THREAD 01
Agent Architectures
How autonomous systems plan, preserve state, recover from failure, and remain inspectable over long-running work.
Open question
Which architectural choices make an agent reliable without making it too rigid?
How we investigate
Architecture teardowns, failure analysis, trace inspection, and reproducible design notes.
3 min readThe Hidden Latency Cost of Stateful Multi-Agent Loops
How context growth and sequential model calls make multi-agent systems slower—and how to decide when extra roles are worth it.
Agent ArchitecturesRead
5 min readPrompt Injection Is Not a Filtering Problem
Published defences report low attack success rates on static benchmarks and fall over against adaptive attackers. What survives that is architecture.
AI securityRead
5 min readWhy AI Security Frameworks Fail in Practice
Frameworks describe controls for a system with a boundary. LLM applications dissolve that boundary, and the checklist stays green while the gap opens.
AI securityRead
5 min readMost Agent Failures Never Throw an Error
An agent that crashes is the cheap case. The expensive failures return a confident, well-formed, wrong answer, and nothing in the stack notices.
Autonomous AI AgentsRead
3 min readThe Legibility Problem in Autonomous Agents
An autonomous agent is governable only when operators can reconstruct its goals, evidence, decisions, actions, and uncertainty.
Agent ArchitecturesRead