Very informative wiki, thank you, I will definitely use it. So Ive made my own "AI Agents framework" [0] based on actor model, state machines and aspect oriented programming (released just yesterday, no HN post yet) and I really like points 5 and 7:

    5: Unify execution state and business state
    8. Own your control flow

That is exactly what SecAI does, as it's a graph control flow library at it's core (multigraph instead of DAG) and LLM calls are embedded into graph's nodes. The flow is reinforced with negotiation, cancellation and stateful relations, which make it more "organic". Another thing often missed by other frameworks are dedicated devtools (dbg, repl, svg) - programming for failure, inspecting every step in detail, automatic data exporters (metrics, traces, logs, sql), and dead-simple integrations (bash). I've released the first tech demo [1] which showcases all the devtools using a reference implementation of deepresearch (ported from AtomicAgents). You may especially like the Send/Stop button, which is nothings else then "Factor 6. Launch/Pause/Resume with simple APIs". Oh and it's network transparent, so it can scale.

Feel free to reach out.

[0] https://github.com/pancsta/secai

[1] https://youtu.be/0VJzO1S-gV0