Tom Hipwell

The master speaks on AI 2027 forecasts.

Great piece on Neil Mehta that has been doing the rounds this week.

I definitely don’t agree with all the predictions here (why do AI nerds always get obsessed with making geopolitical predictions?)

AI increases labour supply rather than reduces it, and watch out for those second order effects on society at large: Occupations more exposed to generative AI saw a rise in work hours immediately following the release of ChatGPT.

Great post from Tina He on the future of work in the era of AI.

Similar to the Model is the Product a couple of weeks ago, the bitter lesson here is that brute forcing problems with compute wins versus clever solutions.

Let’s join the dots between a few different themes this week.

I think this is a strong take on the on the consequences of the recent RL breakthroughs from Alexander Doria: I think it’s time to call it: the model is the product.

Lots to digest here.

Hot take.

I thought this post was interesting, not so much for conclusion about Grok 3 but instead for the range of tests that Andrej performs to get a feel for the capabilities of the model in <=~2 hours.

Another day, another AI dev flow.

Great post from Nelson Elhage (Anthropic pre-training team) on adventures coding with Sonnet.

The title is a little click-baity, but the analysis of the paper in the blog is great.

The insights here are not novel, but Dario provides a strong mental model of how the AI system will keep evolving over time: Shifting the curve.

Here they come, Rocketable is a YCW25 batch startup following the AI Rollup model (see previous post).

There’s a few pieces on AI Rollups floating around and I think it’s worth getting familiar with the model as it looks like a trend.

Good list, I’ve read a few of these but lots more to work through.

I’ve long thought consistency is king - I think this applies in codebases of all sizes, not just those in the single digit millions as Sean describes.

DeepSeek-v3 dropped on Christmas day (!)

Everywhere seems to be full of hype around o3 since Friday’s annoucement from OpenAI so I thought I’d summarise a few points I’ve seen shared in various places but not yet gathered in one place.

Webdev Arena builds on the Chatbot Arena concept but provides a coding-specific benchmark that offers an extremely fast and cheap way for you to evaluate the vibes of the different models out there.

Some interesting ideas from Will on using generative AI to either manage the set of UI components shown to the user or generating the UI in raw pixels on the fly as we’re starting to see in gaming (i.e.

Interesting paper from Meta that has been generating some buzz: We introduce the Byte Latent Transformer (BLT), a new byte-level LLM architecture that, for the first time, matches tokenization-based LLM performance at scale with significant improvements in

OpenAI | 2025 | Technical Report Sarah Guo, Elad Gill, Aditya Ramesh, Tim Brooks, Bill Peebles | 2025 | Podcast This post has been sat in my drafts for well over 6 months now, but with yesterday’s release of Sora in GA I thought I’d have a go at explaining

I thought this was a brilliant, thought-provoking piece on how to use zoom with text in the LLM era from Amelia Wattenberger.

Insightful piece from Marc Brooker on Aurora DSQL, which was announced at AWS re:invent this week.

Decent quality semantic search has got much easier and cheaper to ship yourself in the last couple of years.

This S1 analysis from Meritech went viral due to the (compounding!)

End to end tutorial of function calling with Llama-3.2-3B-Instruct, building gradually from string templating, to using Jinja, to implementing web search with Brave:

The often forgotten first rule of ML is that you might be able to get a good enough result without ML: Rule #1: Don’t be afraid to launch a product without machine learning.

This [cheat sheet] by Brandon Rohrer (https://www.brandonrohrer.com/uv_cheatsheet) works as a handy 30 second introduction to the python package/project management tool if you’ve not met it already.

Brilliant throughout, with lots of small, golden nuggets.

There’s been a tranche of emails released as part of the Musk vs Altman stuff around OpenAI and it makes for some interesting reading.

TL;DR: A study of ~5,000 engineers across Microsoft, Accenture, and a Fortune 100 company finds Github Copilot boosts weekly PRs by 26.08% (SE: 10.2%) - but the effect varies widely, with a 95% confidence interval from 5.88% to 46.28%.

Pattern matching with LLMs used to find security vulns in the wild: A key motivating factor for Naptime and now for Big Sleep has been the continued in-the-wild discovery of exploits for variants of previously found and patched vulnerabilities.

Love a nice data driven product feedback loop; the Jitty folk have found a nice pattern with natural language search: Over the weekend we quietly released a highly requested feature on Jitty: search by travel time 🚌🚶🚗🚴‍♀️🚂 We’ve partnered with the good pe…

Nice paper on AI assisted code review at Google.

I liked Ethan Mollick’s post on ad dollars earlier this week, here it is if you missed it: No one has figured out how you integrate advertising with LLM replies.

I really enjoyed the nonint post on timelines to AGI.

Omar Khattab, Chris Potts, Matei Zaharia | 2023 | Paper | Github | Docs A lot of work with LLMs today involves working through a loop where you break a problem into steps, write a prompt for each step, then put the whole together by adjusting each prompt…

Counts of customer interviews seem to have become a bit of a vanity metric of late.

What’s awesome about Andrej Karpathy’s llm.c isn’t just that it’s a bare-metal, from-scratch implementation of GPT-2 (safety wink definitely required!).

March was the month we got Grok, OpenAI confirmed their strategy and we no longer needed to run on vibes alone as gpt-4 was displaced at the top of the leaderboards.

I thought Devin from Cognition looked super cool this week, the UX feels like a glimpse of a new era.

Anian Ruoss, Grégoire Delétang, Sourabh Medapati, Jordi Grau-Moya, Li Kevin Wenliang, Elliot Catt, John Reid and Tim Genewein | Grandmaster Level Chess without Search | 2024 | Paper Walter Isaacson | Elon Musk | 2023 | Book Towards the end of Walter Isaac…

February feels like it’s gone in a blur.

Lefteris Loukas, Ilias Stogiannidis, Odysseas Diamantopoulos, Prodromos Malakasiotis, Stavros Vassos | 2023 | Paper When I’ve heard folks talking about AI strategy recently a common trope has been that things are moving so fast that it is better to hold o…

End of month one already so its time for a round up.

I guess like everyone in 2023, I’ve thought a lot about LLMs, LMMs and all the rest of it.