I help founders build better technology—whether it’s finding market fit, acquiring early customers, scaling up, or enhancing product experience.
London
Joined January 2009
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How I coached @PlumbsVetDrugs to increase their app subscription conversions by 93%
And skyrocket their average App Store rating from 1-star to an exceptional 4.9-star, based on 781 global reviews.
Understand the transformative design journey I led here:
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Simon Hook retweeted
We've written over 60,000 words on the AI Snake Oil newsletter — almost the length of a book. We just posted an annotated guide to our ~40 essays so far: aisnakeoil.com/p/the-ai-snak…
There are four main themes:
– Resisting AI doom narratives
– Debunking hype about AI’s capabilities and transformative effects
– Understanding why AI evaluation is so tricky (which is one root cause of AI hype)
– Helping AI policy stay grounded in the evidence.
Our book is coming out in September but @sayashk and I will continue to cover AI in the newsletter. We originally started the newsletter as a way to jot down some of our thoughts as we drafted the book, but it's been way too much fun to stop now.
Simon Hook retweeted
Tory Govt froze UK income tax personal allowance (PA) at £12570 in 2021, continued by Labour.
Inflation adjusted PA would be £16048 in 2026/27.
Millions of poor forced to pay income tax.
Capital gains & dividends taxed at lower marginal rates than wages
ajbell.co.uk/news/real-cost-…
Simon Hook retweeted
sam altman watching ChatGPT hallucinate live on stage is the funniest thing i've seen all week
the CEO of OpenAI, on stage, in front of everyone, watching his own AI just make things up in real time
and his face says it all
this is the guy telling us AGI is coming soon btw
Simon Hook retweeted
This is INSANE, Anthropic ran its marketing with basically one person.
Austin lau, a non-technical growth lead, was running paid search, paid social, email, and seo solo.
Here’s the workflow:
> export ad CSVs into Claude Code
> AI flags underperforming ads
> agents generate new headlines + descriptions
> Figma auto-swaps copy across 100 ad templates
> MCP server pulls live Meta data
The results:
> ad creation went from 2 hours to 15 minutes.
> total marketing output grew 10×.
> conversion rates landed 41% above industry average.
One person doing what used to take an entire marketing team.
Simon Hook retweeted
Psychologist Stanley Milgram found that 65% of the population do not have the psychological or moral resources to defy authority’s order, no matter how illegitimate the order is.
Therefore only 35% have critical thinking capacity.
Stanley Milgram's famous obedience experiments (conducted in the early 1960s at Yale University) did not find that 80% of people lack the psychological or moral resources to defy illegitimate authority orders.
The actual results from his baseline condition showed that 65% of participants (26 out of 40) continued to administer what they believed were maximum 450-volt shocks to a "learner" (an actor), despite protests, screams, and apparent distress.
Simon Hook retweeted
Yann LeCun (@ylecun ) explains why LLMs are so limited in terms of real-world intelligence.
Says the biggest LLM is trained on about 30 trillion words, which is roughly 10 to the power 14 bytes of text.
That sounds huge, but a 4 year old who has been awake about 16,000 hours has also taken in about 10 to the power 14 bytes through the eyes alone. So a small child has already seen as much raw data as the largest LLM has read.
But the child’s data is visual, continuous, noisy, and tied to actions: gravity, objects falling, hands grabbing, people moving, cause and effect. From this, the child builds an internal “world model” and intuitive physics, and can learn new tasks like loading a dishwasher from a handful of demonstrations.
LLMs only see disconnected text and are trained just to predict the next token. So they get very good at symbol patterns, exams, and code, but they lack grounded physical understanding, real common sense, and efficient learning from a few messy real-world experiences.
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From 'Pioneer Works' YT channel (link in comment)
Simon Hook retweeted
> be Anthropic
> lost the $200M Pentagon contract to OpenAI
> climbed to #1 on the App Store anyway
> ChatGPT uninstalls surged by 295%
> shipped “Memory”to pull chatgpt users over.
Simon Hook retweeted
Rachel Reeves wants UK pension schemes to significantly increase their allocation to private equity investments.
Despite the fact that they are higher risk, less transparent and higher fees.
And have delivered lower returns:
State Street’s private equity index shows that the S&P 500 outperformed private markets funds over the last 1, 3, 5 and 10 years!
Another bad idea from Rachel.
Simon Hook retweeted
This is spot on. Ben Affleck’s characterization of AI very much matches my experience as an average quant coding person who uses AI day in day out. I don’t think “have something close to AGI” as impressive as Claude is. Fundamentally, “it’s just a tool”.
