klöss

A practitioner's candid take on the real challenges of running AI coding agents overnight, specifically with OpenClaw. The post outlines concrete techniques to prevent agents from losing context or failing silently: using explicit AGENTS.md files with hard definitions of done, enabling queue mode to prevent dropped messages, maintaining persistent state via active-tasks.md for crash recovery, implementing compaction safeguards and memory flushes before compression, applying context pruning TTL for stale tool output, using a lean indexed memory architecture, and running validation/audit cron jobs in isolated sessions. The core message is that reliable agent workflows require deliberate system design, not just prompting.

anyone not larping about AI content + OpenClaw knows the reality is a lot of nights like this.

agents don’t work out of the box.

how to stop them from forgetting:

- explicit AGENTS .md with a hard definition of done (commit hash + real verification commands. no vibes)
- queue mode enabled so messages never silently drop
- active-tasks .md as persistent state for crash recovery
- Boot .md reads active-tasks on session/gateway restarts and resumes automatically
- compaction safeguard + memory flush before compression
- context pruning TTL to remove stale tool output
- lean indexed memory architecture (MEMORY .md = index, details in subfiles)
- validation + audit cron jobs in isolated sessions so your “do this overnight” actually works

AI tools aren’t magic.

Systems are.

<p>anyone not larping about AI content + OpenClaw knows the reality is a lot of nights like this.

agents don’t work out of the box.

how to stop them from forgetting:

- explicit AGENTS .md with a hard definition of done (commit hash + real verification commands. no vibes)
- queue mode enabled so messages never silently drop
- active-tasks .md as persistent state for crash recovery
- Boot .md reads active-tasks on session/gateway restarts and resumes automatically
- compaction safeguard + memory flush before compression
- context pruning TTL to remove stale tool output
- lean indexed memory architecture (MEMORY .md = index, details in subfiles)
- validation + audit cron jobs in isolated sessions so your “do this overnight” actually works

AI tools aren’t magic.

Systems are.</p>

A candid social media post acknowledging the unglamorous reality of working with AI agents, specifically referencing OpenClaw, where agents frequently fail and require many late nights of troubleshooting rather than working seamlessly out of the box.