
iOS · macOS · visionOS · Server-Side Swift engineer. AI-native Apple apps + open-source #OmniFocus MCP server.
Singapore
Joined March 2010
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Brent Deverman 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.
Brent Deverman retweeted
Amazon banning agents is the first opportunity I've seen since Amazon was founded for a startup to create an Amazon competitor. People will want agents to buy stuff for them. It will be one of the main use cases. And they won't want to use some Amazon-supplied agent to do it.
Brent Deverman retweeted
Google: “[Swift] has matured into a viable systems and cloud language, pairing Rust-like data-race safety with predictable, reference-counted performance.” Announcing their Swift-based cloud SDK for backend services: cloud.google.com/blog/topics…
Brent Deverman retweeted
A huge amount of work has led up to this! So excited to have this out!
10 years ago today Vapor 1.0 was released. Today we're super excited to release the first Vapor 5 Beta, a complete rewrite of the framework, built for modern Swift. More details are on the blog:
blog.vapor.codes/posts/vapor…
Brent Deverman retweeted
Swift 6.4 is out! 🎉
This release brings deeper interoperability, stronger platform support, and easier everyday code.
swift.org/blog/swift-6.4-rel…
Highlights in this thread 🧵
Brent Deverman retweeted
Shop is the first of our apps to complete the move back to native. The team rebuilt it in Swift and Kotlin in just 12 weeks.
It now launches 23% faster on iOS and 50% faster on Android, with a 10x lower crash rate and a 109 MB smaller Android build. We expect those numbers to keep improving.
shopify.engineering/shop-app…
Brent Deverman retweeted
Lots of cross-platform Swift news this month. ElementaryUI brings Swift to the web, SwiftTUI brings state and animations to the terminal, and Swift on Windows keeps getting better. Read more in our latest digest: swift.org/blog/whats-new-in-…
Brent Deverman retweeted
At last: a unified home for Swift documentation, pulling together the language reference, core libraries and tooling, and platform specifics into a single central home, no matter what you're building! Check it out and give us feedback: docs.swift.org
Brent Deverman retweeted
Bought nerds.sg.
Planning on making my NERDS events a regular thing.
If you're in Singapore and are a founder, entrepreneur, technologist, researcher, builder, open-source contributor, or simply obsessed with your craft, send me your info.
Brent Deverman retweeted
A busy summer for Swift continues. ☀️
In July:
• Task Stealers land in Swift Concurrency’s runtime.
• SwiftPM gets a package registry reference implementation.
• A talk about explicit ownership at PLDI 2026.
Read more: swift.org/blog/whats-new-in-…
Brent Deverman retweeted
June was a big month for Swift: previews of Swift 6.4, Swift Package Index joining Apple, and a community project that brought Swift to a 1977 Apple II. Read more in our latest digest: swift.org/blog/whats-new-in-…
Brent Deverman retweeted
For web developers on Mac, good news! Safari is adding an MCP server so your agent can easily test, preview, and debug web content with @webkit. For example, @claude can now see what it's building without needing Playwright or other tools. More here: webkit.org/blog/18136/introd…
Brent Deverman retweeted
Swift 6.3.3 is out now! 🔩 This maintenance release improves stability in the Swift REPL, concurrency, and key paths. More here: forums.swift.org/t/announcin…
Brent Deverman retweeted
Polymarket uses Swift on Android!
linkedin.com/posts/theleftbi…
Brent Deverman retweeted
I stole this idea and now use it with every single employee.
It’s the best illustration I’ve seen of teaching someone to be high agency.
It says there are 5 levels of work:
Level 1: “There is a problem.”
Level 2: “There is a problem, and I’ve found some causes.”
Level 3: “Here’s the problem, here are some possible causes, and here are some possible solutions.”
Level 4: “Here’s the problem, here’s what I think caused it, here are some possible solutions, and here’s the one I think we should pick.”
Level 5: “I identified a problem, figured out what caused it, researched how to fix it, and I fixed it. Just wanted to keep you in the loop.”
Using this framework, here’s what I say to every new employee…
You will live at Level 4 from Day 1 and as we build trust you will rise to Level 5.
Being high agency doesn’t just mean tackling problems in this way. It means your entire way of working should be oriented to being a Level 4+ employee.
Plz feel free to steal it as well.
And ty @stephsmithio for the framework!
Brent Deverman retweeted
Swift Package Index has become an essential part of the Swift ecosystem, and joining Apple strengthens it as it continues its mission. Learn more: swift.org/blog/swift-package…
















