alt Hacker NewsUsing a CLI coding agent in your IDE's terminal is a terrible way to view conversation history and works poorly for organizing multiple conversations.
It only fits a hands-on, merely AI-assisted development approach, on one feature at a time, that is not typically productive compared to agentic development.
You might disagree, but you'll find that the proponents of the hands-on approach are losing ground every month as AI gets better at working autonomously.
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I'm expecting IDEs to adapt to new workflows, albeit very slowly.
There is potential to build a better UI than what's constrained within a CLI's grid of characters.
I'll admit I'm currently not up to speed on having multiple features worked at the same time, with git worktrees etc.
Except surrendering cognitive control over the system being built makes things worse.
Claude constantly makes poor architectural decisions, adds unnecessary and costly checks, makes wrong assumptions, etc.
Doesn't take the value out of LLMs writing code, but they need to be properly steered and reasoned with. How will you do so if you don't even browse the code it generates.
I always suspect that the people all in fully agentic codig like this are mostly creating prototypes, half-assed copies of existing products, etc.
I am glad to not work in such an environment.
Agentic development is basically a scam IMO. I’ve written about this before, but collaborative coding with AI is a huge productivity boost and you can still own all the quality. Ultimately with agentic development there’s too much you can’t, and won’t, review. The quality slips out of your hands.
I still read all the code AI produces, and I have a specific workflow. I scaffold the API first using AI, then review it for quality. Then I write tests, and review them for quality. Implementation is last, and technically I need not review the code but I choose to.
When I’ve done agentic development, the only thing I’ve accomplished is 100x more token burn with lower-quality code. It’s also not faster, because the tokens cost time and so many mistakes are made that must be cleaned up. The agents burn so much time going around in circles, when I could’ve just steered the model to write a good implementation.
Keep in mind, this is very fast. Models still produce thousands of lines of code in mere minutes. And with tests backing them up and an API frozen, the model goes much faster as it can iterate and has a framework for what it’s doing.