Jeroen Sangers

A vividly imagined future lets you feel whether you actually want it

Sat, 10 Oct 2026 09:00:00 +0200

When you really picture a future situation, with the place, the people and the small details, you are doing more than daydreaming. Your brain builds a scene out of what it already knows: memories, facts and past experiences, recombined into something that does not exist yet. The more concrete the scene, the more believable it becomes.

Then your brain starts looking around. Which needs could I meet here, which goals move closer? The motives that come up first tend to matter most, because they come straight from your deepest values. At the same time you know which behaviour usually works out well for you: a walk when you are stuck, cooking after a bad day, replying right away to someone you care about.

Finally, the feelings arrive. You get a preview of what that future is like: pride, relief, boredom, loneliness. That preview is information. It answers a question a list of pros and cons cannot reach: is this a future I want to wake up in? And if so, what can I do today to make it more likely?

So when a choice is hard, it pays to do more than calculate. Spend a few minutes living each option concretely, as if you were already there. What you feel then belongs in the decision. It may be the best data you have.

Content is an asset with a lifespan: fleeting content wins an audience, lasting content builds the business

Fri, 09 Oct 2026 14:25:00 +0200

Every piece of content you make has a cost, the time or money to produce it, and a value that can then stay, grow or shrink, just like physical assets. That value axis is the real choice you make with each piece, more than the format or the platform.

Fleeting content, such as a Reel or a post, is valuable the moment it goes out, but that value disappears almost immediately, unless you use it to attract a new audience. Lasting content, such as a course or an email sequence that keeps converting, often costs more to make, but its value compounds: it keeps working long after the publication date.

Spreading yourself across too many platforms mostly feeds fleeting content, which leaves no time to build the lasting assets that carry the business in the long run. Deliberately limiting the number of platforms is therefore the condition for working on something that lasts.

How visible you are says nothing about how fulfilled your life is

Thu, 08 Oct 2026 15:58:00 +0200

We have started using visibility as the measure of a fulfilled life: how large your network is, how many conversations you keep going at once, how often you show yourself. The underlying assumption is that depth translates itself outward into output and connection. But that is an assumption, not a law, and the people who live most deeply are rarely the loudest.

The real measure is something else: can you experience a moment fully without immediately turning it into a strategic goal? A sunset is then just a sunset, not a photo opportunity. That ability to be present without managing the experience is rarer than it seems, and it produces no content, so the systems around us never reward it.

The tricky part is that the performance of an inner life, with its morning walks, gratitude rituals and carefully shared insights, has become almost indistinguishable from the real thing. The only difference: the performance always happens within a frame of broadcasting, and the real thing happens precisely when nobody is watching.

Removing your own ability to give in makes you stronger in a negotiation

Wed, 07 Oct 2026 09:33:00 +0200

If you can always give in a little more in a negotiation, you automatically give the other side a reason to keep pushing: after all, there is still room. The counterintuitive solution is to remove that room yourself. Give up, in advance, the authority to move any further, and the pressure disappears. Not because you negotiate harder, but because there is simply nothing left to gain by insisting.

This is exactly what a salesperson does with “I’ll have to check with my manager”: they can no longer make concessions themselves, so they become much harder to move than if they could make the call. You can use the same mechanism for yourself by giving a third party the deciding vote: a partner who has to agree, or a fixed threshold above which you automatically pause. You stay the friendly, reasonable person, while the room to negotiate is fixed somewhere else.

The pattern also works against you when you don’t recognise it. Every time you say “in principle” or “usually”, you signal, without meaning to, that the exception is open for negotiation. A boundary that leaves no room for interpretation rarely gets tested.

Delegating a task without the why delegates the action, not the judgment

Tue, 06 Oct 2026 14:38:01 +0200

Almost any task beyond the basics requires decisions along the way: which version, which tone, how much depth. If you hand over only the instruction and not the reason behind it, the other person has nothing to hold on to except that instruction. The moment the situation drifts from what was written down, there is nothing to fall back on, and the work lands back on your desk for you to decide.

