Writing
Essays on what AI exposes — in how expertise works, how documentation fails, and how organizations make decisions under new conditions.
When the Recommendation Was Valid
AI systems can identify opportunities and measure outcomes. What they cannot do is evaluate competing constraints and determine which implementation path makes the most sense within the broader system. Identifying opportunities is not the same as deciding which ones are worth taking.
AI Changes the Failure Modes of Documentation
When documentation starts feeding retrieval systems, AI-assisted tooling, and downstream automation, the failure modes change entirely. Machine retrieval systems don't fail the way human readers do — they preserve the appearance of correctness while silently losing the contextual boundaries that made the information trustworthy. Documentation quality is no longer just a communication concern. It's a systems reliability concern.
Technical Writing Was Never Just About Writing
AI is changing not only how humans produce communication, but how they interpret it. The traits associated with rigor and expertise — structured reasoning, coherent organization, reduction of ambiguity — are now read as evidence of automation. The real expertise was never the writing itself. It was the judgment underneath it.
AI, Expertise, and the Appearance of Ability
AI is becoming very good at producing outputs that feel correct — creating a larger and more elusive problem than hallucinations ever did. As the cost of generation drops, the scarce skill becomes judgment: recognizing where assumptions quietly entered the system, and where something coherent may still not be safe to operationalize.