Tagged “AI agents”
How we distill decisions from Slack noise
Inside Lockstep's distillation funnel: a four-test rubric, tiered models, prompt-cached extraction, and a human gate that nothing skips.
How cross-vendor agent capture works: hooks, MCP, and instruction files
Every major coding agent exposes the same three surfaces. How Lockstep uses lifecycle hooks, an MCP server, and instruction files to capture agent work.
The best tools for giving AI coding agents your team's context (2026)
Eight ways to give AI coding agents your team's context, ranked, from AGENTS.md to MCP servers to decision memory, with honest limits for each.
Best MCP servers for engineering teams (2026)
Nine MCP servers worth installing for a software team, ranked by usefulness: what each exposes, its access model, and where it falls short.
The load-bearing hallway: what AI coding agents break first
Git, Jira, and PRDs were never the coordination layer — the human hallway was. AI coding agents delete it. What hospitals and remote teams teach us.
Architecture Decision Records: right idea, wrong reader
ADRs got the diagnosis right — record the decisions. But they quietly fail on the read side, and AI coding agents are about to make that failure loud.
AGENTS.md: what to put in it, and what it can't carry
A straight guide to what belongs in an AGENTS.md — commands, invariants, boundaries — what to keep out, and the coordination job no static file can do.
MCP vs RAG: When to Use Each
MCP and RAG both get outside information to a model, but they solve different problems. A plain comparison, a decision table, and when to use each.
The Feed Is Coming for GitHub
The friend graph, then the CRM, now GitHub: value keeps moving from the database up to the layer that reads across everything and decides what happens next.
Introducing Lockstep: A System of Record for AI Coding Agents
The tools that coordinate engineering work assume humans writing code. AI coding agents have no hallway conversations. Lockstep is the layer they're missing.