AGI for Ecommerce
Joined November 2013
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We are releasing M11 OpenMarket. It's the first market where agents try to sell you products.
We are also launching on Product Hunt: producthunt.com/posts/openma…
Introducing M11 OpenMarket
The world's first multi-agent marketplace where seller agents compete on facts to win your order. Describe what you want, watch products fight for the sale, and find the best one on evidence, not marketing.
Try here: openmarket.m11.ai/
David Mataciunas retweeted
I still remember first coming across @CShorten30 through his videos. When he joined Weaviate, it seemed like an awesome idea to have him host the occasional (😅) podcast with amazing guests from the world of AI. Now look at where we are & we just hit episode 150(!!!)
I think we can all agree that building a playable game is one of the coolest ways to demonstrate what a new model is capable of. Much more exciting than another benchmark.
I wanted to test Fable 5.2's quality with one-shot prompts without human feedback.
Everything in this game is from scratch: models, sounds, textures. ~$550 at API pricing, ~2.7M output and 445M input tokens, heavily cached. Took 8 hours!
Play it here: claude.ai/artifact/BGY1SztrA…
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Visibility analytics tools are slowly being killed by OpenAI and Google.
ChatGPT is building an analytics tool to "track how often your business is mentioned in ChatGPT conversations." It measures both impressions and clicks: number of times a business appeared in ChatGPT responses and number of clicks on links to their website. It tracks those events daily and shows them as a chart.
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Visa tested 22 AI models on shopping tasks. They failed 42.8% of the time.
Even more interesting: 54% of failed runs still ended in a purchase.
The agents either recommended products that didn't meet customer requirements or made decisions without uncovering all those requirements.
Getting agents to buy is one thing. Getting them to buy correctly is another.
Link: fortune.com/2026/11/05/ai-ag…
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David Mataciunas retweeted
From today, Works in Progress is now in stock at Barnes & Nobles nationwide across America.
We're in 570 stores in 49 states*, including the flagship stores at Union Square & Fifth Avenue in NYC; Georgetown, DC; State Street, Chicago; and The Grove, Los Angeles.
We're also now in Hudson News outlets across most major US airports, and the B&Ns at San Francisco Airport.
If you tweet (or LinkedIn/Insta post) a photo of a copy of Works in Progress outside any of these stores, share the post with me or @WorksInProgMag via DM and we'll send you a free tote bag as a thank you. If you're a subscriber already, feel free to do it with own copy!
You can see a full map of Barnes & Noble stockists here, and enter your Zip code to find your nearest store.
*Sorry, Wyoming, we'll get to you!
worksinprogress.co/barnes-no…
Great insights!
So how can Astra read neural network weights? A thread 🧵
Weights of a deep NN are famously opaque, with one exception: the first and last layers, which map to known inputs and outputs. Is that what Astra is reading?
Post by @rikiyatakehi et al: teapawt.net/rikiyatakehi/status/21… [1/10]
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Agentic commerce and AI shopping will become part of how we buy things, especially high-consideration products. As shoppers, we want to feel confident that we're making the right choice. That's becoming harder when the market is flooded with cheap copies, fake reviews, and even established brands seem to be compromising on quality.
I think this creates a huge opportunity for smaller brands that make genuinely great products but struggle to compete with the marketing budgets and distribution of bigger players. If AI agents can evaluate products based on actual quality, customer experiences, and how well they meet someone's needs rather than just brand recognition, we could see a real shift in which brands get discovered and trusted.
We also tend to talk about agentic commerce mainly from a payments perspective: how AI agents will complete transactions on our behalf. Yes, that's important, but getting payments right is only one part of the challenge. Building enough trust for people to let AI make purchasing decisions will take much longer.
To me, the bigger opportunity is everything that happens before the payment. How agents discover products, compare alternatives, verify claims, understand quality, and ultimately help people make better decisions.
Agentic commerce is much more than payments.
re: agentic shopping
I have NEVER in my life heard so much hype and discussion about a tech/product experience that basically does not work at all for me.
I feel like I’m using theranos
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I hate the memory limitations of some AI providers. If you want some creativity, memory is always a bottleneck.
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The possibility of moving from optimizing models through gradients to reasoning directly about their weights is fascinating. Still early, but this could become an important building block for recursive self-improvement.
We asked GPT-6 Astra to edit Qwen3.5-0.8B weights to improve math.
It directly changed only 0.016% of weights, fixing 0.8B's reasoning loops & improving math up to 6x and even instruction following 3x, without gradients or training.
We call this Weight-Space Programming: frontier LLMs can now natively read/write neural network weights! 🧵
Blog: rikiyat.github.io/blog/weigh…
Readers added context they thought people might want to know
LLM was given weights explicitly as text in prompt and used code/forward passes (per authors' logs) to ablate Qwen looping direction, a known thinking-mode issue per model card. Primarily fixed repetition in that mode, not general 'natively' improving weights/math.
rikiyat.github.io/blog/weight-sp…
github.com/RikiyaT/lm_und…
huggingface.co/Qwen/Qwen3.5-0…
huggingface.co/RikiyaT/Qwen3.…
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Trust is the most important part of Agentic Commerce
thank you to everyone in the past week who took the time to share their views and observations on the space. understanding the broader ecosystem is critical to scaling agentic commerce.
can't wait for us all to build a future we can be proud of!
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The interesting part isn't the 20K parameters. It's that reasoning models are starting to treat neural network weights as something they can understand and program directly, rather than optimize through training.
i've reproduced the results from the MIT blog post today on weight-space programming. but one additional result i have to add: this is a new, step-change emerging capability that's appeared in just the latest set of models.
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David Mataciunas retweeted
This is why consumer agents are working now 👇 (OpenAI's new LifeVal benchmark)
Yes, ChatGPT will capture a lot of this value - but there is a LOT of room for more focused products as well
Agentic commerce is growing! We saw an even bigger revenue uplift for our clients at @m11labsai
Shoppers sent by AI show up ready to buy
AI-referred shoppers vs. other online shoppers:
- Conversion +60%
- Revenue per visit +53%
- Bounce rate -34%
Charts of the Week: a16z.news/p/charts-of-the-we…
Do scaling laws apply to AI agent swarms?
We know how LLM performance scales with compute, data, and model size. But what happens when we scale the number of agents instead?
Does a swarm of 1,000 agents outperform 100, or do communication overhead and coordination failures eventually outweigh the benefits?
Could there be entirely new scaling laws for collective intelligence?
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Will we even need GTA 7?
Yesterday, Google DeepMind announced Genie 4, a new world model that can generate interactive worlds in real time. You can explore these worlds, change the environment, and interact with characters that move, react, and speak.
We've been waiting years for GTA 6, probably one of the biggest entertainment releases of 2026. But Genie 4 got me thinking: if GTA 7 takes another 5–10 years to develop, will we even need games built the traditional way?
World models could completely change how games are created. Genie 4 is still experimental and can only maintain coherent worlds for a few minutes, but the progress is incredible. Imagine being able to generate entire playable worlds, characters, and stories instead of spending a decade building them.
Maybe the next GTA won't take another 10 years to create. Maybe we'll be generating our own games long before GTA 7 arrives.
What do you think?
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