Hired for the workflow

In 2018 I wrote that the best way to get a job is to have one competitive advantage. One activity or task that you can do better than the person or company hiring you. In the 1990s, for a lot of companies, it was simply that you could use a computer. In the 2000s it was using the internet. In the early days of software development or security, all it took was good programming or hacking experience. The first edition then gave a list of what that advantage could be in 2018: ML/AI, graphs, chaos engineering, GitHub, Git, Jira, Creative Commons licences, continuous integration, AWS, WallabyJs.

I am not going to give you a list this time. In 2026 I think the answer is one thing: running agentic workflows. Knowing how to brief an agent, give it a boundary, check what comes back, and glue the pieces together until real work gets done. That is the advantage. This chapter is about why, and about the first place it shows, which is before anyone has met you.

This part is called Getting the job, or making it, and the "or" is deliberate. Its three chapters are written for the reader going into a job, because that is still where most people start. The same advantage is the one a founder needs, and Start the company takes that up. Read these chapters as a job seeker, then read them again as the person who will one day be on the other side of the table, hiring, or selling.

There was a time

I have lived this pattern before, in security and in software. There was a time when, if you could break an application, you had a job. If you could read code and do a code review, you had a job. If you could do threat modelling, you had a job. If you could program decently, it did not matter that you had no university degree; you could show what you could do, and you got hired. There was a time when building a website got you a job, and knowing how to send email campaigns got you a job. When Apple opened the App Store in July 2008, with more than 800 apps in its first weekend, people who could build a mobile app got jobs. So did people who knew Salesforce inside out, or could make a spreadsheet do things others could not.

Each of those skills later became normal. That is the shape of it: a skill is rare, it gets people hired on what they can show rather than on what their CV says, and then everyone is expected to have it. The 2018 book said the same thing in its own words: it might seem that the bar was lower then, but those who could do it were the ones who embraced the technologies and learned them against all odds. Individuals can become experts at a new technology faster than the tech companies can. You can be first in line when they need that expertise.

The last row of that table is now. The first phase of agents, the demos and the experiments, is behind us. The tools are getting more mature, the workflows too, and while they are still rough around the edges, you can already glue the pieces together and get real work done. Companies are moving from pilots to products. So this is the moment for the many people on the outskirts: paying a bit of attention, or using a chat window for basic questions, but not yet working this way. Get on with it.

You are more technical than you think

Here is something I hear a lot. Someone uses email, websites and apps at a very advanced level, and still says "I'm not technical". Nonsense. Of course you are technical. You learned all of those. Every one of them was once a new technique that got somebody hired, and you picked it up without a course. You just need to learn the new techniques, and right now the new techniques are the ones that get people hired.

I hear it from both generations this book is for. The final-year student who has lived online since childhood says it, because nobody ever called what she does technical. And the person who has run a pharmacy, a clinic or a legal practice for twenty-five years says it, while running every system in the building. Both are wrong in the same way. The student has every technique but the newest. The expert has every technique but the newest, and twenty-five years of knowing a problem on top, which, as Be a founder: the expert founders argues, is the thing that is now worth the most, because execution just got cheap.

The first edition had an outline on impostor syndrome that I never wrote up. Its one finished thought was this: everybody has doubts about their capacities and everybody makes mistakes; your value is in your ability to execute, and it is key that you learn to share what you do and be comfortable with what you create. I would keep every word of that. The person who says "I'm not technical" is describing a feeling, not a fact. The fact is what they can do, and what they can do is the only thing a hiring manager can see.

Operators, not model builders

The 2018 edition had a chapter on machine learning and AI. It said this was the next major revolution in technology, and that the question was whether you were going to be a player or a pawn in it. It said that, as a developer, you would soon be asked to write code that integrates with machine learning services. The direction was right and the detail was wrong: what arrived was not a library you call from your code, but software you can talk to, and that can build software.

The detail matters because of what companies did with it. In the first wave of corporate AI hiring, when there was a lot of budget, the only people companies knew how to hire were people who did machine learning and wanted to build models. LinkedIn's 2020 emerging jobs report put "AI specialist" at the top, defined by skills like machine learning, deep learning and TensorFlow. For most companies that was the last thing they needed.

