spent some time testing ASD-STE100, ngl it works, embedded it into my pipeline. Also turned it into repo for funsies if anyone else finds it useful: stop-ai-slop - github.com/regardo911/stop-a… 1. writing rules based on ASD-STE100. 2.plain english standard used in aircraft maintenance manuals. 3. plus a python check that flags filler and long sentences in ai replies. chefs kiss😙

Andrej Karpathy: "Prompting is going away. Delete everything, keep Graph." In just 69 minutes, he shows how to build graphs and why they're the only layer that survives in the end Prompts → Agents → Loops → Graphs a loop keeps one agent running until the job is done a graph decides which agents exist and what each one passes to the next anyone can build an agent, almost nobody builds the graph that runs them watch it today, then save the full guide on graphs below before everyone starts catching up ↓

We'll be spending a lot more time trying to understand the outputs of language models. A few thoughts, tips & tricks: Writing. Something I've had success with: Ask your LLM to explain something in ASD-STE100, it's a controlled language specification originally developed for aerospace maintenance documentation. LLMs well-versed in this language and it comes with heavy constraints on clean writing style that I often find a lot more readable. Sometimes I've tried to soften it a bit e.g. ask for "80% of the way to ASD-STE100" because the spec is quite stringent. But even better: Diagrams / images. Instead of writing, ask your LLM to create a diagram. These can be a lot easier to process, parse, and understand. But even better: Web pages. Ask for output "in HTML" to get a beautiful, interactive webpage. LLMs are getting really good at frontend and can create beautiful experiences, animations, etc. But even better: Explainer videos. The output format I am most bullish on is fully custom / bespoke explainer videos generated on any arbitrary topic. Experiment with things like "Create a 3b1b style video explainer on X. Use my ElevenLabs API key for audio narration". (you'd need an API key for the latter or you can ask your LLM to find you decent free alternatives that use your local compute). This is actually starting to work! In summary: - As LLMs get better, they will do more and more of the legwork autonomously, and a lot more of our work will rise up the abstractions into oversight and understanding. - Luckily, LLMs can help here too because as intelligence and code are increasingly abundant, you can ask for large, custom, discardable software artifacts (e.g. web apps, video explainers) that would have never made sense to create before. Push the boundaries here and you'll be surprised.

We're open-sourcing Claude Commerce Agents. This is a blueprint for building shopping and merchant agents, with reference implementations across retail, travel, telecom, and entertainment.

for funsies. Pretty wild that ATH high for #1 was > $17000 . curious to see if it moves the needle on sales lock me in coach. outbid.lol / youcanbuildthings.com