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Being intentional about friction
Pondering what Glitch tell us about friction and developer learning when LLMs can generate code.
This time last year I was building paths for folk migrating apps away from Glitch. We were approaching the shutdown date and I needed alternatives for the Fastly onboarding projects I'd used as the foundation of the learning program I was leading – and that I’d candidly been hoping to integrate enough into product onboarding that the company would be persuaded to keep Glitch around. I also had a more personal need to figure out alternatives, as I'd relied on Glitch for teaching much longer than I'd been employed to work on it.
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Which direction is forward?
Software role changes tell us something about the goals in LLM deployment.
There’s a role that appears to be exploding in popularity in AI adjacent companies right now: the Forward Deployed Engineer. Since I first heard about LLM assisted coding, aside from the very real enabling potential, I’ve worried that the outcome would be a future where fewer people understood how critical systems worked. I believe some of what we’re seeing with these jobs is a reflection of that.
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Pedagogy is the way
Looking back at three years of thinking and posting about ai assisted coding.
It’s three years since I first wrote about AI assisted coding. You can still read that post on the Glitch blog: Software development isn't writing syntax
A lot has happened since then, but as I said in a weirdly popular LinkedIn post recently, my beliefs have proven pretty resilient – tl;dr:
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On convenience and understanding
Can we leverage automation while still preserving understanding?
"There is some compulsion in software where automation breeds more automation and we accidentally leap over the phase where it was actually optimal for both usefulness and understanding." Me, on mastodon the other day
Being able to generate code is forcing us to figure out when it’s a good idea to actually write it.
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How should we teach software development now?
Exploring software development learning topics in the context of AI-assisted coding.
Yesterday I posted on LinkedIn about realising I've been thinking and writing about AI-assisted coding for three years now, and that overwhelmingly I still stand by the positions I've taken. My first public post on the subject was in May 2023, so I'm going to revisit it on the same day this year. But for now, since the discussion touched on what we should be teaching on software engineering courses, it prompted me to jot down my current thinking, still very much WIP but here you go.
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Automation is a trade-off
We should have more explicit conversations about the trade-offs we make when we use automations.
This post was originally published on dev.to.
A couple of years ago I wrote a post about abstractions. I’m revisiting it here with AI-assisted coding in mind, because I see similar issues arising. LLMs make it easier than ever to generate code, but when we look at what happens next, the picture becomes a little bit less clear.
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What to do about developer skills
This week I talked at Haggis Ruby in Glasgow.
I've been giving talks about developer learning and AI-assisted coding pretty regularly over the last couple of months. Doing this is helping me clarify my own thoughts and better position me to advise others, based on what I've learned about software engineering and pedagogy over the years. This week I had the pleasure of speaking at Haggis Ruby in Glasgow, with a community I wasn't part of but who could not have been more welcoming and open to what I was saying. ❤️
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When is a tool the right tool for the job?
Digging into skill development with a group of research software engineering experts.
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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Do your fingers remember how to code?
My Monki Gras talk – discovering developer skills worth learning when AI can write code.
This week I'm talking at Monki Gras about developer learning and AI.
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We should still teach coding
Coding skills are going to be as important as ever.
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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