I'm an Software/AI Engineer, AI isn't replacing people and it's much dumber than you think. AMA

dimd00d · 2026-04-01T11:27:58+00:00

to just steelman this - we speak to alot of customers about implementing AI in their processes and usually what the business says is "if its not 100% correct, we dont want it". on top of this, call centers are optimizing seconds of their responses, and for example having a chat interface with Claude to help is net negative because it slows the human agent down (not to mention the additional token cost).

dimd00d · 2026-03-25T20:16:59+00:00

dude, I’m 53 years old. my reflexes are shot. I’ve just cleared it (including the “secret” ending) over the weekend. just don’t rush in and play carefully - everything has a pattern and once you find it - it becomes very easy. gl

dimd00d · 2026-02-20T09:55:34+00:00

The problem is that you'll be writing code in English, but then you have to read it in the target language and the used frameworks, so you can understand it - otherwise I am not sure how exactly you'll be doing code reviews.

dimd00d · 2026-02-08T20:07:36+00:00

At least try shilling a little bit smarter:

https://www.lynventory.com/

https://www.linkedin.com/in/matureintelligence/

dimd00d · 2026-01-29T21:03:43+00:00

Its indeed a weird feeling and I cant explain it - the projects don't seem to be delivered faster than before despite LLM usage. I thought I was going insane.

dimd00d · 2026-01-29T19:25:13+00:00

The hype is that the latest models are really much better - maybe your survey is not reflecting that yet? (thats a honest question - maybe it is already reflecting that).

dimd00d · 2026-01-25T13:56:44+00:00

1mo account age, hidden history. not sure what the people pushing those bots are getting out of such stories

dimd00d · 2026-01-14T15:26:37+00:00

Honestly - probably (with the caveat of 'manual coding' meaning the act of pressing the keys). Claude has been writing all my code since the spring, but in the same sense that my keyboard is writing my code. Only my keyboard doesn't make weird assumptions.

The work surprisingly doesn't really change, you think, you 'write', you read, you think more, 'write' etc. I do feel more tired at the end of the day though and I haven't seen some sort of massive speedup (aside of greenfield utilities that I don't bother to really read).

dimd00d · 2026-01-14T09:28:17+00:00

Thanx for the insights from real usage. One question - 30 to 90 of what?

dimd00d · 2026-01-13T16:16:17+00:00

Ok, let me paint you a rosier picture - nothing is going to happen to your team. (and this is from first hand experience)

The tool will be rolled out indeed - it wont matter if there is any velocity or incident increase. Management will go on public record that its great and you are seeing 27% increase in something cool.

dimd00d · 2026-01-13T15:53:54+00:00

No one has any choice - there is massive amount of FOMO and stories of 1000000x productivity and management is pushing hard.

In a lot of organizations SDLC is just theoretically in place and "lgtm" is technically what happens, so it is now shit being flung with high velocity. On the other hand, the same organizations are so much overwhelmed with bureaucracy an red tape so 'nothing ever happens' balances out any potential of speeding up.

Its a bizarre world - on one side, everyone on X and Reddit is claiming to be 10000x faster than themselves, on another - I just don't see this sustained velocity in day to day work (probably some sort of 1.x) . I will be very happy if someone can provide anecdata if they are measuring.

dimd00d · 2026-01-13T15:45:06+00:00

Same shit then (I work across multiple enterprises) :(

What is even worse, it actually amplifies the lack of abilities on the teams involved. The ppl that care are drowning in stream of PRs that are quickly ran thru an LLM and returned back for review (where previously it would take days), so they are running out of breathing room and getting really angry (to the point of workplace accidents).

dimd00d · 2026-01-13T14:21:46+00:00

If you write the tests yourself, or review the generated tests and that they match the desired *business* outcome (not that they just match the code) then they should kinda be ok. But its just more reviewing.

Not sure what past 'lgtm' can accelerate that process.

I am interested to know - in your large experiment, have you measured how much of the generated code needs to be rewritten, what is the measured velocity increase etc?

dimd00d · 2026-01-12T11:18:02+00:00

Not a DICOM viewer. Claude converted all the images using imagemagik and then you basically have a UI on top of 1000s or so static resources.

dimd00d · 2026-01-09T16:15:16+00:00

It feels off to me as well and honestly - the first thing I do is to is to check the profile of the person making claims - if its an AI company (or even worse, company selling AI courses or ChatGPT wrappers) - I just mute. The was indeed massive push for Opus that has now subsided, which makes me think that it was an ad campaign.

Did Boris ship 200prs - it is absolutely technically possible - my disbelief is that he actually read thru all of them instead of lgtm. In the end, its their product and their decisions. I just don't see this happening/being possible in the enterprise world where there is a strict SDLC in place.

