Mark Chitty

Product Manager @Zap_Map. Ex-dev. In digital since the late 90s. Fascinated by #EV,#AI,#AR, #VR (not necessarily at the same time). Nascent V̶i̶b̶e Guide Coder.

[Prof. Stefan Rahmstorf 🌏 🦣 @rahmstorf]

I'm afraid that this is why the US administration wants to shut down ocean observations: they don't want the people to know what is happening in our oceans, as it does not fit their ideology and the interests of their fossil fuel industry funders.

https://t.co/G1E5zXdyid

[Mark Chitty @TechPdM]

@theSciTechGuy @AISitRep

[Anon Opin. @anon_opin]

Charlie Brooker should bring back Nathan Barley in an episode of Black Mirror

[Mark Chitty @TechPdM]

@nubient @anon_opin One of the most accurately prophetic series ever made.

It's actually uncanny.

[Mark Chitty @TechPdM]

Life imitates art.

[Pirate Wires @PirateWires]

Gwyneth Paltrow just invited Anduril cofounder @traestephens onto the Goop podcast — and, in a wide-ranging conversation about love, war, God, and Gwyneth’s leftist husband who thinks she’s “becoming a Republican”… Trae explains Anduril’s core goal: to engineer lasting peace.

America, Trae explains, needs AI-assisted weapons that can execute missions without endangering American lives.

Sometimes conflict is necessary. Gwyneth gets it.

Full breakdown from @harrissockel 👇

[clem 🤗 @ClementDelangue]

Token costs are why there will be no saas apocalypse / good dev tools are cached intelligence for agents!

The popular theory goes: agents can write code, so they'll just rebuild every tool from scratch and hit raw APIs. no more dev tools, no more CLIs, no more software layers. just agents and endpoints!

We just tested this and the data says the opposite. We benchmarked Claude Code and Codex on real Hugging Face Hub tasks (~1,000 graded runs), with two setups: the agent-optimized hf CLI vs the agent hand-rolling curl or SDK calls from scratch.

Hand-rolling burns up to 6x more tokens on multi-step tasks and fails more often (84% vs 94% task success).

And that's just dropping one abstraction layer. It would obviously be orders of magnitude more tokens and a dramatically higher failure rate if the agent tried to bypass HF altogether and rebuild model hosting, versioning, and distribution from scratch. Every time an agent re-derives a workflow from raw API calls, you pay for that reasoning in tokens. every single run. a good CLI compresses that entire chain into a few high-level commands the agent can't get wrong.
In a world where everyone is complaining tokens are too expensive, abstraction is leverage: thousands of hours of design decisions your agent doesn't have to re-reason about at inference time.

Good tools are cached intelligence for agents!

So no, agents won't rebuild everything from scratch. they'll gravitate to the most token-efficient tools, because that's what their owners pay for. The software that survives won't just be accessible to agents, it will be accurate and cheap for them to drive.

We're seeing it happen with HF, which is becoming the platform for agents to use AI: ~49M requests in just two months, and growing fast!

https://t.co/Y7q6yuxZrZ

[Andreas Klinger 🦾 @andreasklinger]

A fully electric autonomous tractor that lifts 4 tons, pulls 8 tons, runs 24 hours, and you can repair it in the middle of a field. This is Voltrac. 🦾 Made in Europe 🇪🇺

How would you design a futuristic autonomous tractor? Voltrac threw out everything and started from scratch. 70% fewer parts. One motor per wheel. Hot-swap batteries. Backwards compatible with any attachment a farmer already owns.

Voltrac is more than a tractor, it’s the brain of the farm. One operator supervises multiple tractors across multiple farms. Every drive analyzes the crops, catches disease early, cuts fertilizer costs.

And the same hitch that connects to farm tools connects to demining gear and resupply payloads for the front line.

Disclaimer: I'm an early investor, because this is exactly what Europe needs.

Europe had 70 million farmers in 2020. Projected 7 million by 2030. Our population keeps growing. Everyone still wants to eat. Somebody has to solve this.

They build in Valencia, not China. Because the talent, the precision manufacturing, and the know-how are all here.