What they need is very good AI operators. That is my term, not a job title you will find in a survey: people who know how to use the tools, who know how to run workflows, and who can build a website on steroids in an afternoon. The nearest role the market has named is the forward-deployed engineer, the person who sits with a customer and makes the technology work in their setting; one analysis of job postings found those roles up 1,165% year on year in 2025.

The data points the same way, and I will give it to you with its limits. In Microsoft and LinkedIn's 2024 Work Trend Index, 66% of leaders said they would not hire someone without AI skills, and 71% said they would rather hire a less experienced candidate with AI skills than a more experienced candidate without them. In the same study, only 39% of people using AI at work had received training from their company. The skill is mostly self-taught, which means anyone can start. PwC's 2026 Global AI Jobs Barometer, built from more than a billion job adverts in 27 countries, put the wage premium for AI skills at 62%, up from 57%, and found jobs asking for AI skills growing about eight times as fast as the job market as a whole. Those are adverts, not hires. Gartner predicted that 40% of enterprise applications would carry task-specific agents by 2026, up from less than 5% in 2025, and two months earlier that over 40% of agentic AI projects would be cancelled by the end of 2027, for cost, unclear value or weak risk controls. Both are forecasts, and both can be true. Together they say where the bottleneck is: not the models, but people who can make agents do useful work, safely. That is the person a company wants to hire. It is also the person who no longer needs to be hired to build the first version of something.

When all things are equal

Think about how hiring actually works. However good you are, there is always a moment when someone has to make a decision. It is very unlikely that you are so good at something that you are the only choice. Usually, once the job spec is mapped, two or three people look roughly equal. The question in the hiring manager's head is a plain one: why should I hire you?

My bet is: because you work this way. If you know how to run these agentic workflows and map a problem out, you have a real edge, and it shows from the very first step. Two candidates match the job specification equally well. One sends a CV. The other sends a CV fitted to the role, a short analysis of the company's problem, and an infographic or a small working site they have not seen before. The interview starts from that material, on the candidate's strengths, instead of from the gaps in a CV. An edge is not a job. It helps when the choice is close, and the choice is nearly always close.

So it starts with the recruitment process itself. You send a CV customised for that role. You do an analysis of the company and its problem. You give them something that impresses them: a graph of their market, an infographic, a small site, something they have not seen before. That is exactly the work these tools make cheap.

I know this works because it worked for me, long before agents. I got jobs because of my OWASP work. I remember one interview where they already knew my OWASP project, so I spent half the interview talking about the tool they had been trying to use, and giving them insights on how to use it better. I got the job. Instead of them looking for gaps in my CV, or wondering where I might fit, we had a great conversation, and I was playing from a position of strength. Of course I was a good fit; but the conversation started from what I could do, not from what my CV did not say.

That is the same move, now available to anyone. If you can send a company material they have not seen, about their own problem, the interview starts from your strengths. I wrote in 2025, from the hiring side of the table, about using presentations instead of CVs. Agents make that presentation, and much more, something you can build for each application rather than once a year.

The move does not change when the person across the table is a customer rather than a hiring manager. A founder's first sale is the same conversation: two suppliers look roughly equal, and the one who arrives with an analysis of the customer's problem, and something they have not seen, starts from strength. Sell says more about that.

You have to do it to see it

None of this lands by reading about it. I have seen it with a group I have been working with: people who were not building websites a few weeks ago now build them easily, with the workflow I use for my own publishing, and one of them now has a much better understanding of how all the pieces fit together. I am proud of that. What changed their view was not an explanation; it was doing it. Perception changes when people experience it, and only then. That is my observation of one group, not a measurement.

So, three things, and the next two chapters take them further:

• Pick one workflow and do it end to end. A voice memo turned into a checked article, a site, a research pack. Publish, publish, publish: your own newsroom is one.
• Publish it. Work that can be linked is work that can be shown, which is what Act as the job you want is about.
• Use it in your next application. One analysis, one figure, one thing they have not seen. Or in your first sales call; the material is the same.

The 2018 chapter on getting a job ended with a line I still hold to: you have nothing to lose by giving it all you have got, and everything to gain. The difference in 2026 is that "all you have got" now includes an agent that can do in an afternoon what used to take you a week. Use it.