That is why delegating without explaining often feels like losing time rather than gaining it. You get back something that doesn’t quite fit and end up redoing it. It works the other way too: when someone delivers far more than needed, it is rarely slowness. More often the scope was unclear, and they assumed more depth than a few bullet points required.

The why of a task is only half of it. The other half is your general judgment, which usually lives in your head: whom you consult first, what you need to know before committing, how you weigh cost against quality. Make it explicit and your team can decide without waiting for you. Two concrete things help. First, say what “good enough” means right now, because under a heavier workload the bar tends to drop and nobody says so out loud. Second, set the threshold for escalating: from which client, which amount or which risk you want to be told.

That is the difference between delegating tasks and delegating authority. With the first, the work leaves your desk but the decisions keep waiting for you. With the second, both leave, and the task makes more sense to the person doing it, because they can see where it fits.

The real win in delegating is letting go completely, and that takes competence

A goal only counts as a goal when you can force the outcome yourself, otherwise it is a dream

Wed, 23 Sep 2026 19:55:35 +0200

We often call something a goal when it is really a dream: an outcome we want, but one that depends largely on other people’s decisions, on timing or on luck. Making the bestseller list, hitting a revenue target, getting hired: it feels concrete and measurable, so it gets the label “goal”. But as soon as someone else decides the result, your own effort becomes necessary without being enough. That difference is exactly why SMART goals so often frustrate. They check whether a goal is specific, measurable and time-bound, and never ask who holds the outcome.

The distinction is more than semantics. It shapes how motivation behaves. As long as you see a clear link between your effort and the result, intrinsic motivation holds up. Once that link breaks, a downward spiral begins: a weaker sense of control leads to less effort, less effort produces a worse result, and that result confirms the feeling of helplessness. A dream treated as a goal undermines the very motivation the goal was meant to spark.

The answer is to keep the ambition and rewrite the goal into something that sits entirely in your own hands. Instead of “bring in 2 million euros in revenue”, the goal becomes “hold 40 sales conversations”. The dream, the revenue, stays in place as a direction, while the goal itself moves out of reach of external factors. That also makes it more unforgiving: there is no market, no competitor and no bad timing left to blame. You either did it or you didn’t.

The real win in delegating is letting go completely, and that takes competence

Mon, 21 Sep 2026 09:00:00 +0200

When you delegate, you hope to save time. But the win you actually feel is a different one: you hand something over and stop thinking about it. No checking back, no low hum of worry, no drama. That only happens when the person you delegate to does it well, does it on time and does it without fuss. Delegating to competence is the one kind of delegating that empties your head; every other kind moves the work from your hands to your attention.

Few people know that feeling. Until recently it was reserved for those who worked with exceptional colleagues or teams. AI assistants suddenly put it within reach of many more people, and that explains a large part of the excitement around them: not the technology itself, but the new experience of being able to let go.

The catch is in the word competence. The first time you hand something over, to a colleague or to an AI, the verdict is often: it doesn’t get me, it did it wrong. That is rarely the receiver’s fault and usually the brief’s: saying precisely what you want is hard, and the context that is obvious inside your head is missing on the other side. If you want the relief of letting go, invest first in clarity and context. Competence on the other end is half the story. The other half is that you make it possible for them to be competent.

Delegating a task without the why delegates the action, not the judgment

Shared rituals give a team meaning, and they work best when the team invents them

Fri, 18 Sep 2026 09:00:00 +0200

A ritual is a habit that has picked up meaning. That is the whole difference: a habit is what you do, a ritual is how you do it, with attention and with intent. Brushing your teeth is a habit. Always brushing before you shower, and finding it odd the other way round, has become a ritual. The reversed-order test is a tool rather than a definition: it points to the place where an action has acquired meaning.

People use rituals to steer their mood: to calm down before a performance, to gear up for a hard task, to wash the workday off. Telling yourself to relax rarely works, because failing at it feels like one more failure. A familiar pattern does work, because it asks for repetition rather than achievement.