Simon Hook retweeted
The most skilled guy in the AI industry just said we're 1-2 breakthroughs away from AGI.
And he explained exactly what's missing.
Demis Hassabis runs Google DeepMind.
He won the Nobel Prize in Chemistry last year.
He's literally the reason why Google is considered the leader of the AI race.
And he just dropped the most specific AGI timeline ever:
"One or two AlphaGo-level technological breakthroughs."
That's it. That's all standing between us and artificial general intelligence.
But here's the thing...
LLMs are NOT going to get us there.
ChatGPT, Gemini, Claude - they're all hitting the same wall.
They can't plan long-term. Can't create NEW ideas. Can't understand physics.
Demis called them "jagged intelligences. Very good at certain things. Completely incapable of others."
You've felt this yourself.
You've felt this yourself.
You ask ChatGPT a complex question and it sounds smart.
But ask it to solve something that requires REASONING across multiple steps?
It falls apart.
So what ARE the 2 breakthroughs we need?
Breakthrough #1: World Models
AI that understands how physics actually works. How water flows. How cause and effect works.
DeepMind already has early versions (Genie, Veo).
The insight: If AI can GENERATE something realistic, it UNDERSTANDS it.
This is the foundation for robotics and AI that interacts with reality.
Breakthrough #2: Agentic Systems
AI that can DO things. Not just answer questions.
Plan multiple steps. Execute autonomously. Adjust when wrong.
DeepMind proved this with AlphaGo in 2016 - planning 20+ moves ahead to beat the world champion.
Now they're generalizing it to the real world.
And here's the most interesting part:
Demis says these two things are starting to CONVERGE.
LLMs + World Models + Agentic Behavior = AGI
And when I say converge, I mean Google is already building it.
They're setting up the first fully automated scientific laboratory in the UK.
No humans running experiments.
AI designs the test. Robots execute it. AI analyzes results. AI adjusts and iterates.
The lab will work on:
→ Room-temperature superconductors
→ Nuclear fusion materials
→ New battery chemistries
→ Climate tech breakthroughs
Demis's logic is simple:
"If AI can screen materials 100X faster, the energy revolution takes 10 years instead of 100."
But here's the scary part:
China is MONTHS behind. Not years.
"They're very close to the frontier. Maybe only months behind."
DeepSeek. Alibaba's Qwen models.
They're catching up fast.
And unlike what people thought, they're doing it WITHOUT access to the most advanced Nvidia chips.
The window for the West to lead in AGI is shrinking.
The economic impact?
Demis: "10 times bigger than the Industrial Revolution. And maybe 10 times faster."
Industrial Revolution took 100+ years and reshaped civilization.
This will be 10X bigger in 1/10th the time.
Mass job displacement. Economic restructuring. New industries overnight.
But also:
→ Curing all disease
→ Solving climate change
→ Unlimited clean energy
→ "Radical abundance"
Demis is betting DeepMind can get there first.
Google spent $400 million on DeepMind in 2014.
That stake is now worth 100s of billions.
Because DeepMind is now the "engine room" of ALL of Google's AI.
Every Gemini model. Every AI feature in Search, Gmail, Workspace.
All built by DeepMind.
Shipped across Google's dozens of billion-user products instantly.
That distribution is their superpower.
The final thing Demis said that stuck with me:
"AGI is probably the most transformative moment in human history. And it's on the horizon."
One or two breakthroughs and 5 years away.
According to the most skilled guy in the industry.
Simon Hook retweeted
Computer scientist Judea Pearl:
There are mathematical limits to LLMs that cannot be crossed by scaling alone
LLMs don't discover world models from raw data; they merely summarize the interpretations humans have already written down
"this path is not the way to get AGI"
Simon Hook retweeted
Apart from topping benchmarks, Opus 4.5 feels like it’s in a league of its own. It’s the first time I’ve felt that an LLM can write better code than most devs in real-world work.
We don’t know the real reason unless Anthropic shares the secret sauce, but a couple of ideas:
— Anthropic has found a clear niche (code + agent + tool use) and gone all in. That focus could mean more training data, more targeted post-training, and more evals/iterations on the workflows that matter for shipping software. Other labs are trying to win everywhere at once, and that’s rarely the best strategy.
— Anthropic is still heavily text-first, while others are spreading research and computing across more modalities (image generation, audio, video).
If that’s right, the lead isn’t only about major breakthroughs. It’s also about strategy: staying focused and targeting a niche.
The puzzling part is why there's such a massive gap between Opus and Sonnet, especially the jump from Opus 4.0/4.1 to 4.5 (attaching a benchmark). They feel like very different models.
