(At least the author sprang for a $20 a month subscription.)

Depends on what you mean by underlying issues. If you're in a regulated environment, it may be such a mountain of red tape to change behavior that it's not worth it, even if you know it's not ideal.

But if the underlying issues are tech debt, bad design, and other things invisible to the outside world, that's different.

Of course it won't quite work, but I can definitely see why some people would want that.

Eh maybe not.

Stuff that has a lot of deprecated features is honestly burdensome on AI. It keeps rediscovering the deprecated features as the understanding that they are deprecated fall outside of the context window.

What you need is something that either never deprecates syntax, or is <10 years old with minimal changes over that time.

Since our owners also own an IT consultant agency, I ran the same process through with one of our regular consultants who is an actual awesome data architect. The output was strikingly similar, well except that I/we didn't need to make the slides. I then had him run over the actual slides, and all we changed was adding a { between some arrows to make the source of the arrows more clear.

We're still going to use real human consultants in the loop because they are readily and freely available, and because this is still new. I doubt we'd want to spend 100 consultant hours on something like this in 5 years though. I mean, we'd still do it for decisions where we'd want someone to blame.

Doing in days what used to take months, is a bit of a game changer. Like with past cost reductions, people will underestimate the work and get it wrong. It helps if you know what you are doing rather than just vibe coding things.

But for rewrites, the sunk cost fallacy becomes a lot cheaper. So, that changes how you deal with stuff that clearly isn't living up to expectations. Unceremoniously replacing what wasn't that expensive to begin with might be the cheaper option relative to fixing it.

Estimates are considerably longer, QA is much harder, integration is full of buckets and rakes, some "senior" devs are afraid to touch stale core code, innovation is stifled, devs are frustrated, hiring is harder, attrition bites. The most frustrating thing is that its very hard to communicate the issues as everyone experiences a fragment of the pain and none of it lines up in a spreadsheet for anyone to appreciate the whole cost. Everything just sucks.

LLMs changing the economy of this sounds great, especially if removes the essential issue with the ground up rewrite, which is the "ground up" part.

OP is playing the game. The post literally says "from LinkedIn" so if you look, he has 500+ connections and 1400 followers. That's not nothing. Good for him, all advice points to this new attention economy we live in.

I'm a bit aged out of all this. And I rode the 2010s wave so I can't give any advice in good conscience. I can only say that I see you and there's a whole world of silent majorities out there with no follow count and no broetry with our name on it. (search for that word in this thread, just learned it, it's great!)

Between context collapse and hallucinations, how likely is it that the end result isn't slightly polished slop that misses lots of crucial details?

I mean it is a tool and you need to understand how the tool works. When there is too little context, where there is so much context so that you are poisoning it, when you are allowing the tool to do patch-on-patch and etc.

[1] https://fenwick.media/rewild/magazine/dead-broets-society-be...

For example, the code base contains a physical controller. It’s closed loop in that it can react in realtime to changes. But it’s a slightly untypical implementation because this one can even look into the future through simulations. But Fable does not understand that. Instead, I need to remind it every 30 minutes that this is closed loop. It keeps wrongly claiming that the controller was open loop and then based upon that it will make up constraints that don’t actually exist.

And in my experience, these are _dangerous_. People go into "while we're at it..." mode, and it quickly turns into a big 2.0 kind of thing that takes forever.

I would argue that LLMs can speed this kind of thing up, but not by an order of magnitude or anything, just a bit. Unless there's high risk appetite.

Incidentally, Whenever i've done this in the past it's had a pleasant side effect of improving architecture. You end up forcing something akin to "push for's down and pull if's up" because crossing the ffi boundary is not free. It can be quite magical, as in leading to comically unbelievably speed ups when you also take advantage of vector intrinsics.

These two technologies combined greatly simplified this specific product making it far easier to maintain. Performance on these services was not important so native code was carrying a lot of penalties without the benefits.

Having a well documented messenger like service bus with great SLAs removed several tools we had needed in the old implementation.

We were able to leverage the tests form the original product to define success and tmthus were able to solve a lot of the edge cases in the new code w before we even shipped.

However, the old code was perfectly fine code. If new technologies had not provided significant simplification of the service architecture, a rewrite would've been foolish. And without the very good previously existing tests, we would've run into a lot of issues as we released.

I tend to believe that the engineering culture you describe will end up producing similar or, as Joel postulates, an even worse result, just dressed up in a modern stack.

If the technical leadership remains the very same one that enabled such a culture, I don't see them being able to suddenly produce a genuinely better software product only because an LLM is in a picture - especially considering how easy it is to convince an LLM that your idea is the best one.

But it really is not "true for humans" the way it's true for LLMs. I've said this before: the most depressing thing about the 2020s AI boom is how certain tech folks explain away the lack of intelligence in LLMs by appealing to ignorant and misanthropic folk psychology.

AI won’t.

Building products that no one really knows the internals of is crazy to me, and the methods people have of trying to mitigate that problem seem half assed at best

With more disciplined engineers we are slowly cleaning it up but it is taking years to realize because management won’t allow work to be stopped on feature development. If we’re lucky, we get two sprints a year to fix things, usually around holidays when half the team is afk anyway so not a huge chunk can be fixed. Then on top of all of that, if you break something when trying to Boy Scout rule improve things, you get chastised and management clamps down more on “scope creep”.

Add in LLMs and now engineering management is convinced that they will solve our problems. Except it can’t really because the project is so spread out and disjointed that it’s impossible to reason about. You’d spend tens of dollars just to have it follow all possible branches of our most critical user flows (and then with hallucinations on top!).

I’m not saying the bots aren’t useful, but they cannot comprehend a disaster zone architecture in anything more than extremely targeted chunks. Without being able to see the entire thing, having it reliably refactor is just not possible without weeks of manual testing or taking a risk and being prepared to rollback on short notice. Writing tests would also take many weeks and if the point is to rearchitect to something sane, a snapshot test is not really going to cut it.

It’s a pickle of a problem for sure… and I’m not sure I will survive at this company long enough to see the end (though I’ve been here years already).

If you gave junior dev exact tasks what to do where you will get better results.

Just like with LLM.

Meanwhile, I have a hard time to believe people don't encounter problems with AI solutions on a regular basis (I do).

We have some and sometimes marketing comes back with some extra revenue from a partner if we build out feature X Y or Z for their new product launch. The contracts are signed so engineering has to do it or we’re blamed for lost revenue.

A few of those a year and you eventually end up in a similar situation.

> It's not used in production.

Sounds like it’s a tech demo as of now.

I’ve been hearing for quite some time now that I should be using an LLM to plan before the build. This is treating the LLM as the architect, not as a junior being handed small tasks here and there.

I haven’t bought into it, so don’t use it this way, but an army of people online and in the media are pushing the fomo hard and telling people this is how it should be used. If the LLM isn’t doing what we want, it simply means we need to use the LLM even more. That’s the prevailing message from the industry.

What is definitely not solved is knowing what you want and what user wants and what the end result is supposed to be. To write the code you need the specs and to write the specs you need to know what you want. And that can only be answered by years of therapy.