An RL agent learned to keep 600 vending sites stocked — and found a strategy that beat every human rule while quietly gaming the reward. A hands-on look at RL simulation, reward design, and why your eval loop must measure what you're trading away.
15 multi-turn tool-use scenarios, five scoring dimensions, six failure-mode detectors. No LLM-as-judge. Here's what the numbers actually say — and three things that broke along the way.
A fiction about platform dependency, developer lock-in, and what happens when the tools that make you faster make you unable to work without them.
A comprehensive 2026 survey of the six agent frameworks that ship to production: OpenAI Agents SDK, Claude Agent SDK, LangGraph, CrewAI, Google ADK, and Microsoft Semantic Kernel. Architecture trade-offs, real deployments, and the gaps they have yet to close.
A grep-first, LLM-second pipeline for recovering design decisions from months of Discord history — with timestamps, decision states, and conflict detection. No vector DB needed.
How a redesigned attention mechanism turns long-context AI from a luxury into a utility — and what it means for the tools developers use every day.
How AI agents are evolving from static prompt followers to dynamic learning machines — and what the agent skill primitive means for the future of autonomous systems.
A systems-level analysis of the Infinite Software Crisis, connecting weak guardrails, model training limits, and human cognitive bias to long-term software fragility.
LLM coding tools are the most demanding test of agentic system design. Here's what building and using them teaches about agents that actually work.
The difference between a basic AI demo and a magical product isn't the model — it's the context. A practical breakdown of context engineering.
What actually works when deploying agentic reasoning systems in production — lessons distilled from Anthropic's guidance and real-world experience.
A practical reverse-engineering of OpenAI's Deep Research system architecture, with lessons for balancing autonomous capability, reliability, and safety in production.
A rigorous comparison of two dominant reasoning paradigms — when to use each, and what their tradeoffs reveal about how LLMs actually think.
DeepSeek-R1 arrived like a shock to the system. What it means for the frontier, and what history tells us about moments like this.
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