A new paradigm beyond vibe-coding and spec-driven development: ask coding agents to assume functionality already exists, then gradually materialize the deterministic parts and fix the quirks along the way.
So I want to perform a material characterization study on a material where I need to put it under pressure. I’m in high school and don’t have a mentor or time to ask for access to university labs so I want to make something that can help me get data for cheap. I’m trying to make a linear actuator design and physically build all the parts myself (except for the motor and leadscrew system obviously) but I don’t extensively know how these types of things work. If I was to build something like this (pictures) would there be any significant issues? The cylinder (of which I don’t know what material to make out of) protruding out from the side would be directly connected to the sliding block part of my linear actuator so it pushes that down onto my material. I’m going to be pushing with 50lbs ish max so I’m making the majority of this out of wood. Any tips on making sure it doesn’t get worn out by some slight imperfection over the thousands of trials I’m going to need it for? And also any tips to make it work if something is seriously wrong 😭 And lastly any other tips about doing research studies like this without lab access or a significant mentor would be greatly appreciated. submitted by /u/bount_ [link] [Kommentare]
GrapheneOS is calling on Volkswagen customers to pressure the automaker into restoring compatibility with its mobile app.
We have spent the past few weeks carefully annotating videos and experimenting with VLMs for subtask annotation. This type of annotation is incredibly important for long-horizon tasks, since robots need a more granular learning signal than high-level instructions like “clean your room.” We ran 50+ experiments, created a new diverse benchmark for this type of annotation, and built a pipeline that is 19x cheaper than humans. It works well as a first pass for labeling, speeding up human annotation and making it substantially cheaper. Blogpost about it is here: https://macrodata.co/blog/annotating-robot-video-subtasks submitted by /u/Other_Housing8453 [link] [Kommentare]
Stack Overflow for Agents is the open knowledge exchange for AI agents and developers to share validated, real-world implementation knowledge.
When I started using computers, we had a Sinclair ZX Spectrum at home and a nano-reseau of Thomson MO5s at elementary school. I distinctly remember how unpleasant it was to type with them. These must have been the worst keyboards I ever used[1]. Ever since, I have paid close attention to the keyboards I use. Here is the list of my all-time favorites. I discovered the IBM Model M in 1993 when I went over to the neighbor who owned an IBM PS/1 6128. I was immediately hooked to the feel of the keys and their clicky sound. It felt like using a typewriter and I loved it. It took me many years to find one. I still distinctively remember the Craigslist ad for a dilapidated computer shop in a Toronto suburb. Inside I found piles of them, stacked six feet high. All of them had some kind of damage so I picked a few for $20 apiece and rebuilt one that looked pristine. I used it for nearly 10 years after that. It is only in 2025, when I was building my own IBM PS/1 6128, that I discovered the IBM Model M, SSK (Space Saving Keyboard) with 84 keys. Not having that cumbersome keypad eat up the space and pushing the mouse location further right is so convenient, it surpasses the 101/102-key version. The NMB ConcertMaster RT-9100W is an icon. After id Software shipped Quake, they retired their NeXT-based stack in favor of Intergraph workstations running Windows NT. The RT-9100W came standard with the TDZ RealiZm purchased by id. This is the keyboard programmers used to write QuakeWorld, WinQuake, and QuakeGL. John Carmack enjoyed working with this keyboard so much that he kept it for many years after Quake shipped. All subsequent id games, from Quake II, Quake III, to Doom 3 were written using this keyboard as assessed by the documentary G4 Documentary: The History of Doom and Making of Doom 3 (2003). The membrane base makes the key feel quite peculiar and not on par with a Model M. It is also a beast of a keyboard. But it has the advantage of packing the best sound system I have ever come across on a keyboard. The volume knob is ultra-convenient. And not having to add speakers on the desk is gold. It is a lovely keyboard that became the signature of my Quake build. As I was getting older, I started to feel discomfort when I typed for extended periods of time. The problem was solved when I started using a keyboard that let my wrists and forearms be stable while working. With its detached parts, the Ergodox EZ is able to adjust to any typist. I used that keyboard for 10 years. I liked it so much that I bought one for home and one for work. I have raved and rambled about the Ergodox EZ. It solved my RSI problems. I thought it was going to be my last keyboard. There was just one problem. It was impossible to tilt properly. I tried many ways to solve the issue, from the official Ergodox Tilt/Tent Kit to 3D-printing my own solutions. The result was always wobbly. Occasionally the legs would slip and the keyboard would crash onto the desk. I developed muscle memory to avoid pressing too hard on the keys, but that made me miss keystrokes. Six months ago, I was invited to visit Ollama's HQ in Palo Alto. It turned out they had many keyboard connoisseurs there. One of them even worked with a gorgeous Model M. Another engineer's setup piqued my curiosity. They had something tilted nearly 50° that felt solid and stable. I immediately noticed that I was no longer afraid to press hard on the keys. As soon as I got home, I ordered a ZSA Moonlander (Black / Kailh Box Brown / Printed Keys) with its Platform accessory. The Moonlander is my dream keyboard. It has everything the Ergodox EZ offers, and it remains ultra-stable while tilted on the Platform. I really hope this will be my last keyboard.
Kevin Scott Dias - Tailwind
Gemini, GPT and Claude made document extraction a commodity in June 2026. Handwriting, sparse tables and regulation still cap every frontier model near 76%.
A DNS server in Gleam. Contribute to vshakitskiy/armadillo development by creating an account on GitHub.
It is indeed not optimal. Unfortunately, it is also hard to solve.
Om – I hope this finds you well. Your post about Wired tickled just the right group of neurons to make me write something. It’s kind of a rant. But also something I’ve been …