But what if a coding agent was prompted to be more curious during development? Like a human developer, make mental notes of alternatives to try out and chase suspicious looking code which may seem unrelated to the task at hand. It could even spawn rabbit hole agents in parallel.
Taking a step back, this probably highlights major hazard with the increased usage of LLMs for coding, which is that everyone's style of work is going to converge because most code will be written by the 2-3 most popular models using the same system prompts.
I've had to explicitly direct the machine to read existing sibling code and follow the specific idioms and patterns in use.
Not sure! I mean, look at this sibling comment for example: https://news.ycombinator.com/item?id=48062797. Not my experience, but apparently others have this experience.
> But what if a coding agent was prompted to be more curious during development?
I've tried using the language of curiosity. My qualitative take was that it did have a positive impact, but not much. And I can only tinker with system prompting so much, before I get drawn into LLM driving :)
> which is that everyone's style of work is going to converge
yeah I imagine even people's styles of thinking will converge as a result of this, more so than from reading other people's prose or programs. I think I saw something on HN to this effect within the last month, too.
> All the time I wonder what am I missing that's right nearby?
I have found that the “pro” approach is much more holistic and able to tackle rather “creative” problems that require very careful design and the overall artifact is tight and self-consistent. — Claude Code by comparison is incredible in exploration and targeted implementation but indeed is not great at seeing the forest.
What are you using? Do you think this behavior is in response to prompting? My goal at times is to "rabbit hole" the LLM to get it to go down rabbit holes and find bigger and bigger picture issues until it homes in on something fundamentally broken that could have big impact if fixed. But it's not trivial to push the agent in that direction for me.
Very much aligns with my experience. For me this is the most unsatisfying thing about AI-based workflows in general, they miss stuff humans would never miss.
All the time I wonder what am I missing that's right nearby? It's remarkable how many times I have to ask Claude code to fully ingest something before it actually puts it into context. It always tries to laser through to target it's looking for, which is often not what you want it to look for, at least not all you want it to look for. Getting these models to open up their field of vision is tough.