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.
MODELSQuantization without tears: what you lose at 8, 4 and 3 bits
Smaller weights, faster inference, and a quality cost that depends far more on the task than on the bit count. A practical guide to choosing a level.
MODELSAI-assisted coding that survives code review: a practical workflow
Scope small, give real context, write the test first and review every diff like a stranger's. A workflow for shipping AI-written code with confidence.
MODELSContext windows are not memory
A bigger window lets a model read more at once. It does not make it remember, prioritise or forget well. How to design for that difference.
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.
MODELSHow to read a model card critically
Model cards are marketing and documentation at once. A checklist for separating the useful facts from the flattering ones.
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.