[delusional]

> just ask any software engineer about what’s happening to their profession

I'm a professional developer, and nothing interesting is happening to the field. The people doing AI coding were already the weakest participants, and have not gained anything from it, except maybe optics.

The thing that's suffocating is the economics. The entire economy has turned its back on actual value in pursuit of silicon valley smoke.

[latentsea]

Nothing interesting happening in the field? If you've been paying attention the trend over the last two years has been that the problem space that requires humans to solve has been shrinking. It's continuing to shrink. That's interesting. Significantly interesting.

As an engineer that's lead multiple teams including one at a world leading SaaS company, I don't consider myself one of the weakest participants in the field and neither do my peers generally. I'm long on agents for coding, and have started investing heavily in making our working environment productive not only for humans, but now for agents too.

[jondwillis]

So what does that amount to? Shared Claude code hooks and skills?

[latentsea]

Things like that are only part of it. You can also also up your agents batting average by finding ways to build guardrails and things that inject the right context at the right time.

Like for instance we have a task runner in our project that provides a central point to do all manner of things like linting, building, testing, local deployment etc. The build, lint and test tasks are shared between local development and CI. The test tasks run the tests, take the TRX files and use a library to parse it to produce a report. So the agent can easily get access to the same info as CI is putting out about test failures. The various different test suites output reports under a consistent folder structure, they also write logs to disk under a consistent folder structure too. On failure the test tasks output a message to look at the detailed test reports and cross-reference that with the logs to debug the issue. Where possible the test reports contain correlation IDs inlined into the report.

With the above system when the agent is working through implementing something and the tests don't pass, it naturally winds up inspecting the test reports, cross referencing that with the logs, and solving the problems at a higher rate than compared to just taking a wild guess at how to run the tests and then do something random.

Getting it to write it's own guardrails by creating Roslyn Analyzers to make the build fail when it deviates from the project architecture and conventions has been another big win.

Tonnes of small things like that start to add up.

Next on my list is getting a debug MCP server, so it can set breakpoints and step through code etc.

[jp8585]

That’s fascinating. If you don’t mind me asking, what type of software development do you do? Have you tried any of the latest coding tools? Or even used LLMs as a replacement for stack overflow?

[delusional]

Professionally, I do banking. It's a lot of integration work, sprinkled with a little algorithm every now and then. Lately I've been on capital requirements. The core of that is a system called AxiomSL, which is quite a lot of work for one guy to keep running.

In my spare time I write some algorithmic C, you can check that stuff out on github (https://github.com/DelusionalLogic) if you're curious.

I was an early adoter of LLM's. I used to lurk in the old EleutherAI discord and monitor their progress in reconstructing GPT-2 (I recall it being called GPT-J). I also played around a bunch with image generation. At this point nobody really tried applying them to code. We were just fascinated that it wrote back at all.

I have tried most of the modern models for development. I find then to generate a lot of nonsensical and unexplainable code. I've had no success (in the 30 or so times I've tried) at getting any of the models to debug or develop even small features. They usually get lost in some "best practice" and start looping on that forever. They're also constantly breaking style and violating module boundaries.

If i use them to generate documentation I find it to be surface level and repetitive. It'll make a lot of text about structures that are obvious to me just glancing at the code, but will (obviously) not have any context about the thought process that created that code, which is the only part I care about. I can read the code just fine myself. This is the same problem I find in commit messages generated with AI tools.

For the reversing I also do, I find the models to be too imprecise. It'll take large logical leaps that ruin understanding of the code I'm trying to understand. This is the only place I actually believe a properly trained (not a chatbot) model could actually succeed past the state of the art.

I don't really use stackoverflow either, I don't trust its accuracy, and it's easy to get cargo culted in software. I generally try to find my answers in official documentation, and if I can't get that I'll read the source code. If that's unavailable I'll take a guess, or reverse the thing If it's really important to me.

[frizlab]

I would love to be able to say the same but I’m literally the only last person in the company still not using AI to code (if anything for ethics reasons, but I also truly do not need it at all), and I am obviously not the only good dev in the company. The gain is highly debatable (especially in delivery, I do not trust self-reports), however there have been recent reports of morale improvement since using AI, so at least there’s that.

[nl]

I'm a decent dev and I'm possibly 100 times as productive using AI.

It lets me concentrate on the parts I'm good at and ignore things I don't care about. Claude is a lot better at React than I am and I don't care.

[delusional]

100 times? You do in a day what used to take you 3 months?

Those are just not realistic numbers.

[nl]

Yes.

In the last 2 months I’ve built 3 end-to-end micro-SAAS apps.

It would easily take me a year to do that in the past because I hated some parts so much I'd just avoid working on them.

Now it's literally "bite down for and evening and it's done" whereas it could be 6 months or more before.

If anything 100 times is underestimating how much more I'm doing.