CTOs from Microsoft, 1Password, and Atlassian share how AI is reshaping engineering organizations. Key themes include: the SDLC shifting time from 'create' and 'operate' toward 'plan' and 'validate'; smaller squads (3-4 people) for zero-to-one projects; planning horizons shrinking from 18 months to a single quarter; AI adoption driven by organic champions rather than mandates; managing volatile AI token costs like cloud COGS; non-engineers submitting PRs and test code; and the future engineer profile emphasizing generalist product instincts, agency, and a maker's mindset over narrow specialization.
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What does an AI-native SDLC look like?Has AI changed how your engineering orgs are structured?Do any of your organizations mandate AI usage?How are you managing AI costs?How do you define the skills profile of a great engineer 3-5 years from now?Where are the boundaries when non-engineers contribute code?Sort: