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.
Weekend win: The proof I submitted for Erdos Problem #397 was accepted by Terence Tao.
The proof was generated by GPT 5.2 Pro and formalized with Harmonic.
Many open problems are sitting there, waiting for someone to prompt ChatGPT to solve them:
MetaPlanet for those who want to watch MetaPlanet trade globally ... here is a quick rundown of the market hours. $MTPLF trades US OTC 930am-4pm. 3350.T trades in Japan starting at 8pm ET til 2am ET (Japan breaks for lunch from 10:30-11:30pm ET). DN3 trades in Germany from 3:00am to 11:30am ET. I have posted previously about the nuances of the Tokyo Stock Exchange including the auction process for opening a stock, matching buys and sells to find the opening price and the limit to how much a stock can rise on any given day which has essentially stopped trading of 3350.T this week in Japan because it has hit the daily limit during the auction process... so when the US markets closes today at 4pm ... you can watch and see what Japan does starting tonight at 8pm ET. These hours all reflect regular trading sessions, Monday to Friday, excluding holidays.
@BTCBullRider 👍👍Guys, for next episode may be good to delve into how 3350, DN3, MTPLF trade round the clock, its implications and dynamics of large shorts.
@BenjaminStongMD My cost basis is around 3.1. Really depends on time horizon .. medium to long term this should go much higher. Personally would prefer a pullback to buy more, but yeah hard not to fomo.