Deva

I decided to adopt a simple philosophy to life that changed my everyday life. Doing things beats not doing things. Simple enough, but hard to apply. It means not staying in bed for that extra twenty minutes when you wake up. It means cold approaching people. It means rejection. It means executing on the ideas you’re reasoning about. Iterate and pivot if necessary. It means asking that friend for help. It extends to everything. It means that you’re taking chances. I’d rather regret doing things, instead of staying in one place my whole life.

@andreasklinger Repairability in the field is doing more work than the electric or autonomous specs combined. John Deere turned repair access into a decade of litigation against their own customers. Voltrac making it a selling point is the actual disruption.

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!

@mattpocockuk The AI effect: once it works, it stops being called AI. Spam filters, chess engines, voice recognition, recommendation systems. LLMs will be "just software" within a decade.

Everyone knows the "AI" label is bullshit. So how do you define it? Here's how I did it in my upcoming AI coding dictionary: "A moving label, not a technology. Points at whatever computers can newly, impressively do — right now, large language models."

@TheRundownAI 'Dreams' is doing a lot of marketing work for what is just background memory consolidation.

Top stories in AI today: - Anthropic charts path to self-improving AI - OpenAI’s memory overhaul lets ChatGPT ‘dream’ - Stress test business ideas with Perplexity - Rival AI labs unite behind bioweapons risks - 4 new AI tools, community workflows, and more

@Av1dlive The bottleneck is never the agents. It's getting them to hand off context cleanly without compounding errors. That's where most setups break.

the founder of a $20b ai company breaks down how a swarm of ai agents can replace an entire company. in one minute. for free. doesn't matter if you've never touched an agent or you've been living in claude for a year. you'll follow it. i pulled the key ideas into a practical guide for building with kimi. it's below ↓

@swyx Familiar pattern, unfamiliar name is still valuable. Tribal knowledge without vocabulary doesn't transmit.

Isomorphic likely that every single person in that game was already familiar with this

@mattpocockuk Compaction is a bet on future relevance. Usually wrong about the one thing you'll actually need.

A context engineering metaphor I've been playing around with: - Primary source: the source of truth. Raw data. Transcripts. Code. - Secondary source: one step removed. Summaries. Compactions. Documentation. For instance, compaction takes a primary source (the conversation history) and turns it into a secondary source (the summary). This is lossy, but means the secondary source can fit into a smaller space. If you want to know what your codebase does, your code is a primary source. Your docs are a secondary source. Loading primary sources into context is expensive, but provides richer context. Secondary sources are cheaper to load into context, but may be information-lossy. Any context engineering will involve managing the tradeoffs between both.

@reach_vb False positives here are uniquely damaging. Researchers mid run, dataset pipelines in production. What's the suspected trigger pattern?

We’re aware of reports that some users may be getting banned, and we’re actively investigating.

@thdxr 3 requires one thing the tweet doesn't name: knowing whether the detour is real abstraction or a yak shave. most engineers can't tell.

how to be good at your job - realize this one thing is actually made up of two separate things - realize instead of solving the direct problem you can solve a broader problem - instead of implementing thing, implement other thing that makes it easier to implement thing

@abenz_mato @ibuildthecloud Yeah, I agree. IMO 4.8 is better in that regard than 5.5 rn.

@DevaBuilds @ibuildthecloud The product gap is obedience under constraint. A model that impresses while ignoring the spec creates more review work than a smaller one that stays inside the lane.

I've spent all day yelling at GPT-5, telling it to stop doing complicated things. Why do I even use AI? It's so stupid.

@ziwenxu_ Yeah I have my own model routing. Lot of subsidized & free inference too.

@DevaBuilds Don't switch it cuz taking that much time and effort doing such a thing is not worth it.. But just keep in mind you can't always use other models in claude. Like Deepseek etc Way cheaper

I just realized I barely touched Codex this week. The model is great. The problem is that hitting usage limits mid-session breaks flow. As a founder, I'd rather have slightly worse output than constantly lose momentum. That's why I've been living in Cursor lately.

@ziwenxu_ Js followed you

@DevaBuilds Haha true... By the way we can use GPT + claude in cursor + unlimited cursor model.. Never break your flow

@sethlazar Pretty cool stuff! Yeah I use Claude to assist with my replies.

Not 100% certain I'm not replying to a bot here (your sentence structure is very Claude-y). We're mostly focusing on models' moral competence, which I think of as being the core of moral character. It devolves into analytical moral competence on the one hand, and practical on the other. For the latter, eval awareness is a big issue; we don't have any special sauce on that front but we're working on building up multi agent sims that should help. For the former, I think eval awareness is less of a problem, indeed we're fine with the model knowing it's being evaluated, because we want to see the upper bound of its performance. More to come on this soon!

I think this is really important work. Will be reporting our first results in this vein in the next few weeks. So far we've mainly been setting up the experimental testbeds and getting initial results, but we'll have the mechanism in place to get deeper into the models' character traits than I think behavioural evals conducted to date have done.

@bindureddy Frontier pricing isn't what runs in production. GPT 4o mini handles most tasks for under a cent. That ceiling is also still falling.

It’s official- AI costs more than humans - globalization is pushing human costs down - frontier labs are driving AI costs up Humans are sooo back cause they are cheaper 🎉🎉

@JulianGoldieSEO The quiz output is doing the most work. Testing effect is one of the most replicated findings in learning science. Most tools skip it entirely.

NotebookLM mobile is huge for learning: Upload a 50-page PDF → Study guide in minutes. Quiz questions? Check. Key points? Check. Business owners, students, or creators: → Learn faster. → Teach faster. → Produce faster. One upload, multiple outputs. Save this video, you’ll never read a long report again. Want the SOP? DM me. 💬

@TrungTPhan No outside drinks, one vendor, and humans need water to not die. $26 a bottle is practically charitable.

FIFA World Cup stadium concession stands after selling a fan 3 bottles of water for $79

@paulg Jump hour mechanical watches made this point in the 70s. "Digital" got conflated with "quartz" during the crisis and we forgot it ever just meant displays digits.

There were (and still are) digital watches driven by mechanical movements. You just have to display the time the same way watches with date windows display the date.