similar context just last Tuesday.

What does this look like in practice?

• Guided masterminds: A co-development format where five leaders dissect one participant’s real-life case.

• Community environment as curriculum: Instead of buying a “course,” you buy access to an environment (like Reforge or Lenny’s Newsletter community). You aren’t paying for video lectures; you are paying for the chance not to be alone, for access to shared knowledge, and for the ability to actually talk to people who “get it.”

• Lunch and learn: If someone on the team solves a problem or learns something new, they share it and teach the rest. This isn’t just shared ownership of new knowledge and expertise; it is a way of documenting and reflecting that allows the team to “repeat” success.

Shift 2: From “Just-in-Case” to “Just-in-Time”

To stock up on all the necessary knowledge for a small team of generalists that might be useful someday to someone, you would have to simply never start working. You cannot hoard knowledge for the future! You can’t take three-month pauses for courses — no one is going to pay for that.

We should learn in the flow of work. Moreover, you need to learn exactly at the moment when your new knowledge and skills have an immediate application: you grow while solving a task you couldn’t solve before.

For example:

• Continuously updated micro-courses: 5-minute modules on specific tasks, pains, and situations, contextually linked to what you are doing right now. A “for right now” library: created and updated somewhere by someone—or even by your own team.

• Newsletter courses: Instead of sending a manager to a generic leadership course, subscribe them to a curated newsletter that delivers tools weekly. If knowledge cannot be applied today or tomorrow, it is not education—it is Edutainment.

• On-demand micro-education: Community-based practical education. Today, you ask a question, voice a problem, or say what you wish you knew how to do. Tomorrow, you receive three 1-minute videos and a short guide on how to solve it.

Shift 3: From Prescriptive Ideals to Descriptive Sensemaking

Most courses teach you how things should be (The Norm). But small teams live in chaos. Trying to stretch an ideal textbook model over that chaos only creates anxiety and a sense of inadequacy (can education at least stop making us feel inadequate, please?)!

Karl Weick described what growth and education for leaders — especially in small teams! — actually looks like. He called it Sensemaking:

Something happens → we try to understand it → we act → we re-assemble our understanding.

Instead of theories and frameworks created for someone else, this approach focuses on reflection and the iterative sensemaking of experience. It’s the iterative growth of expertise and skills.

This means analyzing decision logs and data after something has already happened!

As noted in a post by :

“Making mistakes is human. But repeating mistakes makes me frustrated.”

Mistakes are the stimulus and the very object of learning, specifically so they don’t become repeated mistakes.

What does this look like?

• Retrospective Sessions: Moderated (or not) sessions to analyze what happened after the work is done.

• Community-based or peer-to-peer retrospectives: Breaking down what was done, what went wrong, and what was problematic with a group of people in similar shoes.

Shift 4: From The Heroic Leader to Collective Agency

All we ever read is: “the leader must,” “the leader should.”

90% of educational products are targeted solely at the leader, as if everyone else in the office were just mindless blobs wandering aimlessly down the corridors.

Leadership and business education must be grounded in and develop distributed agency, where the unit of learning is not the individual but the team:

• Democratized knowledge: No more “secret management courses.” The principles for creating and executing strategy, finance, and developing corporate culture, along with all the tools (everything!) must be open and accessible to the entire team.

• Leadership for non-leaders: There must be courses and accessible knowledge on leadership and management for people who are not managers. The best youth football academies (like my favorite, FC Barcelona) train thousands of kids as if every single one of them is a future Messi. Only a tiny fraction will make it to a professional career, but they teach EVERYONE the same way and EVERYONE the same thing: how to play great football.

Education for small teams and resource-scarce initiatives is educational bricolage (I love this word, it feels both sophisticated and a little bit spicy 😅 ).

We take whatever is at hand, mix it with the experience of a neighbor (Peer Learning) or a group of neighbors (Community and Cohort-based learning), apply it immediately (Just-in-Time), and make sense of the results together (Sensemaking).

It might not be as prestigious as a Harvard diploma. But it is exactly what allows us to survive and grow.

If you’ve read this to the end, thank you!

If you disagree, feel something important is missing, or have anything on your mind, I’d love to hear it in the comments.

This piece is part of a paired set of essays. Two authors reflecting on the same problem: burnout, overload, and motivation loss of overperformers in small teams — from two different perspectives.

What you’re reading now focuses on possible ways forward.

The second part, written by , explores the lived experience of an overperformer from the inside. I encourage you to read the second part!.

You can read Diana’s piece here →

Language at work

The Overperformer’s Challenge in a Small Team. Inside the experience

This piece is part of a paired set of essays…

Read more

3 months ago · Diana and Danil Lopatkin | Make It Work

Damn, rain all day. Of course, this shitty weather is a perfect addition to today’s meeting. A 1:1 with . I’m still not fully oriented in this small team, but it really looks like Diana is the one carrying most of it.

