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I don't think AI will make your processes go faster

frederickvanbrabant.com

271–280 of 490 posts

Re: I don't think AI will make your processes go faster

#271

Earlier quoted context omitted.

That's the kind of stuff where you would write a few lines of shell script or perl and not bother with the whole GTK stuff. Because GTK would be accidental complexity to the task (unless you used something like zenity). This is one of the reasons I like the OpenBSD and suckless projects. There are solutions that are technically correct, but are overengineered.

Well I would never write shell because I loathe it's grammar/syntax. I enjoy GUIs and am a heavy mouse user, so the GTK part isn't really an "accidental complexity" but a must have for me. If a LLM can one-shot all the GTK boilerplate it's a win. That's (as shown in my sample prompt) one great thing I've been using LLMs for: making GUIs for arcane Linux-based OS/userland settings that I have no interest in doing "sud…

And that’s fine.

I was pointing out that a simpler solution exists. I prefer simple solutions, because I want to test whatever idea I have in real world situation first before I go for a more complete one. Kinda like doodling before committing to do a sketch (or spend weeks doing a painting).

> It's been 30+ years, we deserve a better desktop experience

That desktop experience would need to be like smalltalk (where it’s trivial to modify the gui). The nice power of Unix is having the userland being actually a userland. Meaning you can design a system for your workflow and let the computer take care of that. Current desktop environment doesn’t allows for that kind of flexibility.

Also it’s the nature of unix that makes such basic utilities possible (and building them with raw xlib or tcl is easier than gtk). Imagine doing the same on macOS or Windows where everything is behind an opaque database where some other process fancies itself as its owner.

Re: I don't think AI will make your processes go faster

#272

Earlier quoted context omitted.

Sorry where are we seeing that it failed? It compiled multiple projects successfully albeit less optimized. " It lacks the 16-bit x86 compiler that is necessary to boot Linux out of real mode. For this, it calls out to GCC (the x86_32 and x86_64 compilers are its own). It does not have its own assembler and linker; these are the very last bits that Claude started automating and are still somewhat buggy. The demo vide…

Yeah I think people are really underestimating what LLMs can do even without specs. As an example, I did an exploratory attempt to add custom software over some genuinely awful windows software for a scientific imaging station with a proprietary industrial camera. Five days later Claude and I had figured out how to USB-pcap sample images and it's operationalized and smoothly running for months now. 100% of the code w…

People both underestimate and overestimate what LLMs can do. LLMs have shown very different results when autonomously writing a small program for personal use and autonomously writing production software that needs to be evolved for years.

Re: I don't think AI will make your processes go faster

#273

> This exact thing is what software developers have been begging for since the beginning of the profession: Receiving a detailed outline of the problem and what the end result should look like. > This is often the part that slows down software development. Trying to figure out what a vague, title only, feature request actually means. But that is exactly what Software Engineering is!. It's 2026 and the notion that you…

I completely agree. It's more than 40 years since I wrote my first program, and I've never seen software that was first specified and then written and all was good.

The most difficult part of any non-trivial engineering is understanding the problem, and the first versions of a piece of software are how you reach that understanding.

That's why I do not think that AI-powered "software factories" will ever work. It's waterfall development all over again. An architect writing UML diagrams and handing them off to the team of programmers to do the essentially mundane task of implementing... the wrong thing.

AI is, however, very good at helping you go fast from the wrong first version to the less wrong second one. But you need to remember that your main task is to understand the problem that you are trying to solve.

Re: I don't think AI will make your processes go faster

#274
Whilst the conclusion of the article certainly seems plausible, it glosses over the cost calculations and simplifies them too much.

The cost of a subscription is somewhat offset by being guaranteed income regardless of usage, following the financial models of gyms. Whilst api costs represent both the convenience of on-demand pricing and the scale for applications with many users.

Further, the costs of api and subscriptions need to cover the operating costs of the business, the massive SOTA training costs as well as the costs of inference.

The true cost of serving tokens is buried in all of that in these enormous, opaque companies.

Re: I don't think AI will make your processes go faster

#275

> This exact thing is what software developers have been begging for since the beginning of the profession: Receiving a detailed outline of the problem and what the end result should look like. > This is often the part that slows down software development. Trying to figure out what a vague, title only, feature request actually means. But that is exactly what Software Engineering is!. It's 2026 and the notion that you…

> Trying to figure out what a vague, title only, feature request actually means.

> My take is that to accelerate processes we should reduce coordination overhead and empower individuals and teams to make decisions and execute on them.

This is funny because it's exactly what the agile/scrum training taught me 20 years ago.

Re: I don't think AI will make your processes go faster

#276
People don't really understand that non-trivial software development isn't even 50% coding. The coding step is generally the 'easiest' part and given to Junior developers. In a large org most product changes span multiple systems and human operations. Seniors and even mid-level generally spend most of their figuring out how to shape the local priorities into a new arrangement of the existing cybernetic entity and then getting buy-in on that new vision given these other teams have their own priorities.

