agentic-systems
3 articles
The AI Agent Initiative Problem — When Should an Agent Act on Its Own?
You spent months building a powerful AI agent. It just sits there waiting for you to say something. That's not a technical problem — it's a design philosophy problem. From KAIROS's Heartbeat Pattern to OpenClaw's background sessions, this is about when to let your agent decide to act on its own.
How Karpathy's Autoresearch Actually Works — Five Design Lessons for Agent Builders
Karpathy's Autoresearch isn't trying to be a general AI scientist. It's a ruthlessly simple experiment harness: the agent edits one file, runs for five minutes, checks one metric, keeps wins, discards losses. The lesson? The best autonomous systems aren't the freest — they're the most constrained.
Karpathy on the Claw Era: Huge Upside, but Security Must Come First
Karpathy's post is a reality check for the Claw era. He frames Claws as the next layer above LLM agents, but warns that exposed instances, RCE, supply-chain poisoning, and malicious skills can turn productivity systems into liabilities. His direction: small core, container-by-default, auditable skills.