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How We Vet an AI Product Before Launch
The practical product, security, reliability and operational checks AlanOps uses to decide whether an AI product is ready for customers.
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Field notes
Practical notes on AI products, CTO decisions, and the platforms that keep them reliable.
Latest field note
The practical product, security, reliability and operational checks AlanOps uses to decide whether an AI product is ready for customers.
Read the articleA practical framework for deciding which parts of an AI product should be custom, bought from a vendor or assembled around proven services.
Compare managed hosting with an engineering handover, including ownership, support, security, costs and the exit plan you should demand.
The honest cost of an AI product depends less on screen count than on uncertainty, integrations, data, risk and the standard required at launch.
A compelling AI demo proves a possibility. Production software must also be secure, observable, affordable and dependable when reality arrives.
A PRD is a strong starting point, but a responsible software quote must resolve the assumptions that control scope, risk and delivery.
Use these 15 questions to expose the product, technical and delivery assumptions that must be resolved before development starts.
AI has made code faster to produce, but dependable software still requires product judgement, verification and operational ownership.
AMPD and CarBuddy AI sit at different points in the customer journey, but they keep teaching the same lesson: the hard part is not…
Sometimes the universe decides that one production incident isn’t enough. It needs to stack them like Russian dolls, each one revealing another surprise when…
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