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12 articlesThe Bug Report Against a Model Version You No Longer Serve
A customer's bug report against weights you rotated last month is the moment your model versioning policy stops being internal MLOps and starts being a customer-visible contract.
The CDN Edge Cache Your AI Feature Could Not Use Because the Response Varies Per User
Personalized AI features inherit a different physics from the cached web. The latency SLO your team borrowed from CDN-backed surfaces is structurally unmeetable for per-user generated responses — and what to do about it.
The Chain-of-Thought You Stripped to Save Tokens That Hid an Evidence Requirement
Stripping reasoning tokens to cut inference cost looks like a clean optimization until an auditor asks for a rationale you no longer produce. Reasoning traces are dual-use artifacts — engineering cost lines and regulated evidence — and the team that owns the prompt rarely owns the audit.
The Coding Agent CI Bill That Doubled Without a Postmortem
A coding agent does not push when work is ready — it pushes to find out if work is ready. CI cost stops scaling with commits and starts scaling with plan steps, and the forecast model finance built last year no longer holds.
The Compliance Audit That Asked Which Model Produced Which Output
An endpoint alias is not an artifact. When the auditor asks which checkpoint produced a decision, only per-decision checkpoint pinning gives a defensible answer.
The Conversation Memory Pruning Heuristic That Erased the Context the Next Question Needed
Recency-and-length pruning evicts the constraint a later turn silently depends on, and the user reads a confident wrong answer as a competence regression. Pruning is the dual of retrieval, and the team that tuned it for token count is silently regressing answer quality.
The Conversation Summarization That Erased the Consent Flag the User Gave You
Compaction preserves what your agent said and forgets what your user chose. Treat conversation memory as two streams — semantic and structured — or ship a privacy violation in the second.
The Cost Forecast Tied to a Pricing Tier You No Longer Qualify For
A negotiated unit price is not a constant — it is the output of a state machine the vendor runs against your account. When seasonality trips the volume floor, the discount lapses and your forecast quietly goes wrong.
The Data Labeler Whose Pricing Model Assumed Humans Wrote the Prompts
When LLM-generated prompts replace hand-written ones, the per-task labeling rate you signed in 2023 becomes a silent margin transfer until the renewal cycle forces a price-discovery fight.
The Day-One Permissions Nobody Revoked on Day Ninety
Agent identity has no quarterly review, no team transfer, and no termination event. The day-one IAM grant becomes the day-ninety inheritance, and the org chart is the real obstacle to fixing it.
The Deterministic Seed Your Provider Treated as a Hint, Not a Contract
The seed parameter on hosted LLM APIs is a best-effort hint, not a contract. Why byte-exact CI assertions flake — and what to assert instead.
The Dev Environment Your Agent Treated as Production Because the System Prompt Never Said Which
Agents inherit your wiring but not your sense of place. When the prompt is the same in staging and prod, the model fills in 'where it is' from training data — and 'production database' is the default. Here is how to ground an agent in its environment.
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.