In a team, a shared ritual does something extra. People who perform a small ritual together before they start, even something as silly as tapping their shoulders and stamping their feet, rate the work that follows as more meaningful than people who do the same ritual alone. Tea at a fixed hour on a fixed day, closing every meeting by naming one thing a team member pulled off, sharing weekend plans before the agenda: small things, and precisely because they wear in, they start to carry meaning. Fast-growing companies build their whole planning cadence as a series of rituals for the same reason, so everyone knows what each moment means.

Imposed team building beats doing nothing, even when everyone complains: at least they hated it together. A ritual announced from above, six claps and three shouts at the start of every meeting, mostly harvests eye rolls. Let the team invent its own. A leader’s job is to make the room where a ritual can emerge, and then to protect it, consistently.

A habit is unconscious behaviour that is automatically triggered by an impulse

Thu, 17 Sep 2026 16:38:03 +0200

Currently reading: Conquest of Happiness by Bertrand Russell 📚

Behaviour follows its consequences: what gets rewarded grows, what gets punished fades, and what gets rewarded irregularly sticks best

Thu, 17 Sep 2026 09:39:05 +0200

Voluntary behaviour is shaped by what follows it. When an action brings something pleasant, the odds that you repeat it go up. When it brings something unpleasant, they go down. You never have to decide any of this: behaviour adapts to its consequences whether you notice or not.

Underneath that sits a second layer that is easy to miss. It is not only whether a reward arrives that counts, but when and how often. The same behaviour with the same reward can be learned fast or slowly, and can stick weakly or strongly, depending purely on the rhythm in which the reward is handed out. That rhythm is called a reinforcement schedule.

The surprising part is that irregular rewards work better than constant ones. Behaviour that is rewarded only some of the time lasts longer, even after the reward disappears. The logic, as Scott Young lays it out, runs like this: a predictable reward that stops has probably run out. An unpredictable reward that stops may just be a pause, so carrying on pays. That is the mechanism behind the slot machine and behind the apps you keep opening. Once every reward is gone for good, the behaviour slowly sinks back to its old level.

For anyone building a habit, breaking one, or steering a team, this is a practical handle. A child who gets a compliment right after finishing homework learns something different from a child who hears it at the end of the week, and an employee who knows good work gets seen repeats that work. If you want to change behaviour, look beyond the reward itself to the moment and the rhythm in which you give it.

Motivation grows with the perceived distance to the goal, not the real one

Motivation grows with the perceived distance to the goal, not the real one

Tue, 15 Sep 2026 16:09:45 +0200

The closer you get to a goal, the harder you push. A marathon runner who spots the finish line suddenly finds energy that was nowhere to be found a kilometre earlier. That is not willpower, it is proximity: the reward comes into view and the effort pulls itself along.

What makes this interesting is that the brain responds to perception here, not to facts. A loyalty card with twelve boxes, two of them already stamped, gets filled faster than an empty card with ten boxes, even though the work in both cases is exactly ten stamps. The head start is fictional. The acceleration is real.

That is the lever for anyone who wants to get themselves or others moving. Give a head start, so the first step already looks taken. Make progress visible, so the distance to the finish becomes something you can feel. And cut a big goal into small milestones, so there is always a finish nearby instead of one far away. The effect is strongest in people who feel they have little power or security; those who already feel comfortable need the proximity less.

An indexed PKM of sources and personal syntheses makes a truly personal AI possible

Mon, 14 Sep 2026 09:21:38 +0200

The usual way to give an LLM your documents is to upload them, or to plug in retrieval (RAG). For every question the model hunts down the relevant fragments in the raw sources and pieces together an answer. It works, but nothing builds up. A question that combines five documents gets answered from scratch again next time.

The alternative is a PKM in two layers. The sources sit untouched in a raw layer. Above them lives an indexed layer of summaries, concept notes and cross-references that gets updated with every new source: contradictions flagged, the synthesis revised. Knowledge is compiled once and then kept current. When a question comes in, the LLM reads the index first and then the relevant notes. Up to a few hundred notes that is enough, with no search infrastructure at all.

