AI is the hot topic, and it keeps getting hotter every week. As the capabilities of models grow quickly, so does the pressure to use AI in all kinds of ways and in all kinds of areas.
This pressure can overwhelm you. Using AI may make you feel like you are turning your brain off more and more. But it does not have to be that way.
Software engineers were the first group to feel this pressure. Coding agents have changed and are still changing how software is written. Not everyone likes this.
The r/opensource subreddit is banning anyone who posts about their project “if [it] uses AI, is made by AI, or is intended for AI”. One reason for this is that some open-source developers feel like their code was misappropriated for the training of AI models. Well-funded AI companies like OpenAI and Anthropic have reached unthinkable valuations and are making their investors rich, while open-source projects often struggle to find even rudimentary funding.
Other developers are critical of the quality of AI-generated code. I recently talked to a founder of a tech company that uses “traditional AI” (e.g., image recognition, decision trees, CNNs) and sells products to highly regulated customers. Their technical co-founder is using AI to tackle projects that were out of scope just weeks ago. But to the founders’ surprise and despair, their engineering team is slow to adjust to the new world. Engineers are worried about the quality of the features that AI produces. They worry about the overall quality of the code that they have spent a lot of time crafting by hand.
Models Have Become Too Good Not to Use
Since November 2025, the models have been good enough for more than tailored, very well-described tasks. They have become able to work towards simple goals without babysitting. In July 2026, they made another huge jump and are now capable of tackling broad goals.
Frontier models in October 2026 are able to analyse, understand, structure, plan, and implement a solution for 95% of the coding problems that a senior engineer sees day to day. What I considered a two- to three-week project for a smart and capable working student is now just another prompt. When you are on one of the subscriptions, it costs basically nothing to develop proofs of concept.
This has changed the daily workflow of software engineers. Instead of spending most of the day in IDEs, they now spend time in front of a chat interface describing what they want to achieve. More and more, they review outcomes instead of code.
The Limits of Prompting
When you first interact with coding agents, you start with a single session. Over time, you will hand off bigger and bigger work packages, and the agent will naturally take longer to work on them. So what do you do while you wait? Yes, you write another prompt for another project and start another agent session.
The bigger your prompts become, the longer your agents take, and the more time you have for more prompts. You will find yourself with more and more parallel sessions. Of course, you are on a subscription (Claude Code or Codex). If the usage bar for your weekly limit is not full at the end of the week, it feels like you wasted money.
So you write more prompts. And you need to follow up when they are done and are waiting for the next instruction. You will need to keep the current state of all these projects in your mind or in your notes.
Ultimately, you will discover that the limiting factor for your productivity is your ability to switch between different projects. You will also find that the more decisions you delegate to your agents, the less involved you are in these projects and the harder it will be for you to review the agents’ work.
Detaching Yourself from the Code
If you are a developer who has not meaningfully used coding agents, and you finally give them a real chance, I am certain that each day you will be more surprised by how intelligent and well-reasoned these models can be. They can even advise you on how to use them properly.
Step by step, your role as a software engineer changes. You no longer write code. You review it. And most of the code that you review works flawlessly, is reasonably well written (at least after a few iterations), and seems to fit well into your existing code.
So you start to review with less intensity. You start to trust that the agent does a good enough job. You detach yourself from the code.
Working with coding agents is not without problems. You may be tempted to turn your brain off. This is also part of the critique from earlier: engineers are worried that their work is being hollowed out. My answer to that is: Nothing stops you from using your brain! But agents do make it easier to disengage, so staying intellectually involved has to be a deliberate choice.
Wish Things into Existence
Coding agents are a great tool. They allow you to simply wish things into existence. Increasingly, the limit is your own creativity (and the amount of tokens you have).
You have an idea for a dev tool that would make your life easier? That’s a prompt. Is there a cryptic error in the logs? Give the agent access and let it check the logs against your other metrics. You have two equally good ideas and find it hard to decide which route to take? Let an agent explore both and compare them.
Agents do not have to make us dumber. There are still reasons to learn new things and to go deep into the details of programming basics (compilers, memory management, optimisations). Agents might even help you learn these things.
Personally, in my free time, I was able to complete multiple large projects that each would have taken weeks, if not months:
- I rewrote an existing, half-baked tool that I use to generate a schedule for volunteers at my parish. It allows volunteers to input when they are available and assigns them to open spots.
- At home, we have to collect condensate from the chimney for our boiler since we have no drain next to it. That water goes into a container that needs to be emptied every other week. I built a water level sensor to tell me when it is full. I used an ESP32 and a cheap sensor from Amazon and integrated it into Home Assistant.
- Most recently, I built my own personal assistant inspired by Hermes and OpenClaw to manage my life. I wanted it to run on my own hardware since it has access to my calendar and email. It can also read my smart home data and it has multi-user support. It needs to be polished since my wife uses it as well.
And these are only my personal projects. At work, I finally started projects that I had planned for a long time but never had time for.
Software Engineering Is Changing
I often hear engineers complain that they find it hard to trust code that was AI-generated, and that they have to spend a lot of time reviewing and understanding the code. When they are done, they might as well have written the code themselves.
Other engineers find the texts that agents write too long and spend a lot of time reading them.
I do not doubt that problems like these are real. I have experienced them myself. But there are solutions. If you find it hard to trust the agent’s code, use the agent to help you investigate. Ask it for evidence, such as screenshots, videos, or guided tests. Then judge the evidence yourself. If you are unhappy with the output, ask yourself if your agent really has all the access it needs. You can also tell the agent what annoys you and ask it to fix it. If it helps, tell it to generate an interactive HTML page that explains the code.
Personal workflows and software engineering as a profession are changing. Fighting about formatting style and comments, setting up language servers, and learning IDE shortcuts seem pointless now. The debate about the best IDE has become a debate about the best model or harness.
Evolution Means Adapting
In Germany, people often incorrectly translate the famous “survival of the fittest” as “Überleben des Stärkeren” (survival of the strongest). Fitness depends on the environment. When the environment changes, strengths that once gave an advantage may no longer be relevant. Our tools in software engineering are changing, and we should consider how we can adapt to this change.
If you feel coding agents and AI in general are bringing you down, I would advise you to take a step back and reset your relationship with AI. Using AI does not mean you have to support the large AI companies (there are lots of capable models). It does not mean that you have to stop thinking for yourself. You do not have to surrender your brain to AI slop. Writing great code still means you have to care about the product. And if you want to be creative, you now have more room for it than ever.
If you haven’t yet, now is the best time to start adapting.