This is the the quote I've been citing a lot recently.

Q1 earnings are in: 2026 is off to a terrific start. Our AI investments and full stack approach are lighting up every part of the business: Search queries are at an all-time high with AI continuing to drive usage. Google Cloud revenue grew 63%, Gemini models have incredible momentum, and it was our strongest quarter ever for consumer AI subs, driven by @GeminiApp. Thanks to our partners employees around the world. Much more to share on our earnings call in 20 minutes… and at Google I/O in 20 days!

Jevons paradox is happening in real time. Companies, especially outside of tech, are realizing that they can now afford to take on software projects that they wouldn’t have been able to tackle before because now AI lets them do so. We’re going to start to use software for all new things in the economy because it’s incrementally cheaper to produce. Marketing teams at big companies will have engineers helping to automate workflows. Engineers in life sciences and healthcare will automate research. Small businesses will hire engineers for the first to build better digital experiences. And as long as AI agents still require a human who understands what to prompt, how to review when an agent goes off the rails, how it guide back, how to maintain the system that was built, how to fix the ongoing bugs, and more, we will still have humans managing these agents. This is why all the advice you get of not going into engineering is wrong. The world is going to increasingly be made up of software, and the people that understand it best will be in a strong economic position. This will happen in other roles as well where output goes up and demand increases.

Super cool that this technique might allow you to backprop through the ENTIRE execution sequence - using GRPO - and build better intuition on how to write code...

AIが復元した「清明上河図」に言葉を失う。確かに、AI特有の「滑らかすぎる質感」に違和感を覚える瞬間もある。だが、張択端が描こうとした千年前の喧騒が、圧倒的な解像度で迫ってくるのも事実だから、これは模写ではない。AIという異質なフィルターを通すことで、われわれは初めて「大宋」の熱気に触れる。賛否はあろうが、この没入感だけは否定できないかもしれない。

this is one of the most remarkable technical blog posts I’ve ever read

a=(x,y,d=mag(k=(4 sin(y*2-t)*3)*cos(x/29),e=y/8-13))=>point((q=3*sin(k*2) .3/k sin(y/25)*k*(9 4*sin(e*9-d*3 t*2))) 30*cos(c=d-t) 200,q*sin(c) d*39-220) t=0,draw=$=>{t||createCanvas(w=400,w);background(9).stroke(w,96);for(t =PI/240,i=1e4;i--;)a(i,i/235)}//#つぶやきProcessing

Email from Fiverr CEO to his team about AI ($1b company):

my best one yet. load in 4k then zoom out

Noticing myself adopting a certain rhythm in AI-assisted coding (i.e. code I actually and professionally care about, contrast to vibe code). 1. Stuff everything relevant into context (this can take a while in big projects. If the project is small enough just stuff everything e.g. `files-to-prompt . -e ts -e tsx -e css -e md --cxml --ignore node_modules -o prompt.xml`) 2. Describe the next single, concrete incremental change we're trying to implement. Don't ask for code, ask for a few high-level approaches, pros/cons. There's almost always a few ways to do thing and the LLM's judgement is not always great. Optionally make concrete. 3. Pick one approach, ask for first draft code. 4. Review / learning phase: (Manually...) pull up all the API docs in a side browser of functions I haven't called before or I am less familiar with, ask for explanations, clarifications, changes, wind back and try a different approach. 6. Test. 7. Git commit. Ask for suggestions on what we could implement next. Repeat. Something like this feels more along the lines of the inner loop of AI-assisted development. The emphasis is on keeping a very tight leash on this new over-eager junior intern savant with encyclopedic knowledge of software, but who also bullshits you all the time, has an over-abundance of courage and shows little to no taste for good code. And emphasis on being slow, defensive, careful, paranoid, and on always taking the inline learning opportunity, not delegating. Many of these stages are clunky and manual and aren't made explicit or super well supported yet in existing tools. We're still very early and so much can still be done on the UI/UX of AI assisted coding.

we're waiting for the end of the sentence

More apps should natively offer this. “Export for prompt” button

How fast are we sliding into a world where all “jobs” are just reformatting ChatGPT output?

If you're even half interested in energy, I bet you've seen this chart. I call it The Most Hopeful Chart in the World. The point? We're embracing renewable power MUCH faster than expected. Hurrah! Only problem is, this chart has an evil twin. A chart we really need to discuss 🧵

AI video generation today. When I was back in school, the story of the field of computer graphics (and physically based rendering etc.) was that we will carefully study and model all the object/scene geometry, physics, rendering etc., and after 1000 PhDs and 50 SIGGRAPHs get results like this. That a Transformers can shortcut all of that at this high of fidelity by training on a dataset of videos...

I've been asked countless times why I decided to pay a lot of money for a formal Autism and ADHD diagnosis in my 40s, and this quote perfectly sums it up for me... (h/t @OMGImAutisticAF, who I believe originally wrote this.) #autism #ADHD #neurodivergence

This is Mars...

My Op-Ed in today's Sydney Morning Herald and The Age: smh.com.au/lifestyle/health-… #autism #audhd #neurodivergent #startups @smh @theage