
Staff web platform engineer. One app, several products at Apple Business. Toolmaker, motorcyclist, father, hunter, American, husband to @jeeyunit
San Jose, California
Joined July 2006
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Reid Burke retweeted
Replying to @finkd
Congrats to the team! Amazing to run a model of Muse Spark Open's caliber and scale this efficiently, right from your desk. Mac Studio keeps pushing the boundaries of on-device AI!
Reid Burke retweeted
Dusting off this tweet from April because this gap in shared understanding of LLM capability is *widening*. It's now less "two groups of people speaking past each other" and more a sharp funnel.
- Napkin math somewhere around 6B people (~75% of the population) have barely come in contact with LLMs at all.
- Around 1-2B (~20%) are casual and infrequent users of free-tier ChatGPT-like products. This group sees derpy chatbots and treats them a bit like a better Google search, a writing aid, or etc. Maybe an agent tries to book you a flight. I have non-tech friends who (reasonably, imo) say they have not much use for it at all. Even many professionals outside of math&code are in this tier. For example, execs and many other functions spend a lot of their time talking to other people, so while they understand what is happening intellectually, it is still second-hand and a bit abstract.
- Now we get to professional use of frontier-grade LLMs in math&code. Somewhere around 20M people (0.2%) see first-hand that large, complex projects that used to take them weeks/months can now be completed by agents with a prompt. Building apps, copying apps, translating apps, decompiling apps from binaries... This has all happened very quickly and recently - less than 1 year ago, I was writing code manually by hand, typing memorized computer code commands into a code editor character by character, occasionally pressing Tab to autocomplete a little chunk of code.
- And finally we get to the ~5,000 people (~0.00006%) with access to frontier-grade systems internally. The external world has seen the preview. It looks like swarms of thousands of agents collaborating over weeks on software mega projects: minting zero days, running cyber attacks and defenses at machine speeds, discovering new science, advancing the frontier of mathematics. Things that would have taken top professionals in the industry years of work. Meanwhile, human review and comprehension are starting to fall behind. For example, people are still involved in the "archeology" of the OpenAI-HF incident from many months ago. Mathematicians may be poring over the 722 manuscripts on frontier mathematics for a while.
The funnel is driven by a combination of factors:
1. The impact scales with ambition, problem size, and horizon. A question with a paragraph answer barely stresses the system. You need a reservoir of big, difficult problems that you really care about. This aspect drives the consumer / professional dimension of the funnel.
2. The jaggedness of the system (which I have written about a lot separately). Capability peaks in domains that are digital, verifiable and economically valuable. This is because LLM capability emerges from reinforcement learning on verifiable rewards on a curated environment mixture driven by revenue potential. This aspect primarily drives the area (e.g. math&code) dimension of the funnel.
3. Access. Free-tier, paid-tier, internal.
So this is the weirdness of the moment. The general public has mostly not interacted with these systems. When they have, it looks like a derpy chatbot. The majority of professionals still see only a modest uplift. And a small sliver of professionals are experiencing the vertigo of the curve going vertical. And it is all happening at the same time.
Judging by my tl there is a growing gap in understanding of AI capability.
The first issue I think is around recency and tier of use. I think a lot of people tried the free tier of ChatGPT somewhere last year and allowed it to inform their views on AI a little too much. This is a group of reactions laughing at various quirks of the models, hallucinations, etc. Yes I also saw the viral videos of OpenAI's Advanced Voice mode fumbling simple queries like "should I drive or walk to the carwash". The thing is that these free and old/deprecated models don't reflect the capability in the latest round of state of the art agentic models of this year, especially OpenAI Codex and Claude Code.
But that brings me to the second issue. Even if people paid $200/month to use the state of the art models, a lot of the capabilities are relatively "peaky" in highly technical areas. Typical queries around search, writing, advice, etc. are *not* the domain that has made the most noticeable and dramatic strides in capability. Partly, this is due to the technical details of reinforcement learning and its use of verifiable rewards. But partly, it's also because these use cases are not sufficiently prioritized by the companies in their hillclimbing because they don't lead to as much $$$ value. The goldmines are elsewhere, and the focus comes along.
So that brings me to the second group of people, who *both* 1) pay for and use the state of the art frontier agentic models (OpenAI Codex / Claude Code) and 2) do so professionally in technical domains like programming, math and research. This group of people is subject to the highest amount of "AI Psychosis" because the recent improvements in these domains as of this year have been nothing short of staggering. When you hand a computer terminal to one of these models, you can now watch them melt programming problems that you'd normally expect to take days/weeks of work. It's this second group of people that assigns a much greater gravity to the capabilities, their slope, and various cyber-related repercussions.
TLDR the people in these two groups are speaking past each other. It really is simultaneously the case that OpenAI's free and I think slightly orphaned (?) "Advanced Voice Mode" will fumble the dumbest questions in your Instagram's reels and *at the same time*, OpenAI's highest-tier and paid Codex model will go off for 1 hour to coherently restructure an entire code base, or find and exploit vulnerabilities in computer systems. This part really works and has made dramatic strides because 2 properties: 1) these domains offer explicit reward functions that are verifiable meaning they are easily amenable to reinforcement learning training (e.g. unit tests passed yes or no, in contrast to writing, which is much harder to explicitly judge), but also 2) they are a lot more valuable in b2b settings, meaning that the biggest fraction of the team is focused on improving them. So here we are.
Reid Burke retweeted
I, along with the rest of the Deno company, am joining Cloudflare!
I'm motivated by abstractions that give leverage at scale. The Cloudflare workers programming model is a hermetic computing abstraction that truly embodies the old Sun Microsystems tagline "The Network Is the Computer". The programming abstractions that Kenton designed really force scalability. If you squint your eyes you might even conceive of it as a distributed high-level operating system.