I want to understand what’s going on because it feels like she’s constantly dissatisfied with something ˙◠˙

There are only four of us, and we can’t afford to have one unhappy colleague.

And the rain… well. You don’t choose the day for hard conversations.

“Hi Diana! Ready?”

“Hi Danil, yes, ready 😊”

….

Everything Diana shared with me turned out to be a double-edged blade — hurting her and posing real risks to everything we’re trying to build.

Traps, loops, and struggles

The conversation with Diana turned out to be difficult, and it surfaced several issues.

1. The knowledge trap

Diana has become a single point of failure, but this problem is broader than just one person. It means there is a serious imbalance of responsibility and ownership within the team. When one person becomes “responsible for everything,” the rest of us get used to the cozy idea that ownership and accountability live somewhere else, not with them.

2. Responsibility keeps growing

Tasks, expectations, responsibilities grow without any agreements or trade-offs. We’ve lost intentional role design, and over time, this turns competence into a burden.

3. Loss of boundaries

Something is broken in the team’s culture of mutual support. Help is not the same as exploitation! In the long run (and not even a very long one!), these tendencies lead to two outcomes at once: learned helplessness in the team and burnout for Diana.

4. The urgency treadmill

“Everything is urgent. Everything is a priority.” There are two hidden problems here.

• On one level, it’s clear that the team lacks a shared vision.

• On another hand, Diana, having acted as a constant support structure for so long, has lost the ability to set priorities herself (out of fear of letting others down).

5. Motivation erosion

This one is obvious (and sad), but it goes deeper than individual exhaustion.
When systems and processes are designed in ways that strip people of agency and ownership, motivation erodes across the entire team.

The conversation was long. The rain had already stopped. It was dark.

We were sitting there, exhausted, leaning back in our chairs, staring at the whiteboard — where, piece by piece, we had mapped out our plan for change.

Here is our plan

1. Weekly 1:1s with everyone.

Every week without exception.

The goals are simple:

• to hear the whole team

• to return a sense of agency

• to keep a close pulse on how people are doing

We want everyone to clearly understand their contribution and what’s expected of them, and to feel seen. For too long, too many things just worked by default.

2. Alignment as a fixed part of team meetings. Not just status updates

• what we’re doing and why

• what matters right now and what doesn’t

• where responsibility and ownership actually sit

3. Job crafting.

To restore Diana’s sense of agency, we agreed to give her more control over how her role is shaped.

Diana takes a week to reflect and comes back with an answer to one key question:
“Which parts of your work give you energy and which ones drain it?” Then we sit down and discuss how to adjust her job landscape to reflect that answer.

Research shows that people who regularly use their strengths burn out less, even under a high workload. We decided to take that seriously.

4. High-stakes project!

For people like Diana, the strongest motivator is working on projects that actually matter for the whole company.

We have a major client project ahead. The biggest in our history. If it succeeds, it will fundamentally change the company’s future. Diana will lead it.

My role is to provide the why and the what. Diana will definitely define the how.

5. Protecting focus without breaking the team.

To reduce the incoming chaos around Diana (without throwing the rest of the team into a state of helplessness), we reworked how her time is planned.

Now there is a fixed three-hour window once a week during which Diana responds to colleagues’ requests unrelated to her project. Only those three hours.

This forces the team to prioritize their questions and solve what they can on their own

6. Shared project retrospectives.

After every project (even the smallest one!) we now hold a retrospective wth the whole team.

That’s where we talk about:

• what worked

• what didn’t

• why

• and how to do it better next time

This helps Diana stop feeling solely responsible and helps the team regain a sense of ownership.

7. We treat documentation as delivery

Yes, Diana, this is additional work. And we’re being explicit about it. You have two weeks before the new project starts. Document.

We identified the most frequent questions and processes for which Diana’s help is consistently needed. We will create guides and onboarding materials for the most critical and painful areas.

Diana will also document key decisions in detail, so they become part of project retrospectives and feed into our shared knowledge base.

In the long run, this will reduce Diana’s load and allow the team to learn and grow independently.

8. And yes, we talked about financial motivation too

But that part stays under NDA 🙂

We looked at the whiteboard. The whiteboard looked back at us.

It was time to act. But not today. It’s already 19-00.

“Diana, thank you for the conversation and for your trust. Tomorrow we’ll start acting. For now, have a good evening! Please rest and don’t think about anything tonight.

See you next Tuesday!”

Thanks for reading!
A quick housekeeping note before you move on.

My name is Danil, and this is Make it Work — a shared space for knowledge and support for generalists working in small teams and initiatives.

