Cover
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What you are probably seeing
Your team spends hours updating slide decks and whiteboard diagrams to show the ideal process flow.
Despite the clear visuals, agents still fail in production and you cannot identify which specific data inputs or logic checks are causing the errors.
Why it happens
Workflow mapping focuses on spatial relationships and order rather than the actual data contracts and API dependencies required for execution.
Evaluation metrics are often abstract in diagrams, making it impossible to trace why a specific agent decision resulted in a low quality output during real operations.
What changed recently
2026-10-06 · Notion AI Project Management: Custom Agents and Productivity
UC Today and Forvis Mazars are addressing that gap by focusing on custom agents and process optimization:
• Rakuten France runs 80+ agents to check backlogs overnight
• Notion notes 1 million custom agents were built by May 13
Source: UC Today
Step by step
1. List every data dependency and API call required for your most critical process step to identify missing technical links.
2. Define a measurable success metric for each agent that is based on actual output quality rather than just task completion.
3. Create a simple log entry for every agent execution that records the input, output, and any errors for future review.
4. Schedule a weekly review of these logs to spot recurring failure patterns that visual maps would not show.
5. Update your workflow documentation to include these technical dependencies and evaluation metrics next to the visual diagram.
Ways to go further
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