AI
AI Agent Error Handling: What Happens When the Model Fails?
Treat model failures as normal software states. Classify them, retry only when useful, and give the workflow a terminal failure state.
IndieFounder publication
Practical stories, product lessons, teardowns, and field notes for independent founders.
AI
Treat model failures as normal software states. Classify them, retry only when useful, and give the workflow a terminal failure state.
Archive
AI
Treat model failures as normal software states. Classify them, retry only when useful, and give the workflow a terminal failure state.
Security
Shared service accounts make attribution and permission management difficult.
AI
Agent logs should reconstruct what happened without becoming a dump of sensitive customer data.
AI
Build an eval suite that answers one question: does the agent complete the customer's task correctly and safely under realistic conditions?
Security
Long-running agents need access after short-lived access tokens expire, but permanent credentials create unnecessary risk.
Startups
Turn a repeated AI workflow into a product by wrapping it in onboarding, data connections, permissions, progress, billing, and measurable outcomes.
AI
Stop testing agents with a few happy paths. Use a repeatable evaluation set that covers task success, tool use, failures, safety, latency, and cost.
Growth & Marketing
Google started tagging some Gemini outbound links. Count the new parameter beside the referrer, then rewrite only the pages that actually receive the clicks.

Security
An agent may perform an action for a human, but the audit trail should preserve both identities.
Startups
Validate a niche with interviews, workflow observation, mockups, and manual delivery before spending weeks on infrastructure.