The only major problem with this distributed operating system is that practically people only use it inside of Cloudflare. Cloudflare is an amazing service for nearly all applications - but there are many situations when you might need it to run elsewhere.
I want to solve this problem and make the Workers programming model the default way you write server-side application code.
The time is ripe for new abstractions too - what software we run and how we run it are changing quickly with AI. The number of agents is exploding and I don't think they all need a Linux VM. A much more lightweight Durable Object would suffice for many applications. I'm super keen to talk to people who want to self-host agents at scale on DOs - msg me!
everyone spent ten years learning to code and it turns out the terminal skill was english composition. the machine will do anything you tell it. the only thing left between you and what you want is whether you can form a clear thought and put it into words
Reid Burke retweeted
An uncomfortable truth for a lot of people is that a lot of the most successful people in any industry are wicked smart. We apply stereotypes based on the loudest people, but its not representative of norms. Most are crazy smart and got to where they are because of it.
I grew up in LA, one of my parents was a TV producer, my wife was an actor, many friends "in the industry." I've been constantly surrounded by it, and some of the stupidest seeming people (cause its their bit) are actually insanely smart and strategic in private. It sometimes is just beneficial for various reasons to... not show that side of you.
My favorite anecdote was when a friend (a model) was dating a phD in physics and a very rude person made some off the cuff degrading comment to model friend about it without realizing model friend has their own phD in math lol. You wouldn't know from their instagram though!
For the quoted video, I don't know Ben Affleck. I don't know how deep his knowledge goes. He's almost certainly not going to be more knowledgable than someone who professionally does this area of work full time, but he also to me on the surface sounds like someone who knows a LOT more than the average person and possibly even the average software engineer (on this topic).
Anyways, this applies to tech too. I see it constantly.
Ben Affleck reveals he writes Python, understands convolutional neural networks, worked extensively with GPUs, and used his celebrity status to get private looks at Google and OpenAI’s video models
“I’ve always been kind of into computers since I was young. Then, when film started to move from analog film to digital, I became more interested in that aspect of it. The visual-effects workflow for many years has included machine learning, so I can write pretty shitty Python scripts and stuff like that.
“With convolutional neural networks, which were the precursors to what the transformer can do, which is much more computation simultaneously, you would do things like look at what’s called a tensor. That’s the numerical translation of a visual image in numbers, like the batch number, the frame number and the red, green and blue values of each pixel in each frame. It’s just that simple. That numeric is called a tensor.
“You’d use a convolutional neural network to identify patterns that reveal what’s called edge detection or feature extraction, which is identifying patterns well enough to know, this is where the window ledge is, so we can more easily take the green-screen image out and replace it with something.
“That was familiar to me early on because, prior to Artists Equity, I had a small visual-effects company. I’ve worked with GPUs a lot too. The visual-effects guys said, ‘Hey, you should see. There are a couple: Google and this other company, OpenAI, are doing really interesting stuff with transformers in video.’
“I’ve learned that I can actually just call up and go, ‘Hey, it’s Ben Affleck. Can I come see what you’re doing?’ Sometimes people say yes, to my astonishment.”
What makes a cool logo?
A cool logo is one which does not change.
What sorts of logos change?
Logos don't change: people change them.
Finally.
I’ve been building with Pi for months, but this is a big help. I work with a lot of folks on Claude Code.
I’m thankful for America’s hunting heritage and for access to local federal lands to hunt waterfowl in Silicon Valley.
I hope to see more people get involved with conservation and stewardship of our wildlife.
“Our forefathers looked with awe on our vast prairies, towering mountains, serene deserts, coastal paradises, and rushing rivers. That same awe motivates millions of Americans to invest billions of dollars and countless hours into stewarding our land and conserving our wildlife.”
whitehouse.gov/presidential-…
Reid Burke retweeted
photographs of the World Trade Center in 1976 by Balthazar Korab, who was commissioned by the architectural firm Yamasaki Associates to document the entire design and construction process.
Reid Burke retweeted
"Stop crying. I have to get these people out safely. If something should happen to me, I want you to know I've never been happier. You made my life."
-Rick Rescorla (saved all but 6 of his 2700 employees at Morgan Stanley on 9/11 only to perish himself)
en.m.wikipedia.org/wiki/Rick…
Reid Burke retweeted
The haunting sound of hundreds of PASS (Personal Alert Safety System) devices chirping in the rubble after the towers fell. Each one represents a fallen hero. I can't get that sound out of my head.
Patriot Day ceremony with @SJFD happening this morning from 10:45 am to 12 noon at Fire Station 1 (255 N. Market St.)
“The San José Fire Department is hosting a commemorative ceremony to honor the 25th anniversary of Patriot Day on Friday, September 11, 2026. Join us as we honor the lives lost on September 11, 2001, and recognize the courage, sacrifice, and service of first responders and community members. This free public event is open to everyone.”
sanjoseca.gov/Home/Component…
Never forget. I was 12 and came home from school to see this on TV.
Following @25YearsAgoLive today.
A giant fireball has consumed the World Trade Center complex.
United Flight 175, a fully-fueled Boeing 767, has struck the building deliberately.
Parts of the engine flew out the east side of the building and have landed six blocks away.
The tower physically shifted at least five feet.
Hundreds of people must be dead - and hundreds of millions watched their deaths on live TV.
This is not an accident.
"The developer points Helix at a screen. Helix reads the React Native code and proposes a sequence of checkpoints (small, ordered slices of the work) that can be reviewed in minutes. Then, checkpoint by checkpoint, it builds: each one must prove its behavior with tests, match the running app in a visual review, survive two adversarial code reviewers, and get a human’s nod before it’s committed and the next one starts."





























