[All ideas](https://jardenberg.com/ideas) Essay # We will all be hackers: the origin story. Before replacing subscriptions, there was Karin, an executive assistant at Volvo Group, a frustrating task and a conversation with Copilot. How a small text hack became an experience of agency. 23 October 2026EssayAI + JJ ## The short version - Karin used Copilot to turn a Teams attendance report into a usable list, replacing a recurring sequence of individual copy-and-paste steps. The person with the problem gained a way to change the method. - She already understood her work. AI helped her turn that expertise into action, with a small first technical step and support from an ongoing learning journey. - Her discovery brought all Four Jobs into view: doing the work, improving the method, learning through use and helping colleagues. Relief and confidence deserve attention alongside time saved. - This companion to today's Rebrandly essay moves backwards in the timeline, towards the individual. The wider promise of more people gaining this kind of agency remains something to pursue and test. [Read the full story](https://jardenberg.com/ideas/we-will-all-be-hackers-the-origin-story#the-full-story) In this essay - [The person who knows the work](https://jardenberg.com/ideas/we-will-all-be-hackers-the-origin-story#the-person-who-knows-the-work) - [One small technical step](https://jardenberg.com/ideas/we-will-all-be-hackers-the-origin-story#one-small-technical-step) - [Then a colleague asks a question](https://jardenberg.com/ideas/we-will-all-be-hackers-the-origin-story#a-colleague-asks) - [From n00b to first-grade hacker](https://jardenberg.com/ideas/we-will-all-be-hackers-the-origin-story#first-grade-hacker) - [All Four Jobs, in one ordinary task](https://jardenberg.com/ideas/we-will-all-be-hackers-the-origin-story#all-four-jobs) - [Relief counts](https://jardenberg.com/ideas/we-will-all-be-hackers-the-origin-story#relief-counts) - [The foundation and the freedom](https://jardenberg.com/ideas/we-will-all-be-hackers-the-origin-story#the-foundation-and-the-freedom) - [What the story establishes](https://jardenberg.com/ideas/we-will-all-be-hackers-the-origin-story#what-the-story-establishes) - [Where to begin](https://jardenberg.com/ideas/we-will-all-be-hackers-the-origin-story#where-to-begin) Karin had an attendance report and a task she had done far too many times. Open the report. Copy a name. Switch to Word. Paste it into the template. Go back. Copy the next name. When I tell this story in a room, I sometimes demonstrate the sequence. It takes very little repetition before people begin to feel uncomfortable. Then I ask them to imagine doing it again after the next meeting, and the next, for years. Karin found a way to change that. She copied the whole report into Copilot and asked it to produce a list containing just the names. That was a small text hack. I keep telling the story because of what it meant for the person who made it. Earlier today, I published [We will all be hackers](https://jardenberg.com/ideas/we-will-all-be-hackers), about replacing Rebrandly, sharing JJ Links and the changes I see coming for software. This is its companion, published on the same day but travelling backwards in the timeline. Before my AI team replaced a subscription, Karin had shown me something about where hacking begins. ## The person who knows the work I met Karin through Next Step, a development programme for seventeen executive assistants at Volvo Group. I had initially been invited to deliver a short session about AI. We ended up working together throughout the seven-month programme, with regular AI office hours. That gave us time to bring actual work into the conversation. People could try something, show what happened, ask for help and return with another question. AI became something we could explore together in the middle of working life. Karin is one of my heroes from that experience. There is a spark in her eye, a willingness to try things and a very clear understanding of the work that needs doing. Her attendance report came from Teams. It contained information about the people in a meeting, but it did not arrive in the form she needed for her Word document. So she supplied the connection herself, one name at a time, repeatedly. She had wanted help changing this for a long time. The technical problem was small enough that someone with the right programming skills could have dealt with it quite easily. In the larger organisation, it had remained unresolved. That mismatch matters. A task can be small in an IT backlog and occupy a large place in someone's day. The person carrying it knows exactly how much irritation fits inside a supposedly minor problem. ## One small technical step Karin had decided to make Copilot part of her everyday behaviour. One way she described that decision was to fire Google and hire Copilot. It was a memorable trigger: when a question appeared, try a different first move. With the attendance report, she took all the text at once and asked Copilot for a bullet-point list containing only the names. I am paraphrasing the request here; its ordinariness is the point. The list came back in a form she could use. A repetitive series of individual copy-and-paste actions had become a much shorter operation. There was no application to build before she could benefit. She did not need to learn a programming language or persuade someone else to implement the first version. She could describe a transformation of text, look at the result