On the 19th February 2026, around 1 year after the release of Claude code, it’s creator — Boris Cherny — stated that “Coding is largely solved”. Every line of his codebase is done by Claude code and he hasn’t edited a line of code by hand since November 2025. Everyday he ships 10–20 PRs.
“2026 is the year of Multi-agent orchestration!” is cried from the rooftops of Twitter. Experienced developers are already claiming that using a single Agent is archaic and rudimentary. If you still work this way you are nothing more than a luddite.
I admit, I use Claude code everyday. I’ve seen and experienced it getting better and better. It can do things now that still blow me away. I wrote a Go program last night to record my voice. Completely pointless, but still very impressive.
If AI is so good and “Coding is largely solved” why then do I still have a job? What is my company paying me for? And why do I feel busier than ever?
Non Coding Related Tasks
I organise. I am like a busy little beaver constantly preparing his dam. This can be tasks ranging from architectural documentation, determining priorities all the way to organising tasks for other developers.
I communicate. I have to communicate with the right people in the right tone about the right priority. If a certain user raises a bug I need to understand what the bug is about, is it high or low priority, who can fix it and when.
I decide. In software decisions have to be made and tradeoffs are inevitable.
- What approach to take when refactoring an inefficient piece of code.
- What should and shouldn’t be in scope for this new feature.
- What tools we should use for this new implementation.
- What data model makes sense in this specific scenario with all these constraints.
A constant stream of decisions. Your success or failure are determined by their sum.
AI helps in small ways with these activities: It helps me draft an email, gives advice on a research tasks and assists with writing documentation. However, it hasn’t fundamentally changed my approach. This whole side of work is messy and unpredictable. It’s interacting with other humans and reacting to constant change. It still needs a human in the loop.
Coding Related Tasks
I implement code changes. These can be features, improvements or bug fixes. This is the area where AI is making the biggest difference.
AI is not only writing the code but now it’s even reviewing it. It’s a strange new reality we have entered. Each instance of Claude brings a different opinion and finds different potential issues depending on their contexts.
There is no denying this side of the job has been hugely impacted. This is where real developers are feeling it the most. We have been unmoored from our traditional ways and we’re struggling to even see the land anymore.
Claude code can’t be trusted 100%
Claude code can’t be trusted 100%. It hallucinates, it deviates and it occasionally makes things up. It’s context is too often wrong — either too small or too large. There are many opinions online about ways around it but in my experience whatever you try there are always problems.
The inconsistency is a huge problem for AI companies. It prevents developers letting loose a coding agent on a board of tasks. It would very likely fix a third of the issues correctly, not completely fix the next third and the last third would be totally wrong.
This is one the main arguments against full automation. How can you trust your company’s software to something that consistently give you inconsistency?
The Power Of The Group
Humans real strength comes in group settings. I experience this almost everyday and I think it’s the big advantage humans have over AI. Whenever a new feature is planned, if it’s first discussed in a group, then invariably the outcome will be better.
A group enables more ideas to be put forth and more chance a bad idea will be caught early. This isn’t always the case and it depends on the group dynamic, but in my experience it usually leads to a more reliable and thorough outcome.
If you get rid of the people, you lose a massive business advantage and suddenly your whole business relies on one perspective dictated by one company. Diversity is the key to success, just ask mother nature.
Expectations
The whole world and his dog is aware of AI and the supposed productivity gains. Targets, goals and expectations never stay the same in a company and with all the AI hype going around, expectations have ballooned at work.
Building Software is not a finite task, the goalposts move as the project progresses. A piece of software can always be improved whether that’s a new feature or a refactor. With AI, the goalposts are now moving further and more often.
Conclusion
We’re living in a hyped up reality at the moment. You know that when a shoe company pivots to become an “AI compute infrastructure” company that the equilibrium is out of whack.
It’s really easy to believe this hype and think all Software Developer roles will be gone in 6 months, that LLMs will be writing all software and there will be a mass influx of carpenters onto the job market.
However, this just isn’t the case.
The reason I still have a job is many fold. AI models can’t be trusted 100%, they hallucinate, their context is too often wrong and they always miss off details. On top of that, pricing is starting to increase as the underlying business model of generative AI is not sustainable.
The skill set of a software developer is more than just writing code syntax. It’s about understanding business needs and transforming that into solutions that enable the company to perform, scale and grow. Code is just a part of that transformation.