I write about how projects, ideas, and people survive and grow when resources are limited and roles are blurry.

No growth hacks. No bad-taste coaching. I promise.

See you next week!

Best,
Danil | Make It Work

Let’s talk about small teams, adopting technology, and managing complexity.

To do that (and, honestly, also as an exercise in managerial thinking and capacity building), let’s travel into deep, mind-bending space with the crew of the starship Heart of Gold, from The Hitchhiker’s Guide to the Galaxy by Douglas Adams.

Before we start, here’s a small playlist for your journey into over-complexity.

What are we given?

1. Space

“Space is big. You just won’t believe how vastly, hugely, mind-bogglingly big it is. I mean, you may think it’s a long way down the road to the chemist’s, but that’s just peanuts to space.”
The Hitchhiker’s Guide to the Galaxy

Doesn’t this sound like a market description?

2. The team

• Arthur Dent — a human without a role, strategy, or resources. He’s just… in the team.

• Ford Prefect — an insider who “knows something,” but doesn’t actually manage.

• Trillian — the most competent one, yet in a male-dominated team, she is perceived more as a point of tension. Unfortunately familiar.

• Zaphod Beeblebrox — the formal leader. Chaotic, impulsive, seeing the team mostly as an inconvenience on the way to his pan-galactic ambitions. Like many dysfunctional leaders, he had two heads (in his case, quite literally).

• Marvin — the emotional intelligence of the system. No one listens to him. A bit paranoid.

The team may look dysfunctional, but only to the same extent that about 90% of small teams are functional or dysfunctional: assembled, at best, around a shared vision and goals, and more often by personal connections or by pure coincidence.

3. The ship (the tool, the system): The Heart of Gold

The Heart of Gold is the first starship powered by the Infinite Improbability Drive.

At the heart of the ship is a small golden box. Press a button — and the ship passes through every point in the universe at the same time, landing somewhere.

In the book, it is often where it “needs” to be. Otherwise, the book would be hard to write!

In reality, total randomness. Randomness of randomness.

Stepping out of the analogy

This is what we actually have:

• a huge space (a market), full of possibilities and probabilities

• a not-so-functional small team (too often it is a bunch of generalists)

• and a tool (system) so complex that no one really understands how it works

Some result somehow exists, right?

But because of the tool’s complexity, that result is often unpredictable.

And more importantly, it cannot be deconstructed.

Which means:

• you can’t properly analyze failures

• you can’t really learn

• you can’t reliably fix mistakes

The key trap

Our Heart of Gold (and yes, you’ve got it right - this is a metaphor for tools, AI, automation, platforms, and “smart” infrastructures) promises simplification: less effort, less planning, less coordination… and less thinking, less control.

It often:

• multiplies the number of system states

• makes consequences unreadable

• breaks causality

The overly complex infrastructure comes with a promise:

It will remove complexity and deliver results.

The actual result:

Complexity becomes invisible and grows. The result may still exist, but it becomes weakly controlled.

This is over-complexity disguised as simplicity.

Why are the risks higher for small teams

Complex systems can:

• survive hidden complexity

• distribute consequences across roles

• fail to notice cognitive degradation for a long time

Small teams:

• live on direct connections

• depend on understanding why something works

• have no buffer for errors

When the link between action and result breaks down, a small team loses orientation and control.

If capacity (knowledge, skills, expertise) does not keep up with the growing complexity of the system, this is where the Heart of Gold really starts to break things:

1. Thinking: Solutions always “work,” the ability to formulate problems atrophies.

2. Responsibility: It becomes unclear who is responsible for what, because your outcomes no longer clearly follow your decisions.

3. Learning: The team doesn’t learn, but moves between states.

So what can a small team actually do?

• Prefer tools you can explain to yourself and to others.

• Preserve visible cause-and-effect, even if it’s slower.

• Make sure the team comes first, not the system.

And there is a harder, structural choice underneath all of this.

Either you grow expertise and capacity to match the complexity of the system (which is especially difficult for small teams full of generalists), or you simplify the system to the level of the team’s actual expertise.

Often, the only workable option is doing both.

The main takeaway from this small cosmic journey

Let me be clear: I’m not mocking technology itself.

In our story, the Infinite Improbability Drive solves the problem of movement.

It does not solve the problem of navigation, decision-making, or control.

The temptation to build ever more complex systems in the name of optimization is understandable.

But in small teams, such systems should be limited by something very simple:

our ability to truly understand (and explain) how they work, and our real capacity to manage both the process and the outcome.

Without that understanding, even a team of brave cosmic travelers can end up anywhere except where it actually meant to go.

The end 🚀

Thanks for reading!
A quick housekeeping note before you move on.