We just forget how good we are. If we don't build this, someone in China will and sell it to European farmers. 🇪🇺🔥

Full Video on YT!

[Mark Chitty @TechPdM]

@SawyerMerritt @AmazingChevVolt It's the right conclusion, but with the wrong emphasis.

[Mark Chitty @TechPdM]

@CFSMotorRacing Looking up the range for 6.7l RRs.

It's 350Mi on a good day. 250Mi for city driving. The Ghost does a bit better, more like ~500Mi realistically. Hardly 'no range limits' though eh?

At least with an EV your butler could charge it while you're out shooting grouse. 😆🤦

[Mark Chitty @TechPdM]

@Manhattva @EndjinnFeersum Low poly.

[Chetaslua @chetaslua]

Claude Mythos / Oceanus is insane see the level of detail

using Three.js (from jsDelivr).HTML and a custom meshing engine it made (in like 5 minutes and low effort thinking level)

Credit to @Lentils80 and z..AI , this is so good people are not realising it yet 😭

[Ole Lehmann @itsolelehmann]

i'm obsessed with AI DIY projects.

my favorite one right now is this broccoli farmer in hokkaido, japan using Codex to run his 100-hectare farm

this guy never studied agriculture, never inherited land, started out as a civil servant.

but he wanted his farm to run better, and instead of paying an engineering firm he couldn't afford, he just built the tools himself.

here's what he's built on his own:

> remote control of his greenhouse vents from a chat app, wired up with an esp32 board, a motor driver, and cloudflare workers

> a bot that checks each greenhouse's temperature and opens the vents when it gets too hot

> satellite crop-health data laid over a map of his own fields

> an airtable base linking his plots, tasks, materials, and sensors

> wiring diagrams of his electrical panels, generated from a photo

stuff like this used to be locked behind machinery and engineers only the big agribusinesses could pay for.

but this legend just breezed past all of it with a laptop and Codex lol

[George from 🕹prodmgmt.world @nurijanian]

If you're a PM who's gone looking for AI course recommendations, read the answers to that question on r/ProductManagement.

Hot takes that won't leave my head:

1. Nobody recommended a course. Top answer, 39 upvotes: "just go build something." The whole thread in four words.

2. The "AI PM" certification market exists to monetize your anxiety. Commenters in the thread called it a scam. Several who'd shipped AI features said the same.

3. The judgment calls you've built over years (knowing what to build, what to cut, when something's quietly failing) are exactly what AI product work demands.

4. Evals are the most underrated skill for PMs right now. They force you to define what "good" means before you ship. You've been solving that problem your whole career, just without the word for it.

5. "Build something" doesn't mean launch a startup. Take a real problem from your week, wire a solution in Claude or Cursor, use it for a few days. A week of building your own prototype will teach you more than an 8-week course.

6. The bar is embarrassingly low right now. Most companies don't have anyone who can take a PM brief and turn it into a working prototype in 48 hours. Do that once and you become the person people call.

7. Six months of building compounds faster than three years following AI discourse on LinkedIn. Not close.

8. The AI PM skills that compound (problem decomposition, requirements clarity, eval design, judgment about what to automate vs. what to keep human) aren't in any course syllabus I've seen.

9. The thread had PMs who could describe what LLMs do but hadn't shipped anything that week. Most PM courses teach frameworks, not the habit of shipping.

10. you don't need permission to start. Open Claude. Pick one annoying thing from your week. Build the thing that removes it, and you'll have a portfolio-worthy AI PM project.

[Anthropic @AnthropicAI]

Our internal data shows Claude is accelerating AI development—a possible path to recursive self-improvement, or AI autonomously building a more capable successor.

It’s happening faster than we thought, and the implications deserve greater attention. https://t.co/OVVPJO7VQx

[Mark Chitty @TechPdM]

Just watched The Amazing Digital Circus The Last Act with my kids and it might be one of the most insane things I've ever seen at the cinema.

Quite brilliant, and the kids loved it but it's unlike any 'kids' media I've ever seen.

Packed full of Jungian archetypes and angst.

