Methodology
+Methods for measuring and verifying recurring AI workflows.
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What Is Token Optimisation? A Measurement-First Definition
A practical definition: improve recurring AI workflow efficiency while preserving the agreed result, quality checks and verification. Read the article →
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Context Budgets Are an Allocation, Not a Target to Fill
A method for allocating relevant instructions, evidence and output reserve without filling a model context window by default. Read the article →
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Subscription vs API: Compare Cost per Verified Job, Not a Token Price Guess
A method for comparing subscription and API costs using the same verified-job window without inventing subscription token rates. Read the article →
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Surviving AI Usage Limits: Keep Recovery Outside the Model Turn
Persist job state outside a constrained model request and test resource-wait invariants without mistaking simulation for production evidence. Read the article →