My name is Danil, and this is Make it Work — a shared space for knowledge and support for generalists working in small teams and initiatives.

I write about how projects, ideas, and people actually survive and grow when resources are limited and roles are blurry.

No growth hacks. No bad-taste coaching. I promise.

See you next week!

Best,
Danil | Make It Work

Today, I got stuck in an elevator. For the first time in my life, actually.

So, there I was, sitting in the elevator waiting for a technician to come and rescue me. As I sat there, I realized our elevator had been acting up for quite a while. It’s been “glitching” forever.

And yet, no one ever fixed it. But the moment a human being got stuck inside, help and repairs arrived in 30 minutes! Mind you, we’re in the middle of heavy snowfalls; getting anywhere takes time, patience, and (above all) necessity or at least a very strong desire.

We’re all good at fixing things. We excel at the urgent. Sometimes, we even manage to do the important.

But there are certain types of tasks that we avoid in teams, much like that preventive elevator maintenance. Small teams (and I’m specifically talking to generalists in small initiatives) suffer from this “disease” the most.

We’re a bunch of generalists here. What did you expect?

The invisible to-do list (some examples)

Updating information

Refreshing the website, updating the Privacy Policy, etc.

I just don’t have the time or focus to surface from operations or strategic planning to realize that our website still features a “New Employee” announcement from November 2024 (for someone who has already quit because we forgot to update him, I suppose 😇).

Follow-ups of follow-ups

You launched? Finished an event? Time for a debrief. You discussed it, took notes. See you at the next follow-up?

But how do you actually integrate what was discussed into the next plan?

How do you remember (!!!!), while planning the next project, that you agreed never to work with that specific contractor again?

Feedback and reflection

The best among us run surveys and genuinely care about feedback. But what’s next? That beautiful chart stays in your head until Thursday, because on Thursday something else inevitably breaks, and you lose track of the data everything.

Documentation and manuals

I’ll admit it: I recently made a step-by-step guide for a new colleague on our event launch workflow. You know, how the website connects to the registration platform, mailings, and social media. I felt so satisfied.

Except that colleague isn’t “new” anymore — she has been running events with us for six months already.

Watering the office plants!

Full disclosure on this one: my colleague actually drew me a poster that says “Aloe Killer,” and it’s now hanging on my office door.

What to do? Lessons from the endless struggle

1. Accept the truth

These tasks will never feel “convenient”. You will never suddenly love them. They will always feel misplaced.

We’re in the middle of a fundraising gala, a new feature launch, or a quarterly budget review… there is never a “good” time for routine.

It’s just routine. Deal with it.

2. Use triggers

These tasks shouldn’t rely on your willpower, even if you have one.

They work best when they are built into your workflow as dependencies.

Set this up in your Asana, Trello, or ClickUp.

• Event finished → Trigger: immediate follow-up + logging decisions.

• Project launched → Trigger: website info update.

• New hire starts → Trigger: documentation (even if it’s a “rough draft for now”).

3. Responsibility rotation

In small teams, documentation is often “nobody’s job.”

Introduce the role of the “Process Warden” or “The Gardener.”

This role rotates weekly or monthly.

The Gardener doesn’t do strategy; they pull weeds. They check links, update dates, and water the aloe. When it’s an assigned role rather than an “extra chore,” it gains legitimacy.

4. The Decision Log

The problem with reflections, for example, is that we treat them like the finish line. But it’s not.

Create a simple table or a Notion page dedicated to one thing:

“What we decided to never do again.”

Make reviewing this log the very first task on the checklist for any new project.

5. Maintenance Day

Once a month or once a quarter, host a Maintenance Day.

No meetings. No new tasks.

The whole team focuses exclusively on “tails”: updating the Privacy Policy, cleaning the mailing list, or freshening up manuals.

6. MVP documentation

Generalists often suffer from perfectionism: “If I’m going to write a guide, it has to be perfect.” Consequently, it never gets done.

Write “dirty” instructions. A screenshot with a red arrow in Slack is documentation. A Loom screen-recording explaining a task is documentation. Just put it all in one folder named “How We Work.”

And the very last point (in case you still think I’m a monster because of the Aloe-case)

I did find a tip that saved my second Aloe plant.

I asked an expert: “How often should I water this?”

They said: “Once every two weeks.”

Now, I have a recurring milestone in Asana: “WATER THE ALOE.”

If I see it in the morning in My Tasks section, I just go and water it, I click “complete,” and I forget about it until the next ping.

So far, the Aloe is alive and well. Proof ↓

What is capacity building?

Capacity building is whatever is needed to bring a team or organization (whether a business or a nonprofit) to the next level of operational, programmatic, financial, or organizational maturity, so it can more effectively and efficiently advance its mission into the future.

