
AI Features Without a Feature Factory
Aaron Wise
AI feature prioritization: fund a model only when there is a measurable user problem, data you can use and a way to evaluate it. Otherwise it is output.

Aaron Wise
AI feature prioritization: fund a model only when there is a measurable user problem, data you can use and a way to evaluate it. Otherwise it is output.
Aaron Wise
Real numbers from one week of Claude Code and Codex — cost, cache savings, CI minutes, what ran, and what broke.
Aaron Wise
Leading engineering teams with AI coding agents: make review the main job, keep a named human owner per system, and retrain juniors for judgment.
Aaron Wise
Engineering metrics for the board: report predictability, reliability, cost, risk and capacity, drop activity counts, and adapt the page as you grow.
Aaron Wise
AI feature prioritization: fund a model only when there is a measurable user problem, data you can use and a way to evaluate it. Otherwise it is output.
Aaron Wise
SaaS pricing decisions set architecture: seats, plan limits and usage billing each have a build cost. Bring engineering in to cost options before launch.
Aaron Wise
Real numbers from one week of Claude Code and Codex — cost, cache savings, CI minutes, what ran, and what broke.
Aaron Wise
Coding agents and supply chain security: agents add packages and run install scripts nobody approved. Gate new dependencies, sandbox agents, pin builds.

Engineering, Insights, Leadership & Management, Must Read
Senior engineering leaders need a clear problem, founder-market fit, and rough business plan before joining a startup.

The right roadmap prioritization model depends on your company’s growth stage and strategic goals.
Aaron Wise
LLM cost per query, fully loaded: what one answer costs, what it is worth, what heavy users do to both, and the levers that fix the math before launch.
Aaron Wise
LLM evaluation sets are the spec: write twenty good-answer test cases before building, with product owning the bar and engineering keeping it green.
Aaron Wise
NLP adds context to flat text through statistical and neural models, enabling machines to act on meaning rather than symbols.
Coding agents and supply chain security: agents add packages and run install scripts nobody approved. Gate new dependencies, sandbox agents, pin builds.
SaaS pricing decisions set architecture: seats, plan limits and usage billing each have a build cost. Bring engineering in to cost options before launch.
Leading engineering teams with AI coding agents: make review the main job, keep a named human owner per system, and retrain juniors for judgment.
How to explain cloud and AI costs to a CFO: unit costs, range forecasts with named drivers, commitments shown apart, and what changes by stage.

Cross Organizational, security
Enterprise security questionnaires stall deals nobody owns. Run review as a sales stage: answer library, trust page, one owner, SOC 2 when deals need it.

Product Management, Cross Organizational
SaaS pricing decisions set architecture: seats, plan limits and usage billing each have a build cost. Bring engineering in to cost options before launch.