Technical insights into multi-agent orchestration, local protocols, and
developer-centric terminal workflows.
Loop engineering's six building blocks are all context primitives wearing new names. The scheduling is cron. The part that decides whether the loop works is the context delivered on every iteration.
Stored session transcripts are an external memory most people throw away after 30 days. A skill that forks a cheap model to grep, expand, and re-rank them turns 'what did we decide about X' into ranked snippets — so the agent stops re-making old mistakes.
Decompose a reviewed spec into discrete tasks and drive it with a loop that spawns a fresh headless agent per task. Each unit of work gets a clean context window and a pass/fail gate instead of one agent compacting itself into confusion.
Write the exact verification step into the feature spec your agent loads, so 'done' means the test passed and the result is on the table — not that the code compiled.
Not all code is equally expensive to get wrong. Stop reviewing your agent's output uniformly and start spending your scrutiny where a mistake double-charges a customer.
Agent-driven file discovery burns turns and fills the window with wrong guesses. A parameterized priming command loads exactly the right files in one deterministic shot — reserve probabilistic search for when you genuinely don't know where to look.
Taking the human out of the loop is the real unlock — but headless plus loose permissions plus production access is how you wake up to a wiped repo. Automate only what's tested, sandboxed, and scoped.
A destructive-tool annotation plus a mid-call elicitation request gives you a deterministic human checkpoint that travels with the capability — so a confused or injected instruction can't quietly delete your data, no matter which client is driving.
A single giant root rules file dilutes the agent's attention. Split persistent context into a broad root plus directory-scoped files the agent loads by what it's touching — and push task-specific instructions into commands.
Most AGENTS.md files defend against imagined mistakes. Mine your own transcripts, count what the agent actually gets wrong, and let the failure distribution decide what to write — and in what order.