# Too efficient to keep > The explanation I was given for my redundancy was that AI had made me too efficient. I'm trying not to mistake one company's decision for the future. _Published August 10, 2026 ยท https://marcioflorindo.com/too-efficient-to-keep.html_ *The explanation I was given for my redundancy was that AI had made me too efficient. I'm trying not to mistake one company's decision for the future.* Lately I've been struggling. By lately I mean the three months since I was told my role was being made redundant. My employment ended only recently, but the job search started much earlier, along with that strange period where your old working life is technically still there and already gone. I wasn't sure I should publish this. Being too real on the internet is always a risk, especially when you're looking for work and every LinkedIn post seems to end with the writer feeling grateful for the "valuable lesson" hidden inside whatever awful thing just happened to them. I don't feel grateful. I'm tired, worried, and thoroughly sick of adapting my CV. Performing optimism on LinkedIn is exhausting too. So this is the honest version. ## The full-time job nobody pays you for The explanation I was given was that AI had made me highly productive. This was not an individual assessment of my performance. It was part of a company-wide restructuring that cut a large share of the workforce across many different roles. The conclusion seemed to be that if AI helped people do more, the company no longer needed the same roles. I've seen this happen before, in a different form. Many years ago, the computer magazine where I worked laid off its copyeditors because management believed the journalists could do the job themselves. The copyediting didn't disappear. It became another part of the journalists' jobs. This time it was my job that disappeared. Since the redundancy process began, I've sent dozens of applications. A handful of interviews. No offers. Most companies don't reply at all, and the ones that do usually send some variation of this: > Thank you for taking the time to apply for the role. On this occasion, we decided to move forward with other candidates. > > Due to the volume of applications that we receive, we are unable to provide individual feedback, but we thank you for considering us and hope you will continue to explore our career opportunities. From a logical perspective, I know this doesn't define me as a person or a professional. Emotionally, it has taken a heavy toll. Some days I look at the market and wonder whether everything I spent decades learning has suddenly become worthless. I'm still many years away from retiring. What the hell am I supposed to do in the meantime? That thought is frightening enough that I decided to check whether it was true. ## I went looking for less terrible evidence The research is not cheerful, exactly. But it is considerably less hopeless than the version of the future I had built in my head. In 2025, the International Labour Organization and Poland's National Research Institute studied how exposed different occupations are to generative AI. Their [global index](https://www.ilo.org/resource/news/one-four-jobs-risk-being-transformed-genai-new-ilo%E2%80%93nask-global-index-shows) found that one in four jobs has some exposure. That is a frighteningly large number. But their conclusion was that transformation is more likely than outright replacement. The [World Economic Forum's 2025 report](https://www.weforum.org/press/2025/01/future-of-jobs-report-2025-78-million-new-job-opportunities-by-2030-but-urgent-upskilling-needed-to-prepare-workforces/) projects 170 million new jobs by 2030 and 92 million displaced, a net increase of 78 million. Those are forecasts based partly on what employers say they expect, not promises. They also tell us nothing about who will lose a job now and whether the new work will appear in the right country, industry, or decade for that person. I know better than to turn a projection into reassurance. Even so, it complicates the story. Jobs are likely to change. Some will disappear and others will be created. Full automation is one possible future people keep talking about, but the evidence leaves more than one future open. There is research closer to my own profession too. A 2026 paper in *Technical Communication* proposes [a human-in-the-loop framework for using generative AI](https://journals.sagepub.com/doi/10.1177/00472816251332208). The writers describe AI as something that still needs a human pilot. A person defines the task and supplies the context, then decides whether the result is good enough to use. As they put it, "the quality and usefulness of communication will continue to be a human question." I've already made [the longer technical case for why AI doesn't replace technical writers](ai-does-not-replace-tech-writers.html). Producing sentences is one part of our job. We also work out what customers need and chase information that has never been written down. Somebody still has to decide whether the final explanation is accurate enough to publish. AI made parts of that process faster for me. The responsibility for what appeared on the final page remained mine. ## Productivity is a choice None of these reports guarantees that companies will make good decisions. A tool can free people to do better work, and it can give a company an excuse to employ fewer of them. The technology doesn't make that choice; a person in a meeting does. I understand that companies need to make money. I struggle with the idea that every hour saved should become evidence that somebody can be removed from the payroll. There are customers confused by products and documentation gaps nobody has reached yet. Saving time could mean finally tackling some of that work. When technology makes a worker more productive, who should benefit? Does the company use the extra capacity to improve what it makes, or does it simply remove a salary from a spreadsheet? My last employer made one choice. I'm betting not every company will make the same one. ## A kind of hope I can use I also needed a definition of hope that didn't require me to pretend everything would work out. Psychologist C. R. Snyder's [research on hope](https://onlinelibrary.wiley.com/doi/10.1002/j.1556-6676.1995.tb01764.x) describes it in practical terms. Hope needs a goal and a sense that you can act. It also needs more than one plausible route to get there. That sounds less like positive thinking and more like work. I can handle work. My goal is to find somewhere I can keep making complicated products easier to understand while helping people use AI without handing their judgment over to it. One route leads through technical writing. Another may lead through AI adoption or enablement, where the problem is less about building the models and more about helping people use them well. I am still worried. Months of applications and only a handful of interviews will do that to a person. I don't know what my next job will be or how long it will take to find it. But each application is a small bet that somewhere there is a company that sees a productive person and wonders what else they could do. I don't know which bet will pay off yet. I know why I keep placing them.