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I run a small team building Dreamlux.ai (AI video generation). AI changed my day-to-day in a few concrete ways:

Coding: I write less boilerplate and more “integration glue”. LLMs are great for scaffolding (Next.js routes, workers, SQL migrations) and translating logs/errors into hypotheses. Biggest win is speed from idea → working PR, not perfect code.

Debugging/ops: I paste real production symptoms (headers, cache status, curl repros, traces) and ask for ranked root-cause candidates + experiments. This reduced “blind poking” a lot, especially around CDN caching rules, 429s, image optimization, and edge-case billing/credits.

Planning/reviews: We now require “AI-assisted PR reviews” to include: risk list, test plan, rollback steps, and what metrics should move. It’s basically a checklist generator + reviewer #2. Humans still make the call.

What stuck: ChatGPT + a copilot in editor for daily work; LLM as a “rubber duck” for incident triage and for turning messy notes into specs.

What felt like hype: autonomous agents that “own” features end-to-end. Without tight scopes, they wander; with tight scopes, they’re just faster scripts. The sweet spot is human-led, AI-accelerated loops.

Curious: for managers, what’s your best process change that AI enabled (not just “wrote code faster”)?