MODELSHow to evaluate a new AI model in two weeks: a practical review framework
Launch-day benchmarks tell you little about your workload. A day-by-day plan for testing a new model on real tasks and reaching a defensible decision.
MODELSChoosing a model is a budget decision, not a leaderboard decision
Latency, cost per task and the cost of failure matter more than the top line of any chart. A worksheet you can reuse for every model decision.
TESTSWhat do reasoning tokens actually cost you? How to measure and control them
Hidden thinking tokens are billed like output and vary wildly by task. A practical audit to find where reasoning pays off and where it is burning money.
AGENTSStep budgets and stopping rules for AI agents
Every agent needs to know when to stop. Budgets, loop detection, progress checks and graceful exits that keep agents useful and affordable.
MODELSSmall models, big jobs: where tiny models quietly win
Classification, extraction, routing and on-device work. The jobs where a small model matches a big one at a fraction of the cost, and how to prove it.
TESTSDoes "think step by step" help on short tasks?
Chain-of-thought helps a lot on maths and logic and very little on many everyday tasks. What the research says and how to check your own workload.
MODELSDistillation explained for builders
Train a small model to imitate a big one and keep most of the quality at a fraction of the cost. How it works, when it pays off and what to check first.
PAPERSTokenizers: the layer everyone ignores until it bites
Why models struggle to count letters, why some languages cost more, and why numbers behave strangely. The tokenizer explains more than you think.