whisper: There is no linter.

There is no unsupervised robotaxi service in Austin and there won't be, for years, if ever. Just like the way "FSD" is not fully self driving and likely never will be.

Saying the "boomers ruined everything" is not sophisticated, we can't move forward from a blame game, we have to diagnose the actions and actors that implemented them, but of course this is much more challenging.

Ancedotally, I know plenty of poor boomers. Have you seen who works at a Dollar Tree lately?

The popular dialogue that boomer=rich and greedy, millennial=poor and exploited is not productive, it's a fabricated generational war that distracts us from the real issues.

I understand the desire to find an entity or group of people to blame, but they were acting in their own self interest at a peak time, they didn't know the party would be over soon, for many of them, it still isn't.

In my case, I have CS degree and work as SWE but I probably would've been fine with just my Data Structures & Algos course as I already had programming experience.

Are computational theory, circuits 101, discrete math, logic 101, etc necessary for being a good SWE? Probably not, but they do probably expand your mind a bit.

1. Punch cards -> Assembly languages

2. Assembly languages -> Compiled languages

3. Compiled languages -> Interpreted languages

4. Interpreted languages -> Agentic LLM prompting

I've tried the latest and greatest agentic CLI and toolings with the public SOTA models.

I think this is a productivity jump equivalent to maybe punch cards -> compiled languages, and that's it. Something like a 40% increase, but nowhere close to exponential.

And while you could make the argument that these forms of media were superior to TikTok, I’d also argue that this is mostly just taste.

While we have closed ecosystems now, they’re much easier to make and share content to than the web of the past. It’s much easier to get distribution and go viral. There’s also a well trodden path to monetization so that if you craft great content people love, you can make a living from it.

Yeah quirky designs, guestbooks, affiliate badges, page counters, all that stuff. I miss it. But only ever a very small fraction of society was going to be able to make and consume that stuff.

This new internet is much more accessible and it occasionally produces diamonds of culture, you just have to know where to look.

So no, I don’t think any amount of decentralized protocols or tooling or any technology really can change this. I think this trend is set and will continue, and I’ve had to learn to be more open minded to how I perceive internet content.

No one is going to make personal websites or change their behavior in a major way.

Look, you can still sign up for free web hosting and make an HTML page and tell your friends. There are still people that do this. But it’s naturally eclipsed by these other methods of much easier content sharing.

The point is the content itself, not the packaging. Just get over the shape of the packaging and enjoy.

This blog post reeks of “you can just do things” type of engineering. This is the quality of engineering I would expect from “TPOT” (that part of Twitter) where people talk about working 12 hour days. It’s cause they’re working 12 hours on bullshit like this.

Building some sweet custom codec or binary transportation algorithm was barely cute in like 1989. It definitely ain’t cute now.

How many of these AI and “agentic” companies are just misled engineers thinking they are cracked and writing needlessly complex solutions to problems that dont even exist?

Just burn it all down. Let it pop already.

"Bring me the rats."

The amount of intelligence that you can display within a single prompt, the riddles, the puzzles, they've all been solved or are mostly trivial to reasoners.

Now you have to drive a model for a few days to really get a decent understanding of how good it really is. In my experience, while Sonnet/Opus may not have always been leading on benchmarks, they have always *felt* the best to me, but it's hard to put into words why exactly I feel that way, but I can just feel it.

The way you can just feel when someone you're having a conversation with is deeply understanding you, somewhat understanding you, or maybe not understanding at all. But you don't have a quantifiable metric for this.

This is a strange, weird territory, and I don't know the path forward. We know we're definitely not at AGI.

And we know if you use these models for long-horizon tasks they fail at some point and just go off the rails.

I've tried using Codex with max reasoning for doing PRs and gotten laughable results too many times, but Codex with Max reasoning is apparently near-SOTA on code. And to be fair, Claude Code/Opus is also sometimes equally as bad at doing these types of "implement idea in big codebase, make changes too many files, still pass tests" type of tasks.

Is the solution that we start to evaluate LLMs on more long-horizon tasks? I think to some degree this was the spirit of SWE Verified right? But even that is being saturated now.

Then I found out he was a fraud that had no academic connection to MIT other than working there as an IC.

A) In 5 years no real improvement, AI bubble pops, most of us are laid off. B) In 5 years near—AGI replaces most software engineers, most of us are laid off.

Woohoo. Lose-lose scenario! No matter how you imagine this AI bubble playing out, the musics going to stop eventually.

Kids music toys are often just purely toys tap a button, make a sound... But the skill ceiling could be so much higher, offering the ability to learn and express themselves more. Awesome work.

I'm honestly skeptical this will work at all, the FOV of most webcams is so small that it can barely capture the shoulder of someone sitting beside me, let alone their eyes.

Then what you're basically looking for is callibration from the eye position / angle to the screen rectangle. You want to shoot a ray from each eye and see if they intersect with the laptop's screen.

This is challenging because most webcams are pretty low resolution, so each eyeball will probably be like ~20px. From these 20px, you need to estimate the eyeball->screen ray. And of course this varies with the screen size.

TLDR: Decent idea, but should've done some napkin math and or quick bounds checking first. Maybe a $5 privacy protector is better.

Here's an idea:

Maybe start by seeing if you can train a primary user gaze tracker first, how well you can get it with modeling and then calibration. Then once you've solved that problem, you can use that as your upper bound of expected performance, and transform the problem to detecting the gaze of people nearby instead of the primary user.

We’ve had GPT2 since 2019, almost 6 years now. Even then, OpenAI was claiming it was too dangerous to release or whatever.

It’s been 6 years since the path started. We’ve gone from hundreds of thousands -> millions -> billions -> tens of billions -> now possibly trillions in infrastructure cost.

But the value created from it has not been proportional along the way. It’s lagging behind by a few orders of magnitude.

The biggest value add of AI is that it can now help software engineers write some greenfield code +40% faster, and help people save 30 seconds on a Google search -> reading a website.

This is valuable, but it’s not transformational.

The value returned has to be a lot higher than that to justify these astronomical infrastructure costs, and I think people are realizing that they’re not materializing and don’t see a path to them materializing.