Lead engineering with AI doing the heavy lifting, not the thinking.
Get the CTO / VP Eng briefIn 2026, AI handles much of the first-draft work that used to fill an engineering leader's week: drafting architecture decision records, reviewing pull requests for risk, summarizing incident postmortems, and turning roadmap notes into structured tickets. The role shifts toward reviewing AI-generated technical proposals and catching the failure modes a model misses. Capacity planning, vendor evaluations, and hiring scorecards now start as AI drafts that you correct rather than write from scratch.
Paste these into Claude or ChatGPT and replace the bracketed parts with your own details.
Review this proposed architecture for [system/feature]. Here are the requirements: [requirements]. Here is the design: [design]. List the top 5 failure modes, scaling limits, and operational risks, ranked by likelihood and impact.Here is the incident timeline: [timeline]. Write a blameless postmortem with sections for impact, root cause, detection, and 3 concrete remediation items with suggested owners and priority.Create an interview scorecard for a [level] [role] on a team that owns [domain]. Include 5 competency areas, what strong vs weak looks like for each, and 2 sample questions per area.Turn these roadmap notes into structured engineering tickets: [notes]. For each, give a title, acceptance criteria, rough effort estimate, and dependencies. Flag anything that needs a design doc first.We need [capability]. Compare building it in-house vs adopting [vendor options]. Estimate engineering cost, maintenance burden, and time to value for each, and give a recommendation with the main risk of each path.One AI tool, one prompt, and one trick for CTO / VP Engs, every weekday morning. Free.