John Laramie

@levie Horizontally across #Grocery will have the biggest daily consumer level impact

This chart is a good reminder of how much opportunity there is in AI agents right now. There will be plenty of horizontal opportunities for agents, but equally many workflows that need deep domain expertise to actually make the user successful at automating the unique processes in their vertical. The template is to build agentic software that taps into proprietary data, handles the workflow in a way that bridges the user and the agent collaboration effectively, and has a deep domain-specific context engineering, and the ability to drive change management for customers. There still are huge openings in many categories.

@0xidanlevin Or the data of that human

an agent is only as good as the human behind it.

Check grocery prices, in real-time, at your local stores....coming soon to ChatGPT #carthappy #grocery

Delivery made groceries easier but didn’t fix decision-making. Shopping, in-store or online, is still archaic. Clicking. Searching. Comparing. Rebuilding. Every single week. Try @getcarthappy - the 1st AI grocery shopping agent. 8 spots left this week: carthappy.com/launch-your-ci…

No better walkthrough on agentic commerce than this recent @McKinsey piece: lnkd.in/dzJsMJZx One line really clicked with a @getcarthappy post we wrote on #grocery + agents: as agents optimize for delivered value, trust becomes the ranking signal.

#Groceries, on autopilot. One cart, automatically optimized across stores. carthappy.com

In just 14 days: 36,000 price changes across 17,000 products (average swing: 23%). One retailer. Four stores. One town. Americans shop 2–4 stores a week chasing savings. Check out @getcarthappy.

We’ve built something that’s never existed before: the first #agentic #grocery buyer - a platform that supports shoppers by deciding and checking out groceries automatically, across a single store or multiple stores, in one seamless flow. linkedin.com/feed/update/ur…

The future of #grocery isn’t faster - it’s smarter. AI agents automate everyday buying using real purchase history, shifting commerce from “look what the AI found me” to “I didn’t think about groceries and it cost less.” carthappy.com/blog/agentic-c…

@joshelman @patrickmandia Economically usefulness is the new moat.

@patrickmandia Actually you raise the just the right point. It is not about making apps every day, it is about making the simple useful personal apps that you use every day that otherwise would never exist Once you make a dashboard of them, it just needs to change when your needs change

personal software is such a fugazi. they're building tiktok-level dopamine machines that make you feel like a god while building useless throwaway apps. similar to tok, they lower the barrier to entry for creators, but i think the interest curve decays much faster than short-form video creation/consumption. how many times is bro gonna make personal software for tracking reps at the gym?

@levie Greatest layer of context on a consumer level is their purchase history. We’re extracting with extensions and using agents to combine real time grocery prices with purchase history to build the lowest cost optimized cart. Check it out @getcarthappy

Context is king for AI agents. There’s going to be a massive premium in the future on having up-to-date context for all your most important best practices, decisions, roadmap items, specs, marketing materials, and other critical knowledge across your company. People get a lot of context “for free” in a company. They know where they work, they have people next to them they work with, they can remember the rough outline of the company’s most recent quarterly goals to know if something seems good or bad to work on. AI agents, on the other hand, come in overly eager and ready to work on whatever you give them. At one moment they’re a lawyer for one company and an engineer for the next. This is why context remains absolutely critical for them to execute well on what you want. The teams and companies that take this seriously will have huge leverage and be steps ahead of those that don’t.

That’s why at @getcarthappy we're building #agentic commerce that unifies cross-store purchase history with real-time pricing - automatically creating the most optimized, lowest-cost #grocery cart for every household. carthappy.com/blog/what%E2%8…

Purchase history stands apart. It’s unaffected by ads, uninfluenced by behavioral tracking, immune to third-party data noise, and grounded in what a person or household actually buys.

Pt III: Purchase History Is the Strongest Signal in Commerce - Ads Lie. Purchases Don’t. In our final post on “What’s Missing in Agentic Commerce,” we explore why purchase history is the most powerful form of context - it’s the cleanest, most reliable signal for decision-making.

4 / It's a shame that the movie uses CGI to recreate ping pong scenes....because the matches in the movie were things that @wallygreennyc Kaz, @soundforlove, @waterslideman, @will_horowitz, and @JudahWorldChamp and I were doing every day at @wearespin.

3 / Marty's presence was something I've never experienced before in my life. He was everything NYC, yet at the same time, a masterfully dressed hustler who one needed to be reminded was still in his 70s.

1 / I was always good at ping pong but it wasn't until 2008 when I met Marty Reisman aka @martysupreme in the underground NYC ping pong scene deep in the heart of chinatown. This is where I learned the art of hustling in ping pong.

Part II - Why Real-Time Browsing Matters: carthappy.com/blog/what-s-mi… #AgenticAI

Agentic commerce works best on structured, repeatable, and price-sensitive datasets — and no purchase is more frequent or predictable than groceries. carthappy.com/blog/whats-mis…