This week I spent time with a group of leaders in research software engineering at a workshop on the implications of using LLMs in their work. I gave a short lightning talk and shared a position paper representing my current thinking on AI assisted coding.

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This week I'm talking at Monki Gras about developer learning and AI.

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This post was originally published at dev.to/fastly.

Software written using generative AI is all over the web. Performance and security issues abound. Open source projects are being overwhelmed by bot traffic. There's a lot of harm being caused, but as an educator who cares about lowering barriers to software creation, I can't ignore the democratizing potential of these tools either.

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This post was originally published at dev.to/glitch.

AI-assisted coding is lowering the barrier to making software. It’s also increasing the complexity of managing it. You can make applications with less upfront knowledge than before, and organizations are having to figure out how to handle the ensuing unpredictability and risk. So it’s getting easier and harder.

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This post was originally published at blog.glitch.com.

AI assisted coding has really taken off recently. The tech and the conversation around it say some interesting things about our understanding of what developers do.

AI can write some kinds of code, and it’s even helping people who aren’t coders to make software applications. It’s also frequently wrong. We’re still learning the types of coding task it’s suited to — in what specific contexts it’s a help rather than a hindrance. Unrealistic expectations and inaccurate interpretations abound! The conversation reveals our inability to define the real skills in being a software developer.

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