What turns this into a truly personal AI is the feedback loop. A good answer, whether a comparison, an analysis or a connection you spotted, goes back into the system as a new note. Your own explorations pile up the same way your sources do. The system then holds what you read and what you thought about it, and every next question draws on both.

A PKM built from sources plus atomic notes already has those two layers. The LLM only needs to do the maintenance: indexing, cross-referencing, checking for consistency. Once the system grows large enough, fine-tuning is the next step, so the knowledge lives in the model’s weights instead of its context window.

Sun, 13 Sep 2026 18:54:03 +0200

Finished reading: Duizend schitterende zonnen by Khaled Hosseini 📚

I had a bitter sheet feeling at the end of the book, since I know How Afghanistan has changed since this book was published..

Mon, 07 Sep 2026 22:32:20 +0200

📸 Etna

AI lowers the threshold for building tools, but that is not where business transformation stalls

Fri, 04 Sep 2026 10:15:37 +0200

Anyone can now have a tool built in five minutes by asking a model, without writing a line of code. That feels like a breakthrough if you build tools for a living. Most people do not. As Benedict Evans puts it, a great lawyer spends the day thinking about the case and the client, not about which software would make that work faster. So the bottleneck sits somewhere else: in seeing that there is something to automate at all, and in working out what the right solution actually is. That second part is rarely obvious. It can take years and several failed attempts before someone finds the right shape for a problem.

Even with the right tool in hand, the work is not done. A process touching fifty to five hundred people across departments and systems stops being an individual decision and becomes a purchasing project that runs for months. Software moves on a sliding scale between improvised (a spreadsheet, an email) and institutionalised (a system with audit, security and ownership), and a task slides toward the institutional end once there is enough revenue or risk attached to justify it. AI leaves that scale intact. It moves where the thresholds sit and which choices you have.

This is why giving everyone ChatGPT never turns into company-wide change on its own. It is the same pattern as putting a PC with a spreadsheet program on every desk in the early eighties: a small group took off with it, the rest used it now and then. The real transformation lives in the slow, concrete work of going through every existing process, one at a time.

Productivity doesn't come from working longer, but from letting your brain reset

Thu, 03 Sep 2026 09:00:00 +0200

Your brain does not multitask, it switches, and every switch leaves a residue of attention behind that eats into your cognitive capacity. That is where uninterrupted blocks earn their keep: inside such a block you work on one thing, with no notifications and nothing on the side.

A block like that has a shelf life. After a stretch of sustained attention your sharpness drains away on its own, and a workday without breaks, an open-plan office and a chat that never falls silent hold you in that state of low attention and constant stress. Pushing on feels productive at that moment, while the quality of your thinking has already dropped.

So blocks and breaks do not contradict each other, they work on two timescales: no switching within the block, a reset between blocks. In practice that means stepping away briefly every 60 to 90 minutes without new input, plus a clear stopping time at the end of the day, because it is in those quiet moments that your brain consolidates and creativity comes back. What wrecks your attention is the task switch, not the break.

Three fixes, one worked, and I don’t know which

Wed, 02 Sep 2026 11:00:00 +0200

This site looks different today, and that was not the plan when I sat down with my coffee.

For weeks I had known that the Photos and Archive pages were broken. Both quietly served up the home page instead of my photos or a dated list of everything I ever posted. Nothing crashed, nothing warned me. The pages just answered the wrong question, which is the kind of bug that is easy to keep postponing. Today I gave it a coffee break.

The micro.blog help forum offered three things to try, so I tried them in order. A newer version of Hugo: no effect. Disabling my custom theme: no effect. Installing and activating a new theme plugin: both pages came back to life.

The plugin I picked more or less at random was Mythos by Matt Langford, and I like it enough to keep it. So this is the new look now. I might bring back a few orange details later.

What I still do not have is an explanation. Three changes went in, one of them fixed it, and I have no idea which of the other two was innocent. My pages work and my curiosity does not. For a coffee break, that is a fair trade.

