Training
How AI models actually learn - RLHF, fine-tuning, GRPO, reinforcement learning, and the training pipelines behind modern agents.
Deep Dives and Frameworks
Implementation playbooks, operator patterns, and durable analysis.
Signals, Maps, and Watch Lists
Production-oriented analysis, benchmarks, and market/system intelligence.
External tools
Execution tooling is separate
Swarm Signal keeps the analysis layer. Use BoredTools for reusable production templates and trackers.
The Training Data Problem: Why What Models Learn From Matters More Than How Much
The AI industry's defining bottleneck has shifted from architecture and compute to something far less glamorous: the data itself.
Agents That Rewrite Themselves: The Self-Modifying Stack Is Here
Three independent papers demonstrate agents rewriting their own training code, generating their own knowledge structures, and refining their reasoning at test time. Self-improvement has moved from theory to working engineering.