zlacker

>>tablet+(OP)
I tried the agent thing on:

- Large C codebase (new feature and bugfix)

- Small rust codebase (new feature)

- Brand new greenfield frontend for an in-spec and documented openAPI API

- Small fixes to an existing frontend

It failed _dramatically_ in all cases. Maybe I'm using this thing wrong but it is devin-level fail. Gets diffs wrong. Passes phantom arguments to tools. Screws up basic features. Pulls in hundreds of line changes on unrelated files to refactor. Refactors again and again, over itself, partially, so that the uncompleted boneyard of an old refactor sits in the codebase like a skeleton (those tokens are also sent up to the model).

It genuinely makes an insane, horrible, spaghetti MESS of the codebase. Any codebase. I expected it to be good at svelte and solidJS since those are popular javascript frameworks with lots of training data. Nope, it's bad. This was a few days ago, Claude 4. Seriously, seriously people what am I missing here with this agents thing. They are such gluttonous eaters of tokens that I'm beginning to think these agent posts are paid advertising.

>>mlsu+ur
I don't think it's fair to call that the agent thing. I've had profoundly positive results with agentic workflows for classification, analysis, and various business automations, including direct product pricing. You have to build an environment for the agent to make decisions in, with good instructions for what you want them to do. Then you wire it up so that the decisions have effects in the real world. You can acheieve really good results, and there is a lot of flexibility to tweak it and various tricks to optimize performance. Tools can allow agents to pull in relevant context as needed, or to execute complex multistep workflows. That is the agent thing.

Writing code is one thing that models can do when wired properly, and you can get a powerful productivity boost, but wielding the tools well is a skill of it's own, and results will vary by task, with each model having unique strengths. The most important skill is understanding the limitations.

Based on your task descriptions and the implied expectation, I'm unsurprised that you are frustrated with the results. For good results with anything requiring architecture decisions have a discussion with the model about architecture design, before diving in. Come up with a step by step plan and work through it together. Models are not like people, they know everything and nothing.