Don't want to jeopardize this awesome chat about tools but for AI workshops I think these visual cards I came across could be an amazing way to handout. They cover all LLM concepts and explained visually. Found very useful to revise LLM concepts before AI research scientist/AI engineer interviews.
Author here. I went through ICLR 2026 accepted papers looking for work relevant to multi-agent production problems. Found 14 papers clustered around 5 issues: latency (sequential API calls), token costs, error cascades, brittle topologies, and observability.
A few highlights:
- Speculative Actions: parallel API execution, ~30% speedup
- KVComm: share KV pairs instead of text, 30% of layers gets near-full performance
- DoVer: intervention-driven debugging that flips 28% of failures to successes
Happy to discuss any of the papers or the framing. The decision matrix at the end maps each problem to a starting paper.
Last year, we evaluated different agentic LLM frameworks before selecting to architect our production system. Too many options out there.
So I built a covering their capabilities. If you're evaluating agentic solutions for your next project, hope this saves you time. It maps what's native, what needs integration, and what's not supported.
Let me know if anything needs correction or want to add any other framework.