Directory //
The complete archive of our thoughts, essays, and deep dives.
Teams staff AI as if ML talent is the scarce ingredient. The Capability Triangle — product, engineering, domain — shows the missing vertex is usually domain.
The build-vs-buy AI question is wrong: you needn't own a layer to benefit. The Advantage Map decides build, buy, or neither — by edge and by what is core.
Most AI ROI is attribution theater. The Value Attribution Ladder shows why only the counterfactual rung honestly proves that the AI caused the result.
A 95%-reliable step chained ten times is ~60% reliable. The Reliability Tax explains why agent demos collapse in production and how to architect around it.
Most AI business cases model only build cost and fail within a year. The Three Cost Curves — build, run, switch — model and defend an AI investment to a CFO.
AI moves too fast for a committed roadmap. The Bet Portfolio — exploit, explore, insure — replaces a linear plan with bets you rebalance as the future arrives.
AI capability is commoditizing fast. The durable advantage is judgment: where to apply it, what to refuse, how to earn trust, what to fund. The AI-native stack.
A capable model with poor context is a confident liar. The Context Hierarchy shows why context engineering beats model selection for AI output quality.
In AI the eval suite is the product — the only thing telling you whether a change helped or hurt. The Evaluation Pyramid: unit, capability, behavior, outcome.
You cannot mandate AI adoption — it is trust earned in a fixed order. The Trust Ladder: exposure, understanding, verification, reliance, then advocacy.
Most AI gets stuck in perpetual piloting. The Production Gradient turns the leap to production into a path of stations with exit criteria, so pilots graduate.
Most enterprise AI pilots fail in the organization, not at the model. The Four Gates — Value, Data, Trust, Economics — decide which pilots reach production.
Most AI governance is a gate teams route around. The Guardrail Stack makes the safe path the easy path — policy, defaults, paved roads, tiered review, audit.
AI models are commoditizing. Durable advantage lives in data exhaust: interaction data, expert corrections, evaluation sets, workflow logic. The real AI moat.
A probabilistic system will be wrong in production. The Failure Ladder — prevent, detect, contain, recover, learn — designs the response, not just detection.
The highest-leverage AI skill is knowing what not to automate. The Automation Line maps stakes against the context a model can't see to choose what stays human.
