TESTSHow to test whether an AI model really reasons: the contradiction-trap eval
A planted contradiction, blind judges and zero partial credit. A step-by-step method for finding out whether a model tracks state or just sounds like it does.
PROMPTSAnatomy of a production system prompt
Role, context, rules, tools, format, fallbacks and examples. A section-by-section guide to writing system prompts that behave predictably at scale.
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.
BENCHMARKSBuild an LLM eval set in an afternoon
Fifty real examples, a clear rubric and a script beat any public benchmark for your product. A four-hour plan to build your first eval set.
AGENTSDo you need an AI agent, or just a workflow?
Agents decide their own steps; workflows follow yours. A decision guide for choosing the simplest architecture that solves the problem.
BENCHMARKSBenchmark contamination: how to check whether a model has seen the test
Canary strings, n-gram overlap, perturbed questions and fresh held-out sets. How to tell real capability from a memorised test.
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.
AGENTSAI agent failure modes: a field guide and postmortem template
Wrong arguments, irreversible actions, runaway loops and confident false success. How agents fail, how to investigate it, and which guardrail stops each failure.
PAPERSLoRA in plain English
Fine-tune a large model by training less than one percent of it. How low-rank adapters work, what QLoRA adds and when to use them.