Fastest commerce marketing teams are using AI to move at unprecedented speed. Check out the latest @SuperpilotAI case study with ALICE OLIVIA's NYFW campaign 👉 superpilot.com/customers/ali…

Current crop of SOTA LLM apps are mostly single player, or parallelized D2C, whereas enterprise workflows are very commonly multi-player. Solving that requires new plumbing and will reward the winners handsomely.

Startups win because it's easier to accelerate on the right foundations. Incumbents lose when they chase shiny objects

Surprisingly good McKinsey deep dive on the agentic marketing opportunity mckinsey.com/capabilities/gr…

There's an entire universe between wanting to win and wanting not to lose.

I’m with Brian - the demise of image and video in commerce is highly overstated.

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In NYC next week for AI Agent Conf. @me if you want to meet up!

Apple's Vision Pro fiasco is even bigger when viewed from today's AI superhighway. "Who knew" that humans wanted less computer period, not a computer on their head.

iykyk

Running a frontier local LLM with high tok/sec rate really makes one look at cloud LLM latency and outages in completely new light.

Lightspeed's @buckymoore says the real opportunity in the AI app layer is in large industries far enough afield from where the model providers are today — and where the context engineering to get customer data into the model is extremely nuanced and messy. "I think this is kind of the elephant in the room right now — whether post-training open-source models combined with the unique user feedback you get from being an application provider is defensible enough." "That is going to be an inevitable challenge for any of these industries that hit a maturation point of AI adoption, like legal and software engineering have." "But on the other hand, there are some industries where they're very large, they're far enough afield from where the model providers are today — and probably will continue to be — and the context engineering to actually get the customer data into the model is just so messy. It requires going across different business functions, it requires a lot of hands-on forward-deployed engineering." "Those are the kind of companies that we get really excited about. Because I think being really good at that is not only defensible, but it also allows you to generate a feedback loop with your customers, where you hear a lot of their secrets. And those secrets allow you to feed that back into how you make your product better at the expense of anyone else playing in the space. Because if you're serving the customer, they're only serving you those secrets." "I think Palantir is a good example of this in the pre-AI era, and I think we're going to see many companies ascend in that same way."

One emergent effect of AI on vertical SaaS is an even higher degree of specialization. It’s possible to go deeper, faster on features - while competition heats up, too. In the end, the customer wins.

The #1 thing to get right is aligning the entire company to benefit from the abundant intelligence of agents. It’s a harder & bigger shift for the enterprise than mobile or cloud was - a blue ocean opportunity for startups. h/t @edsim

Copilots ➡️ Autopilots

Web search & web fetch (might be) all you need.

Wrote down a couple of quick observations from building B2B Products in the AI era igorfaletski.com/bridges-and…

Office desk game at @SuperpilotAI continues to level up asymptotically.

Old world: working on weekends to catch up & get ahead. New world: working on weekends to get around AI rate limits & make sure agents haven't stalled.