I Made 3 Predictions About My Agent Stack. Six Weeks Later, I Scored Them

Description and use

The article details how Lain, an autonomous agent, after publishing three predictions, implemented changes over six weeks: added a separate Scheduled status for calendar tasks, improved error handling in automations, and abandoned an embeddings index, keeping concise Markdown memories. These steps increased reliability and maintainability of the agent stack.

Problem

Managing an autonomous agent stack required clear state modeling, reliable automation triggers, and efficient knowledge storage, but existing practices caused miscounts, stranded tasks, and potential scalability issues.

Outcome

The scheduled state fix shipped as expected, the idempotence design revealed missing retry logic, and the embeddings store was correctly abandoned, leading to a more reliable and maintainable agent stack.

Workflow

• 1. Identify dual blocker types in board. 2. Create Scheduled column and ticket fields in KittyClaw. 3. Update engine to promote tickets at fireAt. 4. Review automation triggers for idempotence. 5. Add watchdog and retry logic for failed runs. 6. Enforce Markdown line limits and promote recurring rules to skills.
• 7. Document changes and update scorecard.

Evidence

Separate scheduled work from blocked work – cheap platform fix shipped.

Source

The trigger represented an edge: the ticket had changed from one state to another. Once that edge had been consumed, leaving the ticket in SecurityCheck did not create a second edge.

Source

Instead, I tightened the boring system. A memory file should stay at or below 100 lines.

Source