• For small organizations and teams, capacity building means strengthening their ability to achieve their mission effectively and sustainably. It involves developing and enhancing skills, knowledge, resources, and processes.

• For small nonprofits, this may mean improving leadership, financial management, technology, or strategic planning.

• For small businesses, it can be about upskilling employees, improving operational efficiency, or adopting new technologies.

Often, capacity building feels like something abstract, a luxury you can safely postpone. When resources are scarce, the natural instinct is to focus only on what seems tied to immediate goals: profit, sales, fundraising, production, delivery. But that instinct creates tunnel vision, a self-reinforcing trap that keeps small teams stuck in scarcity mode.

Three levels of capacity building:

1. Individual level

People are the core asset of any initiative. In small ones, this is even more critical: each person usually covers more functions than in large organizations (not always by volume, but almost always by scope).

Backing it up:

• Effective reskilling tends to bring a productivity uplift of 6–12% (McKinsey).

• Every dollar invested in online training can bring $30 in productivity gains (IBM study, also cited here).

• Companies with comprehensive training programs have a 24% higher profit margin (Zippia).

• One IBM white paper cites $1 → $30 productivity gains within three years (IBM source).

It is not just about formal education. Knowledge sharing inside the team is equally important. It may feel like an extra burden, but in fact, it creates a balanced skills map across the team.

1.1. Who should be trained first?

You have to prioritize. There are several approaches:

1. Invest in the strongest: they learn faster, apply new skills immediately, and often pull others along.

   • Risks:

     • Widening the gap inside the team (the weakest remain bottlenecks),

     • Demotivating those left behind.

2. Support the weakest: the team is only as strong as its weakest link.

   • Risks:

     • Resources go into patching gaps rather than creating growth

     • Strong ones may feel neglected.

3. Develop everyone, but with different tools: strong performers get stretch tasks, weaker ones get baseline training. More sustainable, but often impossible when resources are tight.

4. Focus on key roles: in small teams, the question is not “strong vs weak,” but “who holds the critical function.” Sometimes that’s the strongest leader; other times it’s a weaker person in charge of finances or compliance.

I believe, focusing on key roles is the most relevant strategy under resource constraints, especially at early stages.

And one more point: this is not just about learning, it’s also about caring for people, ensuring motivation, and preventing burnout.

2. Organizational level

This is about processes, infrastructure, and tools. Even the most motivated and skilled team will collapse without transparent processes and the right instruments.

2.1 Choosing tools

It’s not just about making a concious choice of tools, considering their functionality, cost, learning curve, and overall usefulness (so you don’t end up stuck in a dark corner of tool-fetishism).

Some examples of tools:

• Project management platforms

• File-sharing systems

• Team communication apps

• Specialized tools (design platforms, website CMS, mailing systems)

And yes, there are many free or truly affordable tools that are both useful and well-designed. However, sometimes one good paid tool is better than ten free ones — it requires less training and fewer integrations.

And sometimes, in the long run, it’s actually cheaper to build something from scratch for yourself than to stay dependent on paid services.

2.1 Building processes

Processes are how you do what you do, repeatably and consistently. Minimal standards, formulated goals, KPIs... Not just documented, but understood, implemented, and regularly refreshed.

• Onboarding: start with a simple checklist (email, project tool, team meetings, role introductions).

• Knowledge base: documents, strategies, reports, and rules, with easy navigation.

• Team rituals: meetings, planning, reporting, or even traditions of sharing new insights (after a project, a conference, or reading a helpful article).

• Documentation: Сapture decisions, workflows, and lessons learned. Keep it lightweight but consistent: notes from meetings, project retrospectives, and “how we solved this last time” guides prevent teams from reinventing the wheel.

Systematization does not mean bureaucracy; if done right, it frees time instead of wasting it.

Transparent, fair, and useful processes for everyone ✊

3. Systemic level

This is the least discussed but often the most decisive layer: how your team is embedded in the broader ecosystem.

Small teams often stay inward‑looking, forgetting that sustainability comes through connections. Partnerships, networks, communities of practice compensate for the resources you don’t have internally.

3.1. Systemic capacity building includes:

• Partnerships: External allies can fill knowledge gaps, share tools, or provide access to resources otherwise unavailable. For instance, a partnership with a local university might bring interns, or collaboration with a peer organization might reduce costs by sharing infrastructure.

• Communities and networks: Being part of professional associations or informal peer groups means faster learning and access to tested solutions. You don’t have to reinvent the wheel.

• Diverse resource streams: Not just financial (funding sources, revenue models), but also human (volunteers, mentors, advisors) and intellectual (shared knowledge, toolkits).

