ОБ ЭТОМ ЭПИЗОДЕ
Indeed increased AI coding tool adoption from roughly 25% to 97% across its engineering organization, but getting engineers to use the tools was only part of the challenge.
In this session from DX Annual, Michael Redding, Principal Product Manager, and Jeff Davis, VP of Core Infrastructure at Indeed, explain how the company used structured training, leadership support, and ongoing community engagement to help more than 2,000 engineers build practical AI skills. They share why an early train-the-trainer model fell short, how they redesigned their approach around hands-on learning, and what they learned about balancing adoption, measurement, and psychological safety.
They also discuss the impact of the program on coding time, the role of continuous enablement after formal training ended, and how Indeed is preparing for the next phase of AI adoption, including agentic workflows and AI-powered coaching.
Where to find Jeff Davis:
• LinkedIn: https://www.linkedin.com/in/utjeffd
Where to find Michael Redding:
• LinkedIn: https://www.linkedin.com/in/reddingsetgo
In this episode, we cover:
(00:00) Intro
(01:05) Indeed's DX survey from January 2025
(02:30) The two-part strategy to double engineering productivity
(04:21) How Indeed increased AI adoption from 25% to 97%
(15:40) Results from Indeed's AI training program
(18:33) How Indeed sustains AI adoption and learning
(23:06) What's next for AI enablement at Indeed
(24:41) Q&A: How coding time was calculated
(25:25) Q&A: How Indeed uses AI playbooks
(26:40) Q&A: Balancing asynchronous and live AI training
(28:22) Q&A: Psychological safety during AI adoption
(31:44) Q&A: Why AI adoption spikes after the holidays
(33:20) Q&A: The metrics Indeed tracked
(35:22) Q&A: Where the time savings are going
(36:54) Q&A: Reaching engineers who skipped the training
(38:08) Closing thoughts
Referenced:
• Indeed
• Claude Code | Anthropic's agentic coding system
• Cursor
• Windsurf
• Amp Code
• The Complete Guide to Building Skills for Claude | Anthropic
