yeap the plan is to map products to semantic IDs which the model can understand

code for data prep, training the RQ-VAE, SASRec, Qwen3-8B, chatting with the model, etc

github.com/eugeneyan/se...

demo of the LLM-recommender hybrid returning both semantic IDs & english, and:
• steering recs via natural language
• explaining the recommendation
• naming the bundle of recommendations
• multi-turn conversation to get recs

watch till the end for the bloopers lol

www.youtube.com/watch?v=_0n4...

For example, given a sequence of items, it can recommend the next best item. But better than that, you can steer the recommendations with natural language! And it can explain why it gave that recommendation, as well as creatively name recommendation bundles.

For example, Amazon started to implement the first version of Amazon Prime in late 2004 and announced it on February 2 2005, six weeks later. An account of how it came amount and lots of anecdotes here. vox.com/recode/2019/...

Also this list: patrickcollison.com/fast

converted all images to webp and hopefully made the site faster. something i wouldn't have bothered in the past

Previously, these tasks weren't worth the effort but now they can be done in hours. What an amazing time to build and play =D

opps! thanks for letting me know, fixed!

p.s., If you’re interested in topics like this, my friends Ben and Swyx are organizing the AI Engineer World’s Fair in San Francisco on 3rd - 5th June. Come talk to builders deploying AI systems in production. Here’s a big discount for tickets: ti.to/software-3/a...

Here's the code for the mcp-server (src), prompts (context), and generated summaries from May 4th (summaries).

github.com/eugeneyan/ne...

Here's a three-minute demo of news-agents in action. It's pretty cool at the 30-second mark how the sub-agents get spawned! We then see the main agent assigning tasks and polling for progress, and finally shutting the sub-agents down when they're done with their assigned tasks.