Ryan Gillespie

Ryan Gillespie

Taking on AI's hardest state problem

About

AI swarms point autonomous agents at fragile DBs like Redis. In production, this causes silent state forks and lets one poisoned agent corrupt the whole swarm. You can't patch bad physics with middleware; you need math. Based on my ACFA research, I built Memora Swarm. Standard aggregation breaks without a central coordinator due to float math. I replaced it with a zero-trust, coordinator-free engine using Q16.16 fixed-point integers, Ed25519 signatures, and a local Rust binary. My philosophy: "Agreement never promotes to authority." If 100 agents agree on a lie, it's still a lie. Memora-Swarm detects untrustworthy state and triggers human escalation before bad actions happen. I'm not building another AI platform. I'm building the TLS for agent memory. The infrastructure swarms occupy.

Badges

Tastemaker
Tastemaker
Gone streaking
Gone streaking

Maker History

  • Memora-Swarm
    Memora-SwarmThe TLS for autonomous agent state.
    Jul 2026
  • 🎉
    Joined Product HuntJuly 19th, 2026

Forums

Memora-Swarm - The TLS for autonomous agent state.

The AI giants run agent swarms on last-write-wins databases like Redis. Result? Silent state forks and swarm-wide memory poisoning (OWASP ASI06). You can't patch this with middleware. Memora replaces fragile DBs with a 3-layer mathematical engine: L1 CRDTs guarantee fork-free convergence. L3 ACFA uses Q16.16 fixed-point math to auto-ban equivocators without a central coordinator. L2 Epistemic logic detects when agents agree on a lie and forces human escalation.
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