Any recommendations for training approaches that help software developers understand how to use AI coding tools safely and effectively?

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Engineering Manager in Construction7 hours ago

Follow the CRIT method. I read The AI Driven Leader by Geoff Woods. This style delivers much better results for most things vs trying to us AI in the same manner as a search.

Head, Software Engineering, Cloud and Digital Transformation22 days ago

We host periodic brown bag and knowledge sharing sessions where we share Do's and Dont's. We also emphasize the mandatory review by human being during PR approvals. And in later phases CI/CD pipeline, we have security scanning tools to make sure that code is secure.

VP of Engineeringa year ago

In addition to external training, we use internal modules and encourage developers to get hands-on experience. AI tools help with tasks like checking code syntax and handling repetitive tasks. Training is an ongoing process, not a one-time event. Regular training sessions, whether monthly or quarterly, are necessary. Bringing in AI experts from external sources can also provide valuable insights into using the technology efficiently.

VP of Engineeringa year ago

We use two main approaches. First, we bring in external experts, like the GitHub team, to conduct training sessions on tools like GitHub Copilot. These sessions often reveal features that developers weren't aware of. Second, we identify power users within our organization—developers who use the tools extensively and understand them well. We are setting up training sessions where these power users can share their knowledge with other developers. Both external training and leveraging internal expertise are effective ways to get developers up to speed.

Customer Success Manager in Hardwarea year ago

It's crucial to educate team members on using AI tools ethically and securely. Training should cover basic knowledge of the tools, examples of handling bad data, and standard operating procedures. Workshops and thorough documentation are essential. Emphasizing security, ethical use, and compliance will help ensure that proprietary data is not misused during automation processes.

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