Kiro

There's obviously no such correlation.

Not sure how you reached that conclusion and most people do not make OSes. A normal backlog at a standard company is not comparable.

Your edit is even more peculiar. Writing a C compiler in Rust? Come on. I'm obviously talking about normal grunt work. And what are you even using as a benchmark? It's not 100x compared to what?

> Now: Auto-memory

Not Claude Code but I just had a task where it started referring another conversation that was complete nonsense and throwaway. I absolutely don't want things to get added to some memory behind my back.

A big reason I use LLMs is because I can try out wild ideas and then just throw it away. I don't want those to pollute the context.

Is 100x even controversial anymore? Anyone can do it by just throwing the whole backlog at AI and let it go crazy. What's the bottleneck? You don't need to babysit LLMs anymore. The problem is that you can only keep up with so much, but it's obvious that a lot of people and companies don't care about that.

What do you hope to achieve here? Posting absurd and ridiculous things and then continuing like if someone would take you seriously after that. Keep going I guess.

The same guy who also happens to be the creator of Rails.

Bad advice considering the success Omarchy has had in marketing it. Whatever they're doing other distros should take note.

Most people played MUDs for the grind. Levels and loot. They care about the story as much as you care about it in Path of Exile.

Pointless nitpicking that completely missed my point. Software developers are not the hardest to replace, so your presumption that everything else should be easier is wrong.

Code is the killer app for LLMs so software developers are the easiest to replace.

Yes, a lot of commenters here (and the author) outing themselves.

Yes, it's demoralizing for a human. Which is why it's good for an LLM. They have no problem implementing these soul crushing workarounds.

I agree. These are classic problems where LLMs really shine. I would be very surprised if GPT-5.6 couldn't fix them.

Attention economy is a red herring. HN shows that you don't need to do much to be more addictive than TikTok. It's human nature.

I really don't understand what Andrew Kelly hopes to achieve here. Even the non-programmers at r/programming who usually piles on any type of anti-AI posts called it out.

I'm trying to not let this affect my thoughts about Zig as a language but it's hard.

Nice opinion but it's clearly a spectrum and not binary. Is assembling machine-made components by hand to make a watch hand-made?

You thinking this is an epiphany makes me feel you severely overlook the impact AI already has on the world, affecting everyone. This seems very minor in comparison.

For people thinking it detected the decoy text. It did not. It was the text I entered myself. Here are the thinking steps:

  Inspected video metadata, extracted frames, and analyzed content
  Detected and analyzed periodicity in stereogram image data
  Blurred, downsampled, and analyzed image frames
  Computed frame pixel shifts and cross-correlation
  Checked OpenCV installation, optimized and analyzed optical flow processing
  Analyzed motion for text
  Estimated vertical displacement and processed image flow
  Refined text extraction
  Processed optical flow and analyzed image

The text I had written in the message. Just some random stuff.

The chat contains the video, which may reveal som meta data about me. But the shared chat also doesn't include any of the images in the thinking steps that my original chat has, where you can see the different maps it generated. Pretty cool seeing it go from noise to patterns to the final image which clearly shows the text as black on white.

GPT-5.6 had no problem seeing the text when giving it a video recording of it.

"No problem" as in using temporal analysis with optical flow and vertical-displacement maps to estimate how the image moved, and combine those into a motion map with increased contrast to see the text. I didn't give it any instructions though, just asked it what it said.

Ask it to generate a completely bananas game idea and it will easily do it. Prototyping any type of game with simple graphics has been solved since many generations of models back. Claiming it's because it has that game in its training data is nonsense.

Won't using it eat up the whole quota immediately forcing you to pay API prices anyway?

Why are you directing the question at me? Obnoxious behavior, and your initial "gotcha" is just nonsense on a similar level as "why don't AI companies just clone all SaaS if the models are so good".

Picking 2012 feels arbitrary to fit the author's thesis and age. I don't see much difference between 2012 and now. Late 90s and now feel like two different worlds though.

They have consistently been proven right. The only thing failing has been the plateau claimers. If anything, it has improved much faster than the optimistic predictions.

LLM versioning is entirely feelings driven. The ideal versioning is probably just names.

I think this kind of "hard work" is a perfect fit for AI, and something where the complexity for a human is incorrectly extrapolated to LLMs.

Tirelessly wading through heaps of specifications and documentation with very clear goal definitions is hard for a human but easy for an AI. Meanwhile, taking UX and edge cases into account in a business application is easy for a human but hard for an AI.

The OpenAI moderation endpoint is free and it doesn't count toward the usage limit.

Not the gotcha you think it is considering how common fake loaders are in all application development. They're inserted for a reason, but that's a different topic. We're talking about pure animations here, not loading screens.