Every agent framework has a loop. Call the LLM, parse the tool calls, execute them, feed the results back. ReAct, AutoGPT, LangGraph, CrewAI — the shape is always the same. What differs is what happens when things go wrong, and more importantly, what can’t happen at all.

Symbiont v1.4.0 is here. This release adds four major capabilities to the agent runtime: persistent agent memory, cryptographic webhook verification, automated skill scanning, and metrics telemetry. Together, they close the gap between “agent that runs” and “agent you can trust in production.”

AI agents are increasingly acting on our behalf — reading email, writing code, managing infrastructure, negotiating with other agents. But there’s a fundamental gap in this ecosystem: when an agent claims to be “Scout v2 from Tarnover LLC,” how does anyone verify that claim?

Exploring the critical intersection of AI safety and security in an era of autonomous agents, from preventing unintended consequences to defending against malicious attacks.

Exploring ThirdKey's comprehensive catalog of AI attack vectors targeting autonomous agents, RAG pipelines, and vector databases - complete with proof-of-concept demonstrations.

At Third Key AI, we’re constantly looking at the horizon of security threats. The rapid integration of AI and Large Language Models into enterprise environments has created a landscape of new, subtle, and largely unexplored attack surfaces. One of the most fascinating and concerning of these is the potential for AI’s own infrastructure to be turned against itself.