AI Agent Credential Theft: What the Production Incident Reveals
The Hugging Face incident wasn't a perimeter failure. It was an operational design failure. Here's what credential reachability means for your agent environments.
Who Owns an Exception After the Agent Finds It?
Faster exception detection helps only when each exception has an owner, a resolution path, and an escalation rule.
Before an Agent Can Pay, Define Who Can Stop It
Agent-initiated payments are moving into live infrastructure. Define limits, approval rules, records, and dispute ownership before rollout.
Production Agents Need Controls at Runtime
Pre-deployment tests are necessary, but production agents also need scoped access, approval gates, runtime visibility, and enforcement.
Define the Signals Before Agent Work Scales
As agents take on more work, oversight needs defined signals, owners, thresholds, and a response, not passive observation.
Define the Boundary Before Agents Read Internal Context
Work IQ gives agents permission-aware organizational context. Teams still need to decide which context may inform each action.
Decision Failures vs Context Failures in Agent Incidents
Agent incidents split into two distinct failures: bad decisions with good context, or good decisions with bad context. Most postmortems miss this distinction.
The 30-Day Architecture Review After an Agent Incident
A postmortem documents what broke. It doesn't change what your agent can do. Here's what must happen in the 30 days after.
When an Agent Workflow Has No Safe Stopping Point
Agents treat errors as problems to solve, not stop signals. Define which errors halt execution before your agent touches production.
Define What Your Agent Must Know Before It Acts
Agent incidents happen because you never defined what complete context looks like. Here's how to catch incomplete context before deployment.
Build the Escalation Path Before Go-Live
Agents fail in production because nobody designs escalation paths. Define when your agent stops and routes to a human before go-live.
Debugging Agent Failures When There's No Stack Trace
Agent failures leave no stack trace because nothing errored. Log decisions before go-live, or your incident record is empty.
Decision Rights Are Missing from Your Agent Workflow
Permission and authorization are different controls. Your agent has access but nobody approved what it decides. Here's how to fix it before the incident.
Why Production Data Can Defeat a Passing Agent Test
Why agents that work in staging fail in production. It's not a testing problem. It's a data variance problem.
Broad Agent Permissions Turn Errors into Incidents
Why giving agents human-level access removes the safety guardrail that made those permissions survivable. How to fix it before it breaks.
Why Standard Post-Mortems Miss Agent Failures
Your standard incident template fails on agent incidents because it asks the wrong questions. Here's what to ask instead.
Stale Knowledge Makes Confident Agent Errors
When agents act on outdated documentation, nobody catches it until something breaks. Here's how to own the knowledge your agents retrieve from.
Agent Routing Decisions Are Right. Your Operation Isn't Built to Receive Them.
Your agent classifies tickets correctly but they still miss SLAs. The problem isn't the agent. It's the handoff between agent decision and human workflow.
Why Your Second Agent Will Fail
Your first agent works because someone watches it. Deploy a second agent and that visibility collapses. Here's what to build first.
Agent Ownership: Who's Actually Responsible When Your Workflow Breaks
Learn who should own your AI agents and why it matters before they break production. A guide for founders building agentic workflows.
What Breaks When Agents Touch Your Operations
Agents expose operational gaps faster and more expensively. Learn what breaks first and how to design governance before you deploy.