and decide whether it helped. Her understanding of the desired outcome was already there. Now she had a means of acting on it. That is the moment I want us to pay attention to. A person who had been living with an awkward process discovered that she could change it herself. ## Then a colleague asks a question Karin brought her discovery to the other sixteen executive assistants in our office hours. The useful little hack became something we could examine together. A colleague wanted the names arranged differently. Another need was an email recipient list that could be pasted into Outlook, so the message would go to the people who had attended. Karin tried asking for those changes. The conversation developed: extract the names, arrange them usefully, provide the email addresses in the required format. She went on to combine the requests into a reusable instruction and share it. The first result gave her something to show. Her colleagues' questions gave her reasons to develop it. The group gained both a useful method and someone they could turn to for help exploring the next possibility. That sequence should sound familiar if you have read today's other essay. Johannes Sundlo asked me to make JJ Links open source. His question changed what I did with a solution I had originally made for myself. In both stories, a relationship expands what happens next. Someone sees a useful possibility, asks a question, and helps a private discovery become more valuable. Sharing carries practical knowledge and the confidence to try another thing. ## From n00b to first-grade hacker This is what I mean when I talk about going from n00b to first-grade hacker. You notice a constraint, try a way around it and gain some control over how your work happens. The word n00b needs care. Karin was an experienced professional. She knew the work, the people, the context and what a satisfactory result should look like. Her newness concerned this technical possibility. That distinction changes how we think about AI adoption. There is already a great deal of expertise in the room. A useful tool can give that expertise another route into action. The first step can involve almost no technical learning. Describe what you want in ordinary language. Try it. Inspect what happened. Ask for a change. Learning starts inside the attempt, close to something you already understand. Almost no technical learning is different from no learning at all. Karin was exploring, checking and refining. Our office hours and her colleagues helped make that possible. Access, encouragement and room to experiment were part of the experience. I use hacker to include someone like Karin. Curiosity and the ability to change a small arrangement belong in that word. We should make the entrance wide enough for people to recognise that they can begin. ## All Four Jobs, in one ordinary task My [Four Jobs framework](https://jardenberg.com/ideas/four-jobs) gives us a useful way to understand what happened. **Job 1: Do the work.** The attendance list still needed to be produced. Karin had commitments to meet and colleagues depending on the result. AI helped her perform that task. **Job 2: Improve how the work is done.** She changed the recurring method. Saving and refining the instruction meant the next attendance list could benefit from what she had learned this time. **Job 3: Improve yourself.** She developed her ability to work with AI through a problem she understood. Each useful refinement gave her another piece of practical knowledge and a reason to keep exploring. **Job 4: Develop the team.** She showed the others, shared the method and worked with their questions. Her learning became available to the group, and the group helped it develop. All four are present in the same episode. We do not have to imagine a long, formal progression before someone is allowed to improve the work or help another person learn. This is one reason I care so much about making room for Job 2. When every available moment is consumed by delivering today's work, the method can remain untouched for years. A small investment in changing it can affect every repetition that follows. The ability to improve a process can also lead to a more demanding question: why are we doing this task at all? An audience member raised that possibility when we discussed Karin's story in a workshop. It is a useful next question, rather than something I can claim Karin had already resolved. ## Relief counts It would be easy to turn this into a time-saving calculation. How many meetings? How many names? How many seconds per name? I do not have a measured before-and-after study of Karin's work, and I will not invent one. The repeated frustration and the relief I describe from this experience deserve attention in their own right. There is a particular burden in knowing that a process is absurd while feeling unable to change it. Each repetition reminds you of the gap between how the work happens and how you know it could happen. Discovering a way to act can change the experience of that task. You can try something, see whether it helps and adjust it. You have a useful contribution to bring to your colleagues. Those are meaningful changes in working life. In [Seven Value Vectors](https://jardenberg.com/ideas/seven-value-vectors), cognitive capacity and wellbeing sits alongside access, inclusion and agency. These are two places I particularly want us to look when considering AI's value. Karin's story gives us a concrete way to discuss them. Learning and