The Instagram algorithm tests new content on people who don't follow you yet

Wed, 02 Sep 2026 09:00:00 +0200

When you post something, the platform first shows it to a small test audience of people who do not follow you, and it watches closely: do they swipe past, how long do they stay, do they react at all. If they drop off, the algorithm concludes that strangers have no interest in this and stops showing it. That is the mechanism behind the feeling that your reach dies. It is not a punishment. It is a test you lost.

That changes the question you should be asking. Not “is this content good”, which is a judgement made from your own taste or that of your regular audience, but “does this work for someone who has never seen me before”. If you optimise only for the people who already follow you, you are optimising for an ever smaller slice of your own reach.

The consequence is that generic, broadly phrased content loses structurally. A stranger has no reason to keep watching something he has seen a hundred times before, phrased in exactly the same way. Being specific and recognisable for your own position works better with strangers than with existing followers, because that is precisely what survives a test swipe.

Tue, 01 Sep 2026 15:20:59 +0200

Nicholas Bate (@HG21C) explains how to brief your AI.

You optimise a system by looking at the whole flow, not by making the fastest part faster

Tue, 01 Sep 2026 09:00:00 +0200

A process is a chain of steps, and it is tempting to improve the step that is easiest to see, or the one that seems most obvious. But making a step faster only helps if that step is the bottleneck. If it is not, the work piles up in front of the next step, which is still the real constraint.

The question that matters is not how to make one part faster, but what a change does to the whole flow. Skip that question and you optimise inside an illusion of progress: a fine result at one station, while the total lead time stays the same or gets worse.

This holds for personal effectiveness as much as for a production line. Finishing a task faster only helps if that task is where the work gets stuck. Otherwise you are just moving the queue.

Start with as little as possible and add complexity as you go

Self-control is a learnable skill, not an innate trait

Mon, 31 Aug 2026 09:00:00 +0200

We usually read self-control as a character trait: you have it or you don’t. Walter Mischel’s marshmallow test fed that picture, because the children who waited longer turned out, decades later, to earn more, be healthier and have stronger friendships. Kentaro Fujita points at the finding that got skipped over: those children were being taught strategies, and the strategies worked. Three-year-olds stare at the marshmallow on the assumption that staring helps. Five-year-olds have already worked out that covering it up or looking away works better. By thirteen, the children who understood the rules of self-control had fewer behavioural problems. The route is known too: children pick it up largely by watching what adults do.

The distinction that makes this possible is that willpower and self-control are two different things. Willpower is the blunt version, suppressing the impulse, and training it produces small and erratic effects in the research. Self-control is the toolkit around it: looking away, reframing the temptation, viewing yourself from a distance. Those strategies do transfer, so you can get much better at self-control without ever gaining more willpower.

That also changes what a slip means. Not that your character falls short, but that this particular tool failed here, and the question becomes which tool you try next.

Whether you think you can or think you can’t, you’re right

Structure is cheaper than intelligence

Sun, 30 Aug 2026 09:00:00 +0200

Ask a language model something about your own life and it has to guess. It never saw your data, so it reconstructs what is probably true, and every so often it hands you something that never happened. No amount of clever phrasing fixes that. Guessing is what generation is.

A well structured knowledge base works the other way around. It looks things up and gives back what is there, with the source attached and with how certain that source is.

Underneath sits a ratio worth remembering: roughly 98 percent of a “Digital assistant” system is data, 2 percent is AI. And that 2 percent does translation, not thinking. It understands that “called Joe about the fieldlab” is a phone call, that Joe is a person and that fieldlab is a project. Nothing more is asked of it.

Every layer of structure you add makes the AI layer thinner.

What looks like intelligence usually turns out to be retrieval. Who should I call is a sort on contact strength and time. This pattern stands out is a count. What did I do last time is a lookup in history. Query, weigh, show. A simple search over a clean schema beats a brilliant model over messy data.

That reframes where the work goes. The interesting question stops being which model you use and becomes how well your own material is organised. Naming things consistently, linking them, recording the type of a thing rather than leaving it as loose text: each of those shifts work out of the model and into the schema, where it stays put and costs nothing to run.

