Deterministic Code

• Same input → same output
• Predictable, reproducible errors
• Unit tests, edge cases
• Code review, testing

AI Agents

• Same input → different output
• Novel, context-dependent errors
• Probabilistic sampling
• Observability, validation, fallbacks

Build reliability from the ground up

I. Automated Tracking
Persistent memory. No tribal knowledge.

II. Context Loading
Load only what you need. Stay under 40%.

III. Focused Agents
One agent, one job. Compose specialists.

IV. Continuous Validation
Check at every step. Catch errors early.

Scale and maintain in production

V. Measure Everything
If you can't measure it, you can't improve it.

VI. Resume Work
Save state. Pick up where you left off.

VII. Smart Routing
Send tasks to the right specialist.

VIII. Human Validation
Humans approve critical steps.

Continuous learning and adaptation

IX. Mine Patterns
Search history. Find what works.

X. Small Iterations
Improve continuously. Small tweaks compound.

XI. Fail-Safe Checks
Prevent repeating mistakes. Add guardrails.

XII. Package Patterns
Bundle what works. Reuse it.

Start with your pain point:

Go deeper:

• The 12 Failure Patterns — What can go wrong
• Case Studies — Enterprise validation
• Workflow Guide — The full picture