The Grug Brained Developer

cubic blog: The real problem with AI coding

Can you ship AI-generated code without creating a maintenance nightmare six months from now? Can you debug it when it breaks? Can you modify it when requirements change? Can you onboard new engineers to a codebase they didn’t write and the AI barely explained?

Most teams haven’t realized this shift yet. They’re optimizing for code generation speed while comprehension debt silently accumulates in their repos.

One team I talked to spent 3 days fixing what should have been a 2-hour problem. They had “saved” time by having AI generate the initial implementation. But when it broke, they lost 70 hours trying to understand code they had never built themselves.

That’s comprehension debt compounding. The time you save upfront gets charged back with interest later.

Generative AI Is Not Going To Build Your Engineering Team For You - Stack Overflow

People act like writing code is the hard part of software. It is not. It never has been, it never will be. Writing code is the easiest part of software engineering, and it’s getting easier by the day. The hard parts are what you do with that code—operating it, understanding it, extending it, and governing it over its entire lifecycle.

The present wave of generative AI tools has done a lot to help us generate lots of code, very fast. The easy parts are becoming even easier, at a truly remarkable pace. But it has not done a thing to aid in the work of managing, understanding, or operating that code. If anything, it has only made the hard jobs harder.

Home-Cooked Software and Barefoot Developers

A very thought-provoking presentation from Maggie on how software development might be democratised.

The collapse of complex software | Read the Tea Leaves

Even when each new layer of complexity starts to bring zero or even negative returns on investment, people continue trying to do what worked in the past. At some point, the morass they’ve built becomes so dysfunctional and unwieldy that the only solution is collapse: i.e., a rapid decrease in complexity, usually by abolishing the old system and starting from scratch.

Agile and the Long Crisis of Software

Time and again, organizations have sought to contain software’s most troublesome tendencies—its habit of sprawling beyond timelines and measurable goals—by introducing new management styles. And for a time, it looked as though companies had found in Agile the solution to keeping developers happily on task while also working at a feverish pace. Recently, though, some signs are emerging that Agile’s power may be fading. A new moment of reckoning is in the making, one that may end up knocking Agile off its perch.