istvan_intrnd

Founder here.

I’m seeing teams run execution in Linear but lose decision rationale across meetings, Slack threads, and time.

When issues are revisited, context/understanding is gone.

How do you handle this today? I’m looking for a few PMs who want to act as early design partners or advisors for something I’m building in this space.

We’ve built and used our own custom agent framework for a while (before “agents” became a mainstream term), mainly because existing tools didn’t fit our needs around control, observability, and composability.

I’m curious what others are actually running in production today—custom frameworks, LangGraph, AutoGen, CrewAI, homegrown pipelines, etc. and how satisfied you are with them.

What’s working well? What breaks down at scale (debuggability, cost, determinism, tool orchestration, evals)?

To make agentic cache work, LLM providers force frameworks to add all tools into the cached prompt. This is the main reason why I cannot properly use cache in my own agentic framework, where the set of tools changes in function of objectives. It confuses most base models, and however many times they say it doesn't my observations contradict this. How about yours?