• Representation and visibility: Taking part in boards, working groups, conferences, or even being visible in sector media strengthens legitimacy and influence.

3.2. Where to start?

• Join one professional community or chat group.

• Map potential partners: who could fill your weak spots, and what mutual value could a partnership bring? Reach out to one.

• Identify one new source of support: funding, expertise, or volunteer help.

Systemic capacity is not a luxury. For small teams, it’s a survival strategy. An isolated team is fragile; a connected team is resilient.

Holistic approach for capacity building in small teams

Capacity building is holistic. You cannot move only on one level:

• If you give tools but no training, people avoid them or misuse them.

• If you train people but don’t set up processes, you end up with chaos, talented people running in different directions.

• If you write down processes but provide no tools, everything stays on slides and docs, never alive in daily work.

• If you build partnerships but don’t strengthen your team, external links will collapse once weaknesses are exposed.

Sustainability appears only when all three levels develop in parallel, even if gradually.

Ever wondered why it’s so hard to think about the future when you’re just trying to survive the week?

There’s actually research that explains this. It also reveals the true cost we pay when we can’t afford to think long-term, as everything feels urgent in the present moment.

The work is called Scarcity: Why Having Too Little Means So Much by Sendhil Mullainathan and Eldar Shafir — a behavioral economist and a cognitive psychologist who decided to study what happens to our thinking when we’re short on money, time, or capacity.

In short, they found this:

When we’re under pressure, we solve today’s problem by using up tomorrow’s resources.

They call it borrowing from the future (What a brilliant line! Love it!).

Examples of borrowing from the future.

When there’s too little money

• Individual: Someone faces an urgent bill and takes a payday loan. Problem solved — for now. But next month, the hole is deeper, and the options are fewer.

• Small team: A nonprofit organization runs out of funds before the next grant is received. To stay afloat, they use personal credit cards or delay salaries. It buys them a week, but erodes trust, morale, and stability.

When there’s too little time

• Individual: You skip sleep or meals to meet a deadline. The work gets done — but at the cost of exhaustion. Can you do the same a few days later? Another round? And another? That’s how short-term wins quietly turn into long-term losses.

• Small team: A team rushes a project, skips documentation, and forgets the debrief. They deliver on time (yay!), but next time they repeat the same mistakes, because no one remembers what worked.

When there’s too little cognitive space

In Scarcity, Shafir and Mullainathan use cognitive bandwidth as a metaphor for our limited mental capacity (the attention and mental energy available to think, plan, and make decisions).

When we live under scarcity of time, money, or stability, a big part of that bandwidth gets consumed by urgent worries and short-term problem-solving.

As a result, there’s less mental space left for long-term thinking or good decision-making, even if we’re perfectly capable of it.

• Individual: You accept a bad job offer or agree to everything. Just to get one stress off the list.

• Small team: Leads say yes to every “great opportunity” (partnerships, grants, events). Soon they’re stretched thin, always reacting, never building.

The Scarcity Loop

This is where it gets dangerous.

Each “borrowing” decision creates less capacity for tomorrow.

Less capacity → more pressure → more short-term decisions.

Scarcity → tunneling (when your mind focuses only on what’s right in front of you) → borrowing from the future → even less capacity tomorrow → deeper scarcity.

Again and again. Until there’s nothing left to borrow.

That’s why people and small teams can’t just “plan better.” They’re already spending tomorrow’s energy to survive today.

What This Means for Small Teams

In small teams, nonprofits, or any resource-limited setting, this loop is everywhere:

• Strategy and documentation get skipped in favor of urgency.

• Recovery time is the first thing to go, so burnout becomes routine.

• Leaders and managers overcommit, spending personal energy that never gets refilled.

How to Stop Borrowing from the Future

1. Leave Some Room

Even in crisis, protect a small pocket of slack: one unbooked day, one unallocated budget line. That’s your oxygen.

There’s a great rule I use when planning budgets: always set aside at least 15% for the unexpected. Always.

If things get tight, cut other lines, simplify production, find cheaper options, but don’t touch that 15% until the storm actually comes

That’s how you build flexibility right into the system.

2. Learn to say no, even to good things

Learn to say no to opportunities, ideas, and even to yourself (we all know the difference).

Sometimes very yes today is a no to something tomorrow.

Be clear about what you’re trading off: time, energy, trust, or focus.

3. Take Time to Reflect (Even Briefly)

One effective way to break the scarcity loop is to pause and reflect before moving on to the next thing.

A short retrospective (there’s always 30 minutes for the right kind of work, even when everything feels like it’s on fire) helps you see what drained you, what actually worked, and what can be done differently next time. It turns exhaustion into learning.

4. Don’t Blame Yourself

When everyone is constantly overwhelmed, it’s not about motivation or discipline.