This naturally involves a lot of tradeoffs and politics - senior engineers know to avoid adding 'weight' to their airframes and fight hard to avoid adding scope to the systems they're responsible for or divergence from their intended direction of travel. So compromises have to be struck or escalations to management to choose between priorities have to play out.

Maybe AI solves that as well but that is a lot more difficult lift.

Re: I don't think AI will make your processes go faster

#277
post #203

Earlier quoted context omitted.

A workable C compiler is a ~10-50KLOC program, and a fairly simple one at that (batch, with no concurrency or interaction). That Anthropic's swarm of agents wrote 100KLOC before failing is a symptom of the problem. It's certainly possible that many programs are in the sub 5KLOC range, but it's definitely not "most software". Plus, almost no software has this level of detailed spec, ready-made tests, and a selection o…

The compiler that claude made went way beyond workable. It could compile the full linux kernel afaik. That is much further even beyond standard C.

People who independently tried to use it reported that it is very much not workable:

- "CCC compiled every single C source file in the Linux 6.9 kernel without a single compiler error (0 errors, 96 warnings). This is genuinely impressive for a compiler built entirely by an AI. However, the build failed at the linker stage with ~40,784 undefined reference errors."(https://github.com/harshavmb/compare-claude-compiler)

- Overall it’s an interesting experiment, and shows the current bleeding edge of Claude’s Opus 4.6 model. However the resulting product is also a clear example of the throwaway nature of projects generated almost entirely by AI code agents with little human oversight. The prototype is really impressive, but there is no real path forward for it to be further developed. It can build the Linux kernel [for RISC-V], which is impressive. It can also build other things… if you are lucky, but you really cannot rely on it to work. (https://voxelmanip.se/2026/02/06/trying-out-claudes-c-compil...)

Anthropic themselves said that the codebase was effectively bricked and that their agents could not salvage it.

Re: I don't think AI will make your processes go faster

#278

> This exact thing is what software developers have been begging for since the beginning of the profession: Receiving a detailed outline of the problem and what the end result should look like. > This is often the part that slows down software development. Trying to figure out what a vague, title only, feature request actually means. But that is exactly what Software Engineering is!. It's 2026 and the notion that you…

I don't agree.

I regularly get pieces of work someone product guy has thought up in an afternoon. They only care about the happy path, and sometimes only part of the happy path. I work for a global company that has to abide by rules and regulations in each country we operate in. The product guy thinks up some feature, we implement the feature, then we're told "actually, we legally aren't allowed to do this in 90% of the markets we operate in". Cool, so we add an ability to disable it in those markets. Then they come back "We can do this in some of those markets if it's implemented with [regulatory bureaucracy], so can you do that please".

Then we have to hack away at the solution because the deadline is right around the corner.

This is not software engineering! None of this is related to the software. The job of a software engineer is to take a list of requirements and figure out the way we accomplish those requirements. Requirements gathering is NOT a software engineering problem. Software is implementation, product is behaviour. That's the split. The behaviour of the thing we're building needs to be known before we even try to seriously build it.

If someone just held back for week and did their due diligence, we would been able to architect a solution that is scaleable, extensible, easy to maintain and can make the future easier.

Re: I don't think AI will make your processes go faster

#279
post #269

Earlier quoted context omitted.

Sorry where are we seeing that it failed? It compiled multiple projects successfully albeit less optimized. " It lacks the 16-bit x86 compiler that is necessary to boot Linux out of real mode. For this, it calls out to GCC (the x86_32 and x86_64 compilers are its own). It does not have its own assembler and linker; these are the very last bits that Claude started automating and are still somewhat buggy. The demo vide…

> where are we seeing that it failed? Anthropic said the experiment failed to produce a workable C compiler: - I tried (hard!) to fix several of the above limitations but wasn’t fully successful. New features and bugfixes frequently broke existing functionality. - The compiler successfully builds many projects, but not all. It's not yet a drop-in replacement for a real compiler. (source: https://www.anthropic.com/eng…

> Can they write production software without careful and close human supervision? Not yet. That's not disparagement, just an observation of where we are today.

I never claimed they could! I just view this as a successful experiment. I don't think anthropic was making that claim with their experiment either.

It feels reflexive to the moment to argue against that claim, but I tend to operate with a bit more nuance than "all good" or "all bad".

Re: I don't think AI will make your processes go faster

#280

People don't really understand that non-trivial software development isn't even 50% coding. The coding step is generally the 'easiest' part and given to Junior developers. In a large org most product changes span multiple systems and human operations. Seniors and even mid-level generally spend most of their figuring out how to shape the local priorities into a new arrangement of the existing cybernetic entity and the…

LLMs mostly only being code-writers was true a year ago, but it is not true now. Now they are tool-callers, which means a coding agent can effectively: run lints/typechecks/tests (and fix resulting errors), dig into observability platforms to identify root cause of isses (e.g. on Sentry or similar), run benchmarks to identify slow code / hot paths, keep systems up to date by reading migration docs (and applying them) for new majors of consumed libs, etc.

So sure, if you have none of these things set up to back-pressure agents and help them better understand the system, then they will just be dumb LLM code writers. But you can definitely go a lot further than that with the improvements that are rapidly happening to models and harnesses.

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