Back to feed
Dev.to
Dev.to
6/30/2026
I Made My AI Rules Self-Verifiable — Here's How

I Made My AI Rules Self-Verifiable — Here's How

Short summary

AI configuration rules without verification mechanisms are just wishes. The author shares a practical system: embed success markers like [✓THINK] into rule text, then use mechanical grep scripts to track compliance rates across sessions. This converts vague aspirations into measurable constraints, improving execution rates and clarity of what "done" means for AI assistants.

  • •Embed verifiable markers into AI rules ([✓MARKER]) to make them measurable, not aspirational
  • •Use simple grep scripts to track rule compliance across sessions automatically
  • •Methodology applies to any process—code reviews, checklists, team workflows—lacking verifiable success criteria

Generated with AI, which can make mistakes.

#ai-tools#ai-agents#certification-education
Read full article at Dev.to

Is this a good recommendation for you?

Comments

Failed to load comments. Please try again.

Explore more

Controlled experiment shows mechanical enforcement dominates rule-format effects in AI agent compliance
Dev.to
I Built a Closed-Loop Self-Healing System for My AI Config — By Accident
Dev.to
I Built 3 Checks Into My AI's Slack Workflow. I've Used One of Them Zero Times.
Dev.to
Running a Team of AI Sub-Agents: What Breaks — and the Rules I Built Around It
Dev.to
I Made My AI Rules Self-Verifiable — Here's How — AiA Feed