
AI Adoption Checklist for Engineering Leaders
A 10-minute AI adoption checklist for CTOs. Seven areas, five levels, and how to find the bottleneck before you buy more tools.

A 10-minute AI adoption checklist for CTOs. Seven areas, five levels, and how to find the bottleneck before you buy more tools.

What TypeSafe's System One Models and Jev mean for product teams - typed decisions instead of chat strings, and where they fit in real AI workflow automation.

Where applied AI automation cuts SMB ops cost first - support, admin handoffs, and knowledge work - and how to pick a 90-day pilot with real KPI.

AI prototyping vs a durable MVP - and why vibe coding without engineering discipline breaks security and stability after a few patch iterations.

A practical framework for growing product companies choosing between local FTE hiring, freelancers, and dedicated team extension when roadmap pressure meets slow hiring.

Which GRC standards apply to whom, what they require in practice, and which tool classes fit each product maturity stage.

How enterprises should choose and roll out coding assistants (Claude, Cursor, Copilot and peers) - infrastructure, code and product quality, adoption KPIs, and what not to do.

Phased application modernization vs a full rewrite - and where AI helps with legacy work versus when generating a new product is a false shortcut.

How to hire dedicated developers who stay committed through a multi-year product roadmap — vetting criteria, ramp-up timeline, retention levers, and pricing, compared with project outsourcing and in-house hiring.