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Research-Driven Agents: When an agent reads before it codes
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Re: Research-Driven Agents: When an agent reads before it codes
#72[dead]
Re: Research-Driven Agents: When an agent reads before it codes
#73When I want to solve a new problem with an agent, I always ask it to search broadly for prior work in the given area online, and then analyze if we can build our solution using it as inspiration. I see it as the solution being out there in “idea space”, and by having the agent search beforehand we can more efficiently explore this space before converging on the final solution.
Is it not safe to assume that all* publicly available prior work is in the training data? Then you could just prompt it to propose options with pros and cons etc. * Bar extremely new stuff from after the cutoff
Included in the training corpus doesn’t mean perfect or even partial recall.
Re: Research-Driven Agents: When an agent reads before it codes
#74This seems analagous to why Vercel found an AGENTS.md better than "skills", when in reality the agents.md is just the already expanded skill.
This fits into the paradigm of finding ways to force better context engineering.
Re: Research-Driven Agents: When an agent reads before it codes
#75This is obvious, right? If you want to build a Facebook clone, you wouldn't tell the agent "build Facebook". You would provide it with a description of every page on Facebook, behaviors, interactions, UI, etc.
Agreed. This is nothing but RAG, which helps when the task benefits from more knowledge. They're just going into the details of their application.
Re: Research-Driven Agents: When an agent reads before it codes
#76[dead]
Re: Research-Driven Agents: When an agent reads before it codes
#77[dead]
Re: Research-Driven Agents: When an agent reads before it codes
#78I've been making skills from arxiv papers for a while. I have a one for multi-object tracking for example. It has a SKILL.md describing all important papers (over 30) on the subject and a folder with each paper's full content as reStructuredText. To feed Arxiv papers to LLMs I found that RST gives the best token count/fidelity ratio. Markdown lacks precision. LateX is too verbose. I have a script with the paper's url…
I am surprised you found RST better than markdown.
Re: Research-Driven Agents: When an agent reads before it codes
#79Earlier quoted context omitted.
I've been working on ctoth/research-papers-plugin, the pipeline to actually get LLMs to extract the notes. I really like your insight re RST over Markdown! It sounds like we're working on similar stuff and I'll absolutely reach out :)
Another format that's worth investigating is Asciidoc. It supports the richness of Docbook XML but has fewer quirks than rST in my eyes.
would it make sense to just go for pandoc instead?
Re: Research-Driven Agents: When an agent reads before it codes
#80this one is interesting cause i have been struggling with deep research.