Study work with AI + robots. @MITSloan PhD, @Ucsb Assc Prof, @Stanford fellow, @tedtalks, @skillbenchinc cofounder, CEO Book: theskillcodebook.com
Santa Barbara, CA
- Tweets 9,004
- Following 246
- Followers 4,784
- Likes 14,361
Pinned Tweet
I'm so grateful and exited to share that my book will be published on June 11th!
It's called "The Skill Code: How to Save Human Ability in an Age of Intelligent Machines"
Available for preorder now, here's a bit of the story:
wildworldofwork.org/p/big-in…
12
34
214
71,148
Matt Beane retweeted
1/ Exciting news. The @uscensusbureau has started asking US firms whether *their employees* are using generative AI for work-related tasks, not just overall business AI usage.
We'll get data every 2 weeks.
5
15
96
13,049
What a moment - and honor. And a new fire to drive forward.
I started the journey towards @skillbenchinc in 2010 when I began my PhD @MITSloan, asking: "how can we boost productivity and human skill development as we deploy intelligent automation?"
Today, from @reidhoffman:
🧵
1/ We’ve just released our inaugural Emergent list in partnership with @NewcomerMedia. In it, we give the mic to founders: which seed-stage companies are the most exciting to them right now?
You can find the full list here. Congratulations to all of the founders! felicis.link/IlBBJvB
3
3
15
822
I went on full academic leave to pursue SkillBench on July 1. Many thanks to my incredible colleagues and dean @ucsbtm for allowing me to take this leap. We are building - and will soon ship to the world - the system I talked about in the last chapter of that book.
1
3
65
@reidhoffman and I connected over all this about TEN years ago - and he's been an ardent supporter ever since. So his nod here is a giant honor and a shot in the arm.
More from us at @skillbenchinc soon. But for now, thank you Reid, @felicis, and @NewcomerMedia for this honor.
1
2
74
Matt Beane retweeted
Very intriguing report from METR, who are very serious people. Tldr: with full access inside of Anthropic, they see evidence of AI speeding up the increase in AI capabilities and do not see reasons this might get bottlenecked in the near term.
Since August, a team within METR has worked with internal Anthropic information to assess whether AI itself is accelerating AI development.
We are now publishing a report summarizing the results of this risk assessment.
1
2
21
1,436
Matt Beane retweeted
Today, we’re releasing a dataset of >2k LLM conversations with real voters about the 2026 Midterms. We wanted to know how the ~millions of American who use AI models to talk about elections actually prompt them. Our hope is to use this data to build better evals for LLMs, to prepare for a world where most voters use AI to think through election decisions.
We observe that:
- People mostly want basic information
- Multi-turn chats follow predictable patterns
- Models differ widely in whether they’ll recommend candidates
8
40
268
45,264
Matt Beane retweeted
(Very rough estimate) After 70 years, machines have just gotten cheaper than humans on $/FLOP.
Nothing in these analyses were about AI (just hardware prices). It's a pretty striking coincidence if this cost crossover hits just as we're reaching human-level AGI.
---
Some details on the back-of-envelope estimates (all adjusted to 2026 dollars):
Human cost per flop: Modern US labor costs ~$30/hr and global average wage (harder to estimate) is ~$10/hr. Subsistence is the bare cost of keeping a worker alive, ~$0.75/hour. @jkcarlsmith's great analysis gives ~1e15 FLOP/s for the human brain (NB wide range of 1e13-1e17 FLOP/s as plausible). Also assuming 100% of the brain’s FLOPs are applied to the task at hand (changing this percentage makes less than an order of magnitude difference).
🧑🦱 Market cost per flop → $10 / hr / (3600 s/hr × 10¹⁵ FLOP/s) = 3e-18 $/FLOP
🧑🦱 Subsistence cost per flop → $0.75 / hr / (3600 s/hr × 10¹⁵ FLOP/s) = 2e-19 $/FLOP
Machine cost per flop – examples through history (adjusted to 2026 dollars):
💻 An early computer like the IBM 704 (1955) was leased for $530k/month and ran at 2 GFLOP/S → $530,000 / (176 h × 3,600 s × 5,000 FLOP/s) = 1.7e-4 $/FLOP.
