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You have to hold AI hand to do even simple vanilla JS correctly. Or do framework code which is well documented all over the net. I love AI and use it for programming a lot, but the limitations are real.
Exactly that is also my experience also with Claude Code. It can create a lot of stuff impressively but with LOTS of more code than necessary. It’s not really effective in the end. I have more than 35 years of coding experience and always dig into the newest stuff. Quality wise it’s still not more than junior dev stuff even with latest models, sorry. And I know how to talk to these machines.
By TuxSH 2026-03-1320:50 I don't have as many years of professional experience as you do, but IMO code pissing is one of the areas LLMs and "agentic tools" shine the least.
In both personal projects and $dayjob tasks, the highest time-saving AI tasks were:
- "review this feature branch" (containing hand-written commits)
- "trace how this repo and repo located at ~/foobar use {stuff} and how they interact with each other, make a Mermaid diagram"
- "reverse engineer the attached 50MiB+ unstripped ELF program, trace all calls to filesystem functions; make a table with filepath, caller function, overview of what caller does" (the table is then copy-pasted to Confluence)
- basic YAML CRUD
Also while Anthropic has more market share in B2B, their model seems optimized for frontend, design, and literary work rather than rigorous work; I find it to be the opposite with their main competitor.
Claude writes code rife with safety issues/vulns all the time, or at least more than other models.
By wek 2026-03-1320:41 This is not my experience either. If you put the work in upfront to plan the feature, write the test cases, and then loop until they pass... you can build a lot of high quality software quickly. The difference between a junior engineer using it and a great architect using it is significant. I think of it as an amplifier.
By seanmcdirmid 2026-03-1320:20 Not in my experience. But then again, lots of programmers are limited in how they use AI to write code. Those limitations are definitely real.
By jcranmer 2026-03-1321:01 I must say, I do love how this comment has provoked such varying responses.
My own observations about using AI to write code is that it changes my position from that of an author to a reviewer. And I find code review to be a much more exhausting task than writing code in the first place, especially when you have to work out how and why the AI-generated code is structured the way it is.
By moezd 2026-03-1320:43 AI assisted code can't even stick to the API documentation, especially if the data structures are not consistent and have evolved over time. You would see Claude literally pulling function after function from thin air, desperately trying to fulfill your complicated business logic and even when it's complete, it doesn't look neat at all. Yes, it will have test coverage, but one more feature request will probably break the back of the camel. And if you raise that PR to the rest of your team, good luck trying to summarise it all to your colleagues.
However if you just have an easy project, or a greenfield project, or don't care about who's going to maintain that stuff in 6 months, sure, go all in with AI.
By keeganpoppen 2026-03-1320:131 reply that's just not even remotely my experience. and i am ~20k hours into my programming career. ai makes most things so much faster that it is hard to justify ever doing large classes of things yourself (as much as this hurts my aesthetic sensibilities, it simply is what it is).
By GalaxyNova 2026-03-1320:22 Not what I've experienced
By comrade1234 2026-03-1320:50 Having an AI is like having a dedicated assistant or junior programmer that sometimes has senior-level insights. I use it to do tedious tasks where I don't care about the code - like today I used it to generate a static web page that let me experiment with the spring-ai chat bot code I was writing - basic. But yesterday it was able to track down the cause of a very obscure bug having to do with a pom.xml loading two versions of the same library - in my experience I've spent a full day on that type of bug and Claud was able to figure it out from the exception in just minutes.
But when I've used AI to generate new code for features I care about and will need to maintain it's never gotten it right. I can do it myself in less code and cleaner. It reminds me of code in the 2000s that you would get from your team in India - lots of unnecessary code copy-pasted from other projects/customers (I remember getting code for an Audi project that had method names related to McDonalds)
I think though that the day is coming where I can trust the code it produces and at that point I'll just by writing specs. It's not there yet though.
By lelanthran 2026-03-1320:012 reply This is a very one-sided article, unashamedly so.
Where's the references to the decline in quality and embarrassing outages for Amazon, Microsoft, etc?
Do we know that it decreased the quality, or introduced more opportunities for bugs by simply increasing the velocity? If every commit has a fixed probability of having a bug, you'll run into more bugs in a week by going faster.
By dboreham 2026-03-1320:30 Everything you read is in service of someone's business model.
