vibe-coding | co-founder https://xitter.cf/t.co/xuj1iGsw9s | director @ Monitor Deloitte | founder @ IoT & health startups in China | EE @Stanford

Earth
Joined March 2009
Nvidia: Silicon is Forever. ❤️
Chinese bride gifts her partner a flagship GPU at wedding — he breaks down in tears She handed him an ASUS ROG Astral RTX 5090 that costs around $12,000
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Flying cars, finally.
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Steven Pu 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.
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Was there a Claude Code update that stops auto mode from editing any local permission settings? This is crazy, the workflow gets stopped constantly. Why is auto mode being crippled?
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Steven Pu retweeted
I was talking with a friend today about how tough the job market is for tech, and how even if you do have a job, it's so unstable because things are changing so fast. I told them that even though I technically have my own business and I'm supposed to have "visibility" into how I'm doing, do I really? No. I just assume the business will change every few months and I don't get too fussed when it does, and trust me it has been changing quite consistently This is why it's obvious to me that, more than a set of skills or a knowledge base, you really have to teach your kids how to adapt to new situations, quickly figure out opportunities, and take risks
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We’ve lost an icon. Margaret Hamilton, a computer science pioneer best known for her work at MIT leading development of the flight software for the Apollo missions to the moon, has died at 90. Read about her legacy via MIT News: news.mit.edu/2026/margaret-h…
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Apple says you need a Mac to build iPhone apps. Today I built one on Omarchy Linux, submitted it to the App Store, installed it on my iPhone over USB, and stopped it at a breakpoint in the debugger. No Mac anywhere. It's all open source: github.com/joshuaswarren/oma…
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Steven Pu retweeted
This is the doom I predicted a few days ago, coming for Photoshop. A clean-room open-source reimplementation. No prizes for guessing that they decompiled Photoshop to source code, processed that to some kind of non-code specification language, then fed the spec to an LLM with an instruction to generate Rust. Adobe just got nuked. And closed source is dead, dead, dead. github.com/storytold/photocr…
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Let me tell you how I delayed WinXP SP2 for a month. My software (BlackICE) was on the list of software that had to work. When they made major changes to the kernel network stack, my software broke. They grabbed their reverse engineers to figure out why. What they discovered was that my software doing something evil, patching the kernel's network stack when our software was loaded. That's tricky on a multi-CPU system with warring instruction/data caches. We wrote a patent on how to do it reliably without crashing the system. We searched through the kernel to find the location we needed to patch, looking for a certain pattern of bytes. They changed the network stack so that thing we were patching no longer existed. So to make our software work, the inserted that pattern back into the kernel. As packets arrived, the new function would jump to that pattern, and then after, jump right back. This way, we could find the pattern and patch it -- and thereby patch the intended function. Some Microsoft lawyers wanted to sue us for violating the software license agreement, which forbids reverse engineering, which we had to do in order to patch the kernel at runtime. Cooler heads prevailed. The point is our software did an ugly hack in order to work, and then Microsoft did an even crazier, uglier hack so that we'd keep working. For years after, when meeting Microsoft engineers at conferences, they'd love to yell at me. When Vista came along, they added signing of kernel models, putting an end to such nonsense, but also providing a real documented API we could use.
Microsoft once discovered SimCity was crashing on Windows 95 because SimCity had a memory bug. Instead of saying “not our problem,” Microsoft added a compatibility workaround just for SimCity. Because users don’t care whose bug it is. They care that software that worked yesterday still works today. Backwards compatibility is a feature.
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Going back to Claude Code, it is the superior product. Here are the measures I've taken, 1. Analyzed all instances where bio safeguards were triggered, mapped them to Claude's published dual-use boundaries 2. Enumerated the trigger topics, and all sources in which these triggers might occur - e.g., code test data, external data (lit search), generated prose 3. Encoded the boundaries into claude.md to never generate test data in or adjacent to these topics, and to spin up non-safeguarded model as subagents to read any data that might contain them & hand back reports scrubbed of any science 4. Switching production model APIs to OpenAI's models 5. Wait for Claude's LSVP program to open up to applications - long term solution
Claude's bio safeguards keep interrupting my workflow, as I'm building AI apps for microbiologist labs. It also started to interrupt workflows due to "reasoning_extraction", so apparently I cannot read model outputs anymore either? Tried Codex with Sol 6.1. First, got hit with the 272k context limit, how does anyone work with this? Then, asked it to migrate my Claude skills, a simple op that should've taken 5 minutes instead took 30, triggering an auto-compaction, before I stopped it. Apparently it dug itself into a hole, continuously building tasks, test cases, installers, rollbacks for the installers (wtf?!), etc. So, Claude Code is smart, but I am not allowed to use it. Codex is dumb as a brick. Can we have a third choice please?
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This system is working pretty well so far after ~5 hours of usage. Opus 5.5 carefully avoids anything that might trigger a safeguard, automatically instantiating a subagent to read potentially sensitive files, and hand back an analysis scrubbed of science.
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Claude's bio safeguards keep interrupting my workflow, as I'm building AI apps for microbiologist labs. It also started to interrupt workflows due to "reasoning_extraction", so apparently I cannot read model outputs anymore either? Tried Codex with Sol 6.1. First, got hit with the 272k context limit, how does anyone work with this? Then, asked it to migrate my Claude skills, a simple op that should've taken 5 minutes instead took 30, triggering an auto-compaction, before I stopped it. Apparently it dug itself into a hole, continuously building tasks, test cases, installers, rollbacks for the installers (wtf?!), etc. So, Claude Code is smart, but I am not allowed to use it. Codex is dumb as a brick. Can we have a third choice please?
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Thanks to Opus 5.5, I now work 16 hour days instead of 10. The better these models get, the more opportunity cost anxiety they trigger: I could be doing so much more right now instead of wasting time on XYZ!
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Opus 5.5 is on "safeguard steroids", even randomly contrived bio-related test code & prompts get stopped mid-flight. So looks like only Anthropic gets to use Anthropic models for bio and no one else eh...
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Good: Opus 5.5 finds A LOT of bugs. Bad: Opus 5.5 finds A LOT of bugs.
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Bonds: I SET THE PACE.
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Opus 5.5 obeys rules really well. I created a lot of tools to help manage the coding process, along with skills and claude.md instructions. I think 4.8 ignores half of it. So much of 5.5's quality improvement comes from it actually using the provided tools & instructions. 🥳
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