It means the system is built on overcommitment: too many tasks, not enough resources.

And if shit has already happened, the last thing you need is self-blame. Your mind is overloaded enough. Don’t waste what’s left of it on guilt.

Use that energy to understand what went wrong and to build a better setup — for your next project, your team, and your future.

Amin! 😉

A strong idea will succeed no matter what? It’s a common thought, often repeated.

But that’s not what I mean. I see an idea, a concept, as a resource in itself — just like budget, time, people, or expertise. And this resource is often undervalued.

No, it won’t replace everything. But it can anchor the project, shift focus away from limitations, and even compensate for what’s missing.

Here’s what well-shaped concepts can offer in resource-limited projects:

1. Redirects attention

When a project lacks resources, it will have weak spots: a clunky website, basic visuals, or imperfect processes. A strong concept helps shift attention away from what’s missing and toward what matters — the idea. It becomes the first thing people notice and remember.

A good piece of copy can grab all the attention, pushing free stock photos or Canva templates into the background.

2. Turns constraints into narrative

Sometimes, a limitation can become part of the story. Instead of saying “we didn’t have money for a stage” you choose an apartment setting because intimacy matters more to you and to your audience.

3. Offsets functional flaws with emotional value

When you can’t deliver something technically perfect, you can still deliver aesthetic, emotional, or symbolic value. People often forgive imperfections if they feel the project “gets them.”

But there is a catch: in that case, consistency becomes incredibly important. In some of our projects, we use ready-made Figma templates simply because we don’t have the budget for a designer. And in those projects, we follow just two rules:

• keep it minimal (easier to maintain)

• keep it consistent.

Believe me, we get just as many comments like “this looks great” simply because everything is clean, simple, and steady.

Or take another example: if I were helping a shelter run its social media, I’d drop design altogether and focus only on photos, narrative, and text. Just the cutest faces, nothing else. And that’s exactly what many in this field already do. Because it works.

4. Motivates the team and satisfies the makers

A strong concept isn’t just external; it matters internally, too.

It can be the one thing that gives creators a sense of pride or joy, especially when everything else feels like a compromise. At least we know what those compromises are for.

5. Reaches the right people

When there’s no money for promotion, a clear concept can become its own form of targeting.

Message, tone, and aesthetic can help attract exactly the people the project is meant for, sparking word of mouth, shares, reposts in groups and chats.

6. Conceptual thinking creates legitimacy, even at a small scale

In nonprofit or grant-funded projects, the issue is often not just delivering something, but making it look intentional and aligned with the mission, even when modest.

A strong concept helps:

• create a sense of coherence,

• explain trade-offs through values,

• and make the project feel credible to stakeholders (funders, boards, or clients).

I can’t even remember the full context or the project itself, to be honest. It was some kind of a fashion show production I was involved in more than 15 years ago.

I remember a line someone on the team threw out half-seriously:

“Conceptual thinking is the best cover for scarcity.”

For a long time, it was just a meme. A line we’d repeat when things were falling apart, but the idea still looked good.

Eventually, I realized that behind this ironic phrase was more than just lived experience.

There’s a whole set of approaches and practices that describe how strong projects can be built under resource constraints.

I’ve always been curious about where the line lies between digital maturity and tool fetishism.

In the projects and organizations I’ve worked with, we’ve regularly introduced new tools and sometimes out of necessity, sometimes as part of a broader strategy. Still, every now and then (thankfully, not too often → credit to the teams), I’d hear: “Another tool? Again? He’s obsessed with tools.”

For me, the distinction is fairly simple:

• Digital maturity is a process of growing alignment between tech, people, and purpose.

• Tool fetishism is a dead end and a false performance of progress.

Signs of Digital Maturity

1. Technology supports goals. It doesn’t dictate direction.

2. Culture of learning and adaptation. New tools are adopted through team engagement and support, not dropped with a tutorial link and hope.

3. Stable, repeatable processes. Work doesn’t collapse when one person is away. Knowledge isn’t trapped in someone’s head. It’s distributed, shared, and sustainable.

4. Knowledge is managed and accessible. Everyone knows where to find things. Information lives longer than a Teams chat. What’s created is stored, shared, and built upon.

5. Decisions are based on data and observation. Not “that’s how we’ve always done it,” but “that’s what the evidence shows.”

6. Integrated tools and workflows. Systems talk to each other: no duplicate work, no isolated platforms. Tools function together, not just coexist.

Signs of Tool Fetishism

1. Tech FOMO. Tools are adopted out of fear of missing out: “Everyone’s using it, we should too.”

2. Constant tool-hopping. One month it’s Google Forms, then Typeform, and then Airtable Forms, but no one knows where the data lives.

