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The architecture is what the product does when the model is wrong.

A model that is right most of the time is an architecture problem, not a prompt problem. These articles cover the surfaces that decide what the reader experiences on the other days: the contract on the output, the route to a second model, the trace that explains a bad answer, and the incident process for a system that is wrong fluently.

6 articlesProduct Architecture

Articles in Product Architecture

Incident Response for Systems That Can Be Wrong Fluently

A response playbook for quality regressions, prompt attacks, retrieval contamination, runaway agents, cost spikes, and provider failures.

Observability for LLM and Agent Systems

Tracing model calls, retrieval, tools, state transitions, quality signals, and cost without turning telemetry into a privacy liability.

Model Routing, Cascades, and Fallbacks

How to choose models per request using task risk, calibrated confidence, operational health, and total expected cost.

Structured Outputs Beyond Valid JSON

Designing schemas, constrained decoding, semantic validators, repairs, and safe evolution for dependable model integrations.

AI Product UX for Systems That Can Be Wrong

Designing intent, progress, evidence, editing, confirmation, and recovery so capability becomes trustworthy product behavior.

Production AI Architecture in Laravel and PHP

Queues, streaming, typed provider boundaries, retrieval, tool execution, and observability for durable AI features in Laravel.

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Put this against a real system.

If a decision in Product Architecture is in front of you right now, the fastest version of this is a call: bring the architecture, the failure you are seeing, and the constraint you cannot move.

Discuss the system