Lance Martin of LangChain applies The Bitter Lesson to building AI agents and workflows.
Assertion Contradicted
Martin: OpenDeep Research is the top-ranked open-source Deep Research agent
“OpenDeep Research is a deep research agent that I've been working on for about a year, and it's now, according to Deep Research Spence, the best performing Deep Research agent at least on that particular benchmark. So it's pretty good. Listen, it's not as good…”
Insight
Martin: Multi-agent systems excel at parallel read-only tasks, not writing tasks
“I like the take that apply multi-agents to problems that are easily parallelizable, that are read-only, for example, context gathering for deep research, and do, like, the final quote-unquote write, in this case report writing, at the end. I think this is tric…”
Insight
Martin: Tool-based search with llms.txt beats maintaining vector indexes
“You give an LLM access to simple files, file tools. In this case, I actually use an LLM.txt to help it out. So it can actually know what's in each file. It's extremely effective and much more simple and easy to maintain, easier to maintain than building an ind…”
Insight
Martin: Selective History Pruning Adds Unnecessary Complexity to Agent Scaffolding
“So I'm not sure I love the idea of kind of selectively trying to prune your message history when you're building an agent. It can add more logic than you need to manage within your kind of agent scaffolding or harness.”
Insight
Martin: Context caching solves cost and latency, but not context rot
“I do think an important and subtle point here is that caching doesn't solve the long context problem. So it, of course, solves the problem of, like, latency and cost, but if you still have a 100,000 tokens in context whether it's cached or not, the LM is utili…”
Insight
Lance Martin: Black-box agent abstractions break when underlying models evolve
“Agent abstractions are problematic because you don't know what's necessarily under the hood of the abstraction. You don't understand it. And if I was building, for example, you know, OpenDeep research with an abstraction, I wouldn't necessarily know how to rip…”