3. Interface over impact (it’s all polished and smooth in our age of perfect UX, after all!)

4. Ignoring the team’s digital capacity.

5. No implementation, just installation. A tool gets introduced, but there’s no onboarding, adoption strategy, iteration, or support.

What I call tool fetishism isn’t always intentional. It’s a symptom that can show up even on the path toward digital maturity. And I feel it myself from time to time.

I love planning.

Seriously. Give me a task or a goal, and I will break it down into tiny, beautiful pieces. Market research, budget, business model, project timeline, roles, a clean design system, a sharp value proposition, and neat mind maps. I’m genuinely good at this.

And it feels… satisfying.

Sometimes it feels like the work is already done.

I once finished preparing a budget for a large festival and realised I felt almost as much pleasure as if we had actually run the event. In my head, everything was there: the venue, sponsors, programme, a huge audience. It all made sense. Conceptually perfect. Almost emotional.

This strange feeling — when preparation gives you a sense of completion — is what made me want to write this.

The problem: Planning as a proxy for progress

We usually think bad planning means underestimating time or resources.

But this trap is different.

• You plan, and it feels productive.

• You refine, revise, rearrange, and brainstorm. It feels like progress.

• You get a dopamine hit from “figuring things out”.

• And you delay starting the actual work.

Fabio Rosato calls this the Planning Trap: when planning becomes an end in itself, not a tool for action. Planning feels safe and controllable, while doing the work feels risky and uncertain.
Source: fabiorosato.com/posts/planning-trap

Easy Momentum puts it even more directly: planning becomes procrastination in a tailored suit. You tell yourself you’re preparing, but in reality, you’re postponing the moment when things get messy, hard, and unpredictable.
Source: easymomentum.substack.com/p/how-planning-became-the-new-procrastination

Anna Kornick connects this to overplanning and analysis paralysis: too many variables, too many scenarios, too many versions of what “launch” should look like — and nothing ever ships.
Source: annadkornick.com/overplanning-and-analysis-paralysis/

The Paralysis of Planning in small teams

Big organisations have deadlines, KPIs, managers, stakeholders, and external accountability. In a 30-person team, someone will eventually ask, “Where’s the deliverable?” And the project ships because it has to.

In small teams or solo projects (like my Make It Work), that pressure often doesn’t exist. Time and results are self-regulated. There is no weekly stand-up where you must show progress.

No boss defining what “done” means.

There’s also something else we don’t talk about enough: the fear of launching as a public act. It’s one thing to say, “Look, our team or organisation launched a project.” It’s a very different thing to say, “I am doing this.” That moment triggers impostor syndrome, fear of judgment, and fear of being seen. Planning becomes a safe hiding place. You’re “working”, but you’re not yet visible.

So the move from planning to doing becomes an internal decision, not something forced by external pressure. And that makes it much harder. Staying in the comfort zone of plans is easier than stepping into imperfect action.

This is why small teams and solo builders get stuck in planning loops more often than large organisations with formal structures.

Signs you and your team are in the planning trap

1. You’re stuck in planning mode. Plans keep growing, while real tasks get smaller.

2. You feel productive without output. Planning gives you a real sense of progress.

3. You feel overwhelmed by decisions and options.

4. Revisions beat execution. Every week, you rewrite the plan instead of building.

5. You’re chasing perfection before starting.

6. You avoid the actual work. Launch is delayed because “something is still missing”.

What to do about it

1. Time-box planning

Give planning a strict limit. For example: two hours, then stop. Everything (revision, rethinking, reflection, other amazing re’s!) only after the action

2. Use the “Good Enough” mindset

“Good enough now” beats “perfect later/never”. Feedback comes only from things that exist in the real world, not from your head. If it doesn’t directly move something into the real world, it doesn’t belong in the planning phase anymore.

3. Create a Power Hour

One hour with no planning, no optimisation, no improvements. Just action. Even if the result is rough.

4. Set action triggers

An action trigger is a rule that tells you when planning must stop and action must start.

For example:

• After the first draft, I publish.

• After one screen, I put the page online.

• After one post, I don’t think about the content strategy.

This removes emotion from the decision and replaces it with a simple rule.

5. Add external accountability

Even if you work alone:

• Make public commitments. Tell your partner that Thursday is launch day. Tell a friend you’ll show something before Friday beers.

• Set weekly check-ins. A short, recurring moment where you answer one question:

  What did I actually ship this week?

A small amount of external pressure helps turn intention into action.

Planning isn’t the problem. Without a plan, you’ll probably just stay stuck.

The trap is when you start confusing preparation with progress. You spend hours on a perfect Notion board or a strategy deck, and it feels like work.

A first step based on a “good enough” plan beats a perfect plan that never leaves your head every single time.