[VraserX e/acc @VraserX]

Anthropic looks like it’s gearing up to launch Mythos, and wow, the rumored pricing is brutal:

$16 input
$80 output per 1M tokens

If Oceanus is really the preview, this thing better be insanely good.

At that price, every prompt needs a financial advisor.

[Bilawal Sidhu @bilawalsidhu]

Gosh I love the OSINT community. This project throws every plane flying overhead onto your ceiling in near real time – decoded from a cheap radio, w/ live stars and the ISS behind it. Falling asleep under a live map of the sky. h/t @CameronPaczek

[Jack 🤖 @JacklouisP]

Humour my recent rabbit hole into the colour blue. I discovered it’s universally hard to produce, and the physics is very cool:

•Real blue is rare AF. Fewer than 10% of plants are blue, almost no animal makes a blue pigment, and the ones that look blue are mostly faking it. Humans have had the exact same challenge.

•The challenge. Pigments colour things by absorbing some wavelengths and reflecting the rest. Blue is the hardest because it means absorbing red, the weakest light energetically. Soaking up low-energy light takes a big, complex molecule, and the bigger the molecule the more expensive it is to build. So nature leans on cheaper colours like red and brown.

•Nature also fakes it. Most blue you’ve seen in the wild isn’t pigment, it’s structure. Butterfly wings, peacocks, blue eyes: no blue pigment in any of them, just nanoscale architecture that scatters blue light back at you. Damage the structure and the blue dies.

•Even blueberries aren’t blue. Squish one and the juice runs deep red. The blue is a coat of microscopic wax crystals that scatter blue and UV light, sitting over a dark red skin. We only figured this out in 2024.

•Humans also struggled. Real blue was so hard to make that ultramarine, ground from a single Afghan stone, cost more than gold.

•The fix came by accident: in 1700s Berlin a contaminated lab batch produced Prussian blue, the first cheap, synthetic blue, and the dam finally broke. Its colour isn’t a fragile molecule at all but iron sitting in two charge states in one crystal; light knocks an electron between them and that jump swallows red, leaving a deep, stable blue.

How did we beat it? Not with a better organic molecule, nature already tried those and they’re all expensive. We stepped outside biology.

Nature is a great model, but it has its limits.

[Jip @jipvandervelde]

grug is probably the first Apple Design Award winner built by two designers using Codex to write the code.

We didn't prompt "build me an award-winning app, make no mistakes.” It did not wake up one morning and decide the world needed grug. We did. We wanted to build it and AI was the tool that helped us take it all the way there.

Ever since we started building with AI a few years ago, we got bolder. You stop killing ideas just because they sound too hard to build. You get weirder when trying things becomes cheap enough to be silly again. You start following the strange little thought further than you normally would.

That is how grug happened.

AI can write your code. It can help you move fast. It can make impossible things feel possible.

But it cannot care. It cannot make your app memorable. It cannot make your app feel like it has a soul.

You have to bring the taste. You have to stay incredibly close. You have to take small steps, make thousands of tiny decisions, throw away good-enough work to get to your best work, and protect the thing that made the idea worth building in the first place.

grug would not have been this memorable if we didn't have Codex to go all-in on all the crazy ideas we had. If we had not decided to make the whole thing hand-drawn. If we had not spent days and nights obsessing over every detail, every animation, every interaction, every tiny bit of weirdness.

That is the difference between slop and something with a soul.

And I think that is why this award means so much to us. Not because what we were able to do using AI to build grug, but because Apple recognized the care we put inside all the weirdness.

For the past 15 years, so many of our ideas stopped at the mockup. They were too weird, too small, too hard to explain, too expensive to build, too unlikely to survive a meeting. Now designers like us can build the fun little things. Designers like us can ship the crazy ideas. Designers like us can make unreasonable little things and see if the world cares.

There are plenty of people who do not get grug. That is totally fine.

We do not try to build for everyone, because when you do you end up building for no-one. The people who get grug really get it. And if it makes their morning feel a little lighter, that is all that matters to us.

Make the weird thing. The right people will find it.

grug no wait for permission.

grug back sun rise.

[Mark Chitty @TechPdM]

@Polymarket