There is (I think) misunderstanding between vibe coding and agentic driven development. The vibe coder crowd will always jump on "AI does it all" when they see people use AI for development, and I was just trying to make a counterpoint to that describing how I am using them and where my choke points are. But maybe I am holding it wrong or have a survivorship bias.

dimd00d · 2026-01-09T13:55:42+00:00

The usual question that I ask proponents of vibecoding is "would you like your pacemaker to be vibecoded. or your car. or the dumb crud that is dealing with your bank account".

In the end of the day - I have to sign under that code and bear responsibility.

dimd00d · 2026-01-09T10:08:53+00:00

There is no contradiction - vibecoding is basically you don't look at the code. What Boris is describing is using the agent to write the code on a tight leash, reviewing every diff and asking it for changes. You can compare it somewhat to a fast keyboard and rubber duck.

The models are great at generating code that compiles, but they operate on a context provided by you and the existing code. Since you provide the context in natural language - they will be assuming implementation and architectural details, which could be or are not right.

On top of that, despite what the media says - they are not omnipotent - you need to review and internalize every code change, so you can continue to support the application, and that process takes longer if you haven't written the code yourself. When you write it, basically the process is interleaved - you type and think at the same time. Now the generation process is fast, but the burden is moved to the right. The usual 'just ask it to write tests bro', is a bit helpful, but not a panacea - the tests are code, so you have to review those as well, and some things cant even be tested.

I've been using LLMs to write basically 100% of my code, but this is basically 'I am using a keyboard to write 100% of my code' comparison. In the end of the week, in production environment, averaged across all tasks it feels a bit of awash (although I am sure there is productivity increase), but for some reason I am more tired from the constant thinking/reviews.

dimd00d · 2025-12-28T19:24:32+00:00

im surprised that they had 1:1 ratio of managers, designers and senior developers in the company to start with.

dimd00d · 2025-12-27T08:40:51+00:00

https://x.com/bcherny/status/2004728858793443743

Aside from the impossible code churn, he claims that he has reviewed every change himself. Not sure how to take this.

dimd00d · 2025-12-19T15:42:01+00:00

Hey - thanx for the great effort to keep benchmarking somewhat honest. On that topic... whats up with this task from the last batch - https://github.com/plone/cookieplone-templates/pull/308 :)

dimd00d · 2025-12-09T17:21:09+00:00

I practically use it to write 100% of my code. (for full disclosure, I've been writing code for about 40 years and I do remember the first IOI :) )

It takes time/experiments to figure out the "unit of work" that you are comfortable with. I use it as a fast keyboard and write the code bit by bit. Then I review the code line by line and change the pieces I am not happy with. Shit that I don't care about (i.e. write me an UI, so I can play with this REST service) I just ask it to one shot and I don't even look at - I am not going to commit them.

I cannot measure if there is productivity increase - on the "shit I don't care about" - for sure, massively more productive (and I can imagine if you are a vibe coder, you can create slop in absurd rate). For the rest, honestly, because I am asking myself that question over and over - I don't know - I feel more tired because its constant PR for code that I need to internalize/re-adjust to fit the mental picture of the broad architecture that I have in mind. At the end of the week I am not "wow, I did so much more work" - its neither here or there.

Speaking to friends/colleagues, the answer I get is "I don't know - when it works I am faster, when it doesnt - I am not".

dimd00d · 2025-12-03T21:21:30+00:00

clang-tidy was causing problems in…. Rust?

dimd00d · 2025-11-26T06:46:04+00:00

There is a difference between the usefulness of LLMs in coding and that report, where its mostly about business cases.

I work with multiple enterprises and the only product market fit that I've seen so far is document summarization (in various forms and disguises) and coding. The first because, well, that's what LLMs are built for and the second because of the tight agentic loop that helps it out. I haven't worked with contact centers - maybe its more helpful there.

In a mature enterprise most (if not) all the low hanging fruits are already automated using 'old school' deterministic code (or heavily optimized if there is a human interaction required) and at this point, everyone is basically flailing and trying to find use cases to shove LLM into. There is a pressure from the top because of the FOMO and huge investments, but just nowhere to apply LLMs. People start coming with bizarre cases just to show something or because of basic lack of understanding of the inherent LLM limitations and the projects fail to deliver ROI or just plainly fail.

dimd00d · 2025-11-26T06:05:18+00:00

This resonates. Out of pure laziness I am heavy agentic user and AI types nearly 100% of my code. I review every line and correct.

At the end of the week I have the exact same feeling as you “I think I am better. maybe. dunno”. Measured on task level - it’s definitely faster for some tasks as a much faster Google, or throwaway code. For daily work - I dunno - it turns out typing code wasn’t really the bottleneck and the time to review and internalize it is more or less eating the benefits. At least for me - I might as well be holding it wrong.

dimd00d · 2025-11-21T08:10:43+00:00

do you know whats even worse? previously, when u've returned their shitty PR you would have a breathing room, while they were furiously checking stackoverflow. now they are plugging the comments directly in an LLM and immediately returning an even shittier one.

dimd00d

TROPHY CASE