💻 A 1999 computer like the Pentium III cost about $1090 and ran at 2 GFLOP/s. If used 24/7 for 4 years → $1,090 / (1.26×10⁸ s × 2×10⁹ FLOP/s) = 4×10⁻¹⁵
💻 A 2010 GPU like the GTX 580 (which AlexNet was trained on) cost about $590 for 1.5 TFLOP/s → $590 / (1.26×10⁸ s × 1.5×10¹² FLOP/s) = 3e-18 $/FLOP.
💻 A 2027 AI chip like NVIDIA Rubin costs about $55,000 and runs at ~35 PFLOP/s at 4-bit precision → $55,000 / (1.26×10⁸ s × 3.5×10¹⁶ FLOP/s) = 1e-20 $/FLOP
---
I will try to write this up in more detail soon. Some refs:
* FLOP/s of the human brain: coefficientgiving.org/resear…
* US and global labor costs: bls.gov/news.release/empsit.…
ilo.org/sites/default/files/…
* subsistence wages:
jstor.org/stable/10.1086/498…
17
16
152
16,935
Matt Beane retweeted
Steve was very early on this. But he’s exactly right—chatbot era was never going to be a huge productivity boost. Analyses should put the line at January 2026; agentic AI is where productivity gains are.
Unpopular opinion: AI basically became useful for enterprise use early this year with agentic AI acceleration. Everything before was basically consumer and hobbyist. 2026 is year 0 for AI enterprise use. So why would anyone have expected measurable productivity increase already.
34
41
836
118,474
Matt Beane retweeted
People who have been in research fields develop a felt sense that most "research" (in almost any field that isn't exactingly technical) is research theater, and many superstar careers enjoy star status not because of a unique connection to the truth but because of a unique connection with an audience. No one really has the time or stature to, from a position of objectivity and trust, bring popular researchers to heel. But it will get increasingly hard to hide from serious critique. The machines can do critique now, at the level of depth and rigor previously only possible for the academically deranged. We're going to have to revise a lot of what we "know" about the world that isn't really knowledge but is actually just received popular consensus - like floating voltages without grounding wires. The grounding wires are coming.
Tyler Cowen:
'I am not even sure what to say at this point. We need a radical revaluation of this work, and of the associated policy arguments. More generally, this is only a single step in the story of how AI is going to revise economic science, and indeed past research more generally. As I stress in many of my recent talks, there will be significant gains and losses in status, with the losses often outweighing the gains. I see this as one of those cases.'
55
240
1,809
201,388
Matt Beane retweeted
SIR PATRICK STEWART (1940-2026)
Before everything else, Patrick was defined by being born and bred in Yorkshire, the proud county in the north of England which he loved to the end. You could hear it in his accented voice and in the stern honesty with which he told you what he thought and felt. Yorkshiremen have no truck with half-truths or avoidance of big issues. He wore his heart on his sleeve, which made him a man to rely on, to admire and in my case, love.
We first met as ambitious young actors with the Royal Shakespeare Company half a century ago but we weren’t in the same productions. My first strong memory was a few years later, meeting him in the street in central London when he told me about an offer to take over a leading part in 'Star Trek'. “But Patrick think of your stage career in the UK. Do you really want to risk—getting lost in Hollywood for years and years?”. Well, he took the risk and thank goodness for us all that he did for not just his devoted Trekkies but film and theatre audiences, who marvelled at his using international celebrity to star in a string of cinema successes ('X-Men' of course) and in great classical plays by Shakespeare, Ibsen, Arthur Miller, Peter Shaffer, Pinter and Beckett at Stratford-upon-Avon, in London’s West End and on Broadway.
