Richard de Crespigny

This robotic hand can be 3D printed by anyone and assembled in under 8 hours. Researchers at ETH Zurich created the Orca hand, fully open-sourced with artificial bones and tendons. For context, advanced robotic hands cost over $100,000 and require constant maintenance... Orca costs under $2,000. 50x less (!) A self-calibration system maps every motor to every joint, eliminating the manual tuning that tendon-driven hands usually need. Each fingertip has built-in tactile sensors covered by silicone skin. The hand can actually feel when it touches something, giving it feedback to grip objects without crushing them or letting them slip. It can hold over 20 lbs, learn tasks by watching human demonstrations, and transfer skills trained in simulation directly to the real world. The team proved its durability by having it pick up and place a cube over 2,000 times across 7 hours with no human intervention. The full design files and source code are open source, so any robotics lab in the world can start building one today.

Focus on the black cross and the red dots will appear to follow waves even though they move straight.

It is hard to communicate how much programming has changed due to AI in the last 2 months: not gradually and over time in the "progress as usual" way, but specifically this last December. There are a number of asterisks but imo coding agents basically didn’t work before December and basically work since - the models have significantly higher quality, long-term coherence and tenacity and they can power through large and long tasks, well past enough that it is extremely disruptive to the default programming workflow. Just to give an example, over the weekend I was building a local video analysis dashboard for the cameras of my home so I wrote: “Here is the local IP and username/password of my DGX Spark. Log in, set up ssh keys, set up vLLM, download and bench Qwen3-VL, set up a server endpoint to inference videos, a basic web ui dashboard, test everything, set it up with systemd, record memory notes for yourself and write up a markdown report for me”. The agent went off for ~30 minutes, ran into multiple issues, researched solutions online, resolved them one by one, wrote the code, tested it, debugged it, set up the services, and came back with the report and it was just done. I didn’t touch anything. All of this could easily have been a weekend project just 3 months ago but today it’s something you kick off and forget about for 30 minutes. As a result, programming is becoming unrecognizable. You’re not typing computer code into an editor like the way things were since computers were invented, that era is over. You're spinning up AI agents, giving them tasks *in English* and managing and reviewing their work in parallel. The biggest prize is in figuring out how you can keep ascending the layers of abstraction to set up long-running orchestrator Claws with all of the right tools, memory and instructions that productively manage multiple parallel Code instances for you. The leverage achievable via top tier "agentic engineering" feels very high right now. It’s not perfect, it needs high-level direction, judgement, taste, oversight, iteration and hints and ideas. It works a lot better in some scenarios than others (e.g. especially for tasks that are well-specified and where you can verify/test functionality). The key is to build intuition to decompose the task just right to hand off the parts that work and help out around the edges. But imo, this is nowhere near "business as usual" time in software.