You still need a large model while the schema is being discovered. That is the architect designing the house: which tables relate to which, where the structure has gaps, which patterns hold. Once the house stands, you can live in it without the architect. What remains is small enough to run on your own laptop, no cloud and no dependency on a vendor who might change the terms next year.

So the useful measure of a personal system is not how smart its assistant is. It is how much of your life the assistant can simply look up. Every time you tidy a corner of that, you need slightly less intelligence to make sense of it.

Use AI to reduce unnecessary difficulties, not to avoid essential effort

Time management training leaves volition alone

Sat, 29 Aug 2026 09:00:00 +0200

Time management training is popular. The evidence that it works is thin.

The critique that landed hardest for me: these trainings teach planning and structuring, and they leave volition alone. Volition is the capacity to protect an intention against everything competing with it. Distraction, a colleague at your desk, the pull of an easier task.

Planning and structuring your activities may simply not be enough to keep an intention alive once the day starts pushing back.

Kuhl and Fuhrmann pointed at what is missing: strategies that work on motivation rather than structure. Finding meaning in a task. Making it more attractive to start. Deciding in advance what you do when the pull arrives.

That reframes what a good system is for. Not a better container for your work, but something that keeps you willing to do the work you already decided mattered. Structure gets you to the desk. Something else keeps you there.

Fri, 28 Aug 2026 09:29:14 +0200

The top use cases for AI in 2026 are:
Therapy and companionship
Troubleshooting
Fun and nonsense
Fan fiction and storytelling
Technical use of software
Autonomous agentic operations
Relationship advice
Work buddy
Astrology and tarot readings
General advice

Marc Zao-Sander https://hbr.org/2026/06/how-people-are-really-using-ai-in-2026

My use cases are 6, 5, 2, 10, and a little bit of 8. Might need to look into Astrology and tarot readings though, as it seems a natural fit for AI’s hallucinations. 🤪

Implementation intentions correct the planning fallacy

Fri, 28 Aug 2026 09:00:00 +0200

A to-do says what. An implementation intention says when, where and how.

“Write the proposal” is a task. “I write the proposal tomorrow at nine, at the kitchen table, before I open my mail” is an implementation intention. Gollwitzer named them in 1999, and the difference turns out to matter more than it looks.

Koole and van ’t Spijker found that people who wrote their plans this way completed more of them and were interrupted less often.

They also help with the planning fallacy: our habit of estimating how long something takes by imagining it going well. No traffic, no interruptions, no discovering halfway through that the file is somewhere else. Specifying the circumstances forces the obstacles into view before you commit to a time.

It costs about ten extra words per task. That is a cheap correction for a bias that has been wrecking estimates for as long as anyone has been making them.

Jeroen Sangers

A vividly imagined future lets you feel whether you actually want it

Content is an asset with a lifespan: fleeting content wins an audience, lasting content builds the business

How visible you are says nothing about how fulfilled your life is

Removing your own ability to give in makes you stronger in a negotiation

Delegating a task without the why delegates the action, not the judgment

Related

A goal only counts as a goal when you can force the outcome yourself, otherwise it is a dream

Related

The real win in delegating is letting go completely, and that takes competence

Related

Shared rituals give a team meaning, and they work best when the team invents them

Related

Behaviour follows its consequences: what gets rewarded grows, what gets punished fades, and what gets rewarded irregularly sticks best

Related

Motivation grows with the perceived distance to the goal, not the real one

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An indexed PKM of sources and personal syntheses makes a truly personal AI possible

Related

AI lowers the threshold for building tools, but that is not where business transformation stalls

Productivity doesn't come from working longer, but from letting your brain reset

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Three fixes, one worked, and I don’t know which

The Instagram algorithm tests new content on people who don't follow you yet

You optimise a system by looking at the whole flow, not by making the fastest part faster

Related

Self-control is a learnable skill, not an innate trait

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Structure is cheaper than intelligence

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Time management training leaves volition alone

Implementation intentions correct the planning fallacy

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