Beyond the Hype: A Pragmatic Look at How Developers Actually Use AI Tools
summary
Claude Code, GitHub Copilot, Codex, MS Copilot Studio and PyCharm agents feature in concrete workflows: deployed a website in 30 minutes using an open‑source privacy model, language tutors run in Claude, CI agents automatically open draft PRs after running tests, and Copilot is assigned issues that turn into merged PRs. Small models run locally on a MacBook Air, SEO edits run on CI, and practices surface—one-in-ten do the task manually—plus strong warnings about hallucinations and cleaning up AI‑generated junk.
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chapters (15)
- 0:00Introduction
- 1:14AI tools daily use
- 4:27Daily workflows with AI
- 10:07Workflow changes past 6 months
- 13:38Balancing small vs frontier models
- 15:05Choosing AI tools to learn
- 17:33AI for new challenges
- 18:59AI excitement and fatigue
- 20:48Avoid over-engineering with AI
- 23:14Advice for AI newcomers
- 26:49Recommendations for AI users
- 28:53Responsible AI use
- 29:15AI applications and future
- 30:40Mentoring developers
- 31:45Closing
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