America was his adopted home, where he met his adored Sunny who has cared for him through sickness and health, through thick and thin. But he never forsook his origins: and the proudest achievement of the most respected and beloved actor of his generation on either side of the Atlantic, was his appointment as Chancellor of Huddersfield University in Yorkshire.
His farewell performance in 'Avengers: Doomsday' is yet to be seen.
Ian McKellen 29 October 2026
Photo: University of Huddersfield
3,370
91,998
474,783
6,872,746
There’s 100% a kind of mania you can get into with coding agents, where it feels like you’re getting a lot done and working all the time but nothing is really happening.
I think it's often a form of avoidance of something else in life.
811
848
17,003
1,421,048
Matt Beane retweeted
New DeepMind Institute essay: "What is work for? Human wellbeing and the value of work in the AGI era."
The empirical evidence shows that many people value their jobs beyond earning a salary, and the importance of agency, status, and meaning. At the same time, we investigate alternate sources of wellbeing, and the possibility that societal norms around work may change over time.
with @JulianDJacobs @locross
Read it here: bit.ly/wellbeing-work-agi
2
31
171
11,461
We're in the early days of a Cambrian explosion of an agentic ecosystem.
Just yesterday (i.e., last week) it was reverse engineer anything.
Now, as a countermeasure, this adversarial defense packet is ripping around the interwebs: github.com/qybaihe/bla
4
324
Matt Beane retweeted
Lots of debate this week on whether journals should ban AI in peer review.
We actually tested this in our new preprint, and the results were pretty clear to me.
For context, I've reviewed for most of the big journals and evaluated 1,000 human reviews as an editor. I love to read and evaluate science.
TLDR: From now on I won't do any peer review without AI. For clinical trials, I'd even call human-only review dangerous 🧵
137
521
2,137
285,307
Top of my queue.
This doesn't answer "what new jobs can we expect?" but it does help us see the stocks and flows of labor in the economy, and the types of work involved, given a variety of assumptions about the AI cost/performance curve. Massive potential predictive power.
I joined @GoogleDeepMind to develop a research program on the economics of AGI. Today, together with Andrew Koh (@andrewjkoh) and Shane Legg (@ShaneLegg), we are incredibly excited to release The Economics of Intelligence, the first in a series of projects from our group on how AGI will change the economy.
How do capability improvements transform the economy, and when? In this project, we define thresholds of economic capabilities, e.g., minimal AGI, based on how they transform the economy. We then track how the economy–market structure, employment, and wages–changes during the transition across capability regimes.
We have seen exponential increases in what AI agents can do but the broader economy seems almost remarkably unchanged. Part of the reason is that the solo AI agent is the wrong economic object; economic transformation is an equilibrium outcome where organizations compete. Looking at how intelligence functions within organizations, transformation will depend on when two key capability thresholds are crossed: competence (gains on individual skills, e.g., coding, math) and coordination (gains on ability of agents to cooperate and work together).
We show that what economic transformation looks like depends on whether AI becomes supercompetent, supercooperative, or both—the regime of artificial superintelligence (ASI). Tracking this transition shows why the real visible transformation may come from improvements in coordination—a capability most benchmarks don’t yet track. Past a certain threshold, AI capabilities can break the Coasian ceiling on firm size and lead to an economy that looks drastically different than the one we see today.
Two main takeaways:
1. To understand the path of transformation, we should be tracking agentic coordination more closely.
2. The impact of AI will likely show up in wages before market structure or employment.
We are really excited about this paper. Excited to hear people’s thoughts.
Link: institute.deepmind.com/essay…
1
1
15
1,953
This has only been presented to 4m people.
Endorsed by 10k.
Shared by 2.1k.
Jason is right, but not loud enough. Don't think anyone could be, really.
Let's hope this is y2k-level. That would mean we really don't understand the emerging AI security ecosystem!
as bad as things have gotten in the past 4 days, they are going to get a lot worse before they get better. security leaders, never let a crisis go to waste: please go to your boards and ask for help right now. not for ai, for the basics. (we need to hold on for ~18 months.)
6
759