AGENTS.md and CLAUDE.md have become standard practice in AI-assisted development — the go-to mechanism for telling a coding agent what it needs to know about your project. A controlled study across real repository benchmarks now complicates that assumption. Developer-written context files produced a modest performance improvement. LLM-generated context files

A supply-chain team deployed two AI agents simultaneously — one optimizing procurement speed, one minimizing daily capital spend. When demand spiked, the agents entered complete gridlock: the procurement agent generated purchase orders; the finance agent canceled them immediately. The cycle repeated thousands of times, burning compute tokens while delivering zero operational

Long-horizon agents — those capable of working through multi-step tasks over extended sessions — are no longer a research prototype. They are operational in real engineering environments today. But operational does not mean autonomous. The meaningful breakthrough of early 2026 is not that agents can now be left unsupervised; it is that