Engineer systems that
think, act, and ship.
Practical guides on building autonomous AI systems, scaling engineering teams, and technical leadership.
Latest Dispatches
Retrieval Pipeline Residency: The Embedding That Crossed the Border Your LLM Call Didn't
Your inference endpoint is pinned to Frankfurt. Your embedding API, vector control plane, rerank service, prompt cache, and trace store are not. A walkthrough of the six residency surfaces in a RAG request and the org gap where each one quietly crosses the border.
The 40-Point Gap Between Your Interviewers When the Candidate Says 'I'd Just Prompt It'
A forty-point disagreement on the same candidate is not a candidate problem — it's a rubric problem. How to calibrate an AI-engineer hiring loop your own team cannot yet agree on.
The A/B Test Powered by Token Counts Instead of Outcomes
When the experiment platform makes token counts easy and user outcomes hard, prompt A/B tests ship local maxima the team cannot distinguish from regressions.
The Agent Budget That Approved Cost-Per-Call and Never Measured Cost-Per-Resolved-Task
An agent that drives cost-per-call down 25% while cost-per-resolved-task drifts up 40% is the most common unit-economics failure in agentic deployments. Here is why the vendor SKU is not the unit of work, and how to put the right metric on the wall.
The Agent Plan That Branched on a Fact Your Context Pruner Already Dropped
When a context pruner evicts a tool result that a later plan step silently depends on, the agent keeps branching against evidence that no longer exists — and the trace looks like a hallucination.
The Agent Rollout Cadence Your Customer Success Team Could Not Absorb
When the AI team ships behavior changes weekly behind feature flags but customer success trains monthly, the gap shows up as customer trust quietly collapsing. The fix is a coordination contract, not more meetings.
The Agent Runbook Your Incident Commander Could Not Execute
Most agent runbooks read fine in daylight and run blocked at 02:17 because the author has access the on-call SRE does not. Federation, declared scopes, break-glass endpoints, and drills are the fix.
The AI Feature Your CTO Funded That Your Security Team Will Not Let You Ship
AI features that ship on time treat the security threat model as a shape constraint at the spec stage — not a checklist at the readiness gate. A guide for engineering leaders on moving security upstream.
The Annotation Queue Your Humans Quietly Stopped Reading
Annotator throughput is the silent ceiling on every LLM eval program, and the queue ordering is the sampler nobody designed. How to treat sampling-for-grading as a first-class engineering surface.
The Are-You-Sure Confirmation Step Your Users Learned to Click Through
Uniform confirmation prompts in AI agents create habituation: users click through high-stakes actions with the same reflex as low-stakes ones. A stakes-aware friction budget, artifact previews, and instrumented time-to-click rebuild the safety layer.
The Async Tool Call Your Agent Fired and Forgot
Function calling treats sync and async tools as the same shape. The agent fires a job, receives an ID, marks the step done — and the work never lands.
The Budget Cap That Fires After the Action Already Shipped
When the kill-switch fires correctly but the agent has already booked the flight, sent the email, and closed the ticket — why budget caps measured in tokens miss the damage measured in actions, and how to separate spend from irreversibility.
About Tian Pan
I'm Tian Pan, an engineer-founder focused on agentic engineering — building autonomous AI systems and scaling engineering teams. I write practical guides on system design, technical leadership, and shipping with AI agents. Previously an early engineer at Uber, Brex, and IoTeX.