shared knowledge are visible too. We can explore those connections without pretending one anecdote establishes every kind of value in the framework. And if a person finishes the day less depleted, that counts. We do not need to fill every reclaimed minute with another task before we are allowed to regard the change as worthwhile. There is a life to have after work. ## The foundation and the freedom The infrastructure distinction from the Rebrandly essay belongs here too. Karin worked within an existing digital environment. Teams, Word and Copilot supplied capabilities she could use. Her discovery changed a small connection between them, close to the task she understood. In JJ Links, Cloudflare handles the underlying redirects while my own tool gives me a way to manage them. The scale and implementation differ, but both stories involve making something more suitable around capabilities that already exist. I expect us to need more dependable foundations as more people begin adapting their own work. The freedom to try small changes becomes more useful when the underlying services are reliable and intelligible. That also gives an IT function a valuable role: make appropriate capabilities available, make the boundaries understandable and help useful discoveries travel. The people doing the work will encounter needs that a central team cannot anticipate individually. A small local improvement should have somewhere to go when others could benefit. Karin's office-hours group provided that route. An organisation can deliberately create more such places. ## What the story establishes This is my account as a facilitator who worked with the group, revisited through earlier workshop and keynote transcripts. It is a retelling of that experience, rather than a new interview with Karin or a formal evaluation of Volvo Group's AI programme. The concrete sequence is the evidence: a recurring task, a plain-language request, a useful result, colleagues asking for refinements, and a method developed and shared. My interpretation concerns what that sequence reveals about agency, learning and improving work. I have not established a quantified wellbeing outcome, a universal productivity gain or that everybody will find their first attempt this approachable. The continuing group support belongs in an honest account of what happened. My wider forecast is that many more people will gain ways to alter the digital arrangements around them. Some will make text hacks. Some will connect existing tools. Some will build applications or replace subscriptions. The extent and consequences of that shift remain open. The practical evidence is already enough to challenge a limiting assumption: that changing how digital work happens must always begin with someone who knows how to write software. ## Where to begin If you want to explore this for yourself, start with a small frustration in work you know well. Choose something whose result you can inspect. Bring it to an AI tool you can appropriately use for that material, describe the outcome and see what happens. Give yourself room to learn from the response. If it helps, ask what would make the next repetition easier. Then show someone. Their question may be the most useful next instruction you receive. If you lead people, protect some room for that exploration. Pay attention to the discoveries people bring back. Ask what became lighter, what they learned and whether someone else could benefit. Those questions make more of the value visible. I have told Karin's story many times because it makes a large idea tangible. The distance from enduring a frustrating process to changing it can be surprisingly short. An ordinary request can become a first experience of having more control. Today's two essays follow that possibility from different directions. One looks towards what happens to software and the businesses built around it. This one goes back to a person, her work and the discovery that she could do something about it. We will all be hackers. Karin helps me explain where we can begin. ## Sources and scope JJ's first-hand facilitator account of Karin's text hack during the Volvo Group Next Step learning journey, cross-checked against earlier workshop and keynote transcripts. Requests are paraphrased; interpretation and forecast are identified. Developed for publication on 23 October 2026. Writing: AI + JJ. - [Companion essay: We will all be hackers.](https://jardenberg.com/ideas/we-will-all-be-hackers) - [The Four Jobs](https://jardenberg.com/ideas/four-jobs) - [Seven Value Vectors](https://jardenberg.com/ideas/seven-value-vectors) ## Continue reading Editorial connections · AI + JJ [We will all be hackers.](https://jardenberg.com/ideas/we-will-all-be-hackers) · 2026-10-23 Published first, this companion follows the idea forward into replacing Rebrandly, sharing JJ Links and a forecast for software. [Seven Value Vectors](https://jardenberg.com/ideas/seven-value-vectors) · 2026-10-19 Look beyond time saved, especially towards cognitive capacity, wellbeing, learning and agency. Source: https://jardenberg.com/ideas/we-will-all-be-hackers-the-origin-story AI + JJ. Original human work and other people’s ideas retain their attribution. Joakim Jardenberg’s own writing: CC BY 4.0. Credit Joakim Jardenberg and preserve AI + JJ / AI translation attribution. Third-party quotations, recommendations, photographs, screenshots, logos and media retain their own rights and are excluded. Licence: https://creativecommons.org/licenses/by/4.0/