
We are all trying to get things done and it's a mess 💎🥁💫 🌊🌱supporting good collaboration @letsgohq and exploring aliveness for me and us
London
Joined May 2014
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At @SD_LDF I talked about how we can create momentum in collaborative projects - and if you liked the taste of it then my TEDx is a good compliment on the dynamics of groups and how we can have better conversations #sdff2019 #sdff youtu.be/rf3imYVetWo?t=21
Rich Watkins 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.
Ok so for an LLM tokens ARE time - the substrate upon which things happen - whereas time is not really a dimension that matters, apart from that tokens are processed IN time. Right?
Rich Watkins retweeted
RIP to Annie Dillard, whose work frequently left me unable to speak sensibly for several minutes after reading it. This essay, This Is The Life, was my entry point to her work
Rich Watkins retweeted
if you haven't read this essay, you really should.
one of my all time favorites
Rich Watkins retweeted
Best plural forms ranked:
1) internal (tours de force, culs-de-sac)
2) ending in -i (magi)
3) is to es (oases)
4) suppletive (people)
5) vowel changes (geese)
6) f to ves (thieves)
7) adding en (oxen)
8) no change (moose)
9) adding es, ies (boxes, babies)
10) adding s
and though the questions
that have assailed us all day
remain—not a single
answer has been found—
walking out now
into the silence and the light
under the trees,
and through the fields,
feels like one.
(mary oliver - last lines from 'first snow')
New post! Alignment doesn't just relate to a model's properties, but also the systems and institutions under which it operates. As we enter an increasingly multi-agent world, better harnesses, protocols, and mechanism design will be critical for safety. 🐜 blog.cosmos-institute.org/p/…
Rich Watkins retweeted
Replying to @nosilverv
More importantly, he said:
“One should be an enigma not just to others but to oneself too. I study myself. When I’m tired of that I light a cigar to pass the time, and think: God only knows what the good Lord really meant with me, or what He meant to make of me.”
Chatted to @thelazyguru for his podcast and here it is - I share some of the thinkers that have shaped how I think: Ludwig Wittgenstein, Martin Heidegger, Virginia Satir, Donna Haraway, David Bohm podcasts.apple.com/gb/podcas…
Rich Watkins retweeted
BBC literally built the greatest sound library on the internet.
It is called BBC Sound Effects, and it gives you access to more than 30,000 recordings from around the world.
Just search any word, and it instantly finds matching sounds.
You can filter them by category, duration, and even the continent where the sound was recorded.
Every sound can be previewed inside your browser, downloaded, or added to the built-in mixer so you can layer multiple recordings together.
And the archive gets insanely specific.
You can find creaking ships, old typewriters, jungle ambience, distant church congregations, and even someone vigorously washing their hands.
There is a good chance a BBC engineer recorded the exact sound you need decades before you were born.
sound-effects.bbcrewind.co.u…
Most of the words we use about organisational culture – High Performance, Collaborative, Innovative – feel flat and meaningless. As if they've been photocopied too many times. Let's see what moral philosopher Alisdair MacIntyre might say about that 🧵
If your culture work is chosen, institutional, agreed and declared, then you have designed it – and that won’t keep a place alive.
A living culture is inherited, practice based, argued and lived.
And you don’t design something that is alive. You tend it.
This is my work @letsgohw - full article: goodcontact.substack.com/p/t… and thanks to @meekaale for tweeting unendingly about AM for years before i picked it up.

















