이 에피소드에 관해
This one is a build deep dive. Daniel has spent eight years on the same problem, and the answer has changed shape three times along the way: a consumer app in 2018, a shoppable recipe platform in 2023, and now a conversational shopping assistant running inside grocers’ own sites.
We go deep on the plumbing here: product catalogs, ontologies, eval systems, model selection, retail media, and what an agent does when a shopper types “taco night.” If you like knowing how these things actually work under the hood, this is your episode.
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Highlights:
- 𝗧𝗵𝗲 𝗻𝘂𝗺𝗯𝗲𝗿𝘀: Live in over 700 stores, reaching over 10 million shoppers, with the number of locations set to double before the end of the year. The consumer app has over a million users.
- 𝟰𝟭 𝗱𝗮𝘆𝘀 𝗰𝗼𝗻𝘁𝗿𝗮𝗰𝘁 𝘁𝗼 𝗹𝗶𝘃𝗲: A one-line JavaScript install that reuses the retailer’s existing catalog, add-to-cart, analytics, and retail media. National scale in six weeks.
- 𝗦𝗲𝗮𝗿𝗰𝗵 𝗮𝗻𝗱 𝘀𝗲𝗹𝗲𝗰𝘁 → 𝗿𝗲𝘃𝗶𝗲𝘄 𝗮𝗻𝗱 𝗮𝗰𝗰𝗲𝗽𝘁: Daniel’s framing for the whole shift. The old era: you search one thing, you select it. The new one: the agent assembles a solution and you approve it.
- 𝗧𝗵𝗲 𝗲𝘃𝗮𝗹 𝘀𝘆𝘀𝘁𝗲𝗺: Thousands of test scenarios with grading criteria aligned to each retailer’s merchandising principles, run tens or hundreds of times to get a distribution of responses.
- 𝗧𝗵𝗲 𝗳𝗶𝘀𝗵 𝗿𝘂𝗹𝗲: Retailers write procedures the agent pulls when a scenario matches. One of Daniel’s favorites: if you’re cooking fish today or tomorrow, it recommends fresh. If it’s later in the week, frozen.
- 𝗧𝗿𝗮𝗶𝗻𝗶𝗻𝗴 𝗮 𝗻𝗲𝘄 𝗱𝗶𝗴𝗶𝘁𝗮𝗹 𝗲𝗺𝗽𝗹𝗼𝘆𝗲𝗲: Onboarding is essentially an interview with the business. What are your values? How do you respond? What are your merchandising principles? That becomes the agent’s identity and personality.
- 𝟭,𝟬𝟬𝟬 𝗙𝗼𝘂𝗿𝘁𝗵 𝗼𝗳 𝗝𝘂𝗹𝘆 𝗯𝘂𝗻𝗱𝗹𝗲𝘀: Instead of one holiday carousel every shopper sees, merchant teams define ~20 axes — price, dietary needs, brand preference — and an agentic process generates permutations personalized against transaction history.
- 𝗔𝗜 𝗖𝗵𝗲𝗳𝘀 𝗼𝗻 𝗧𝗶𝗸𝗧𝗼𝗸: Long before ChatGPT, Cooklist ran a TikTok series generating recipes with GPT-2 and early GPT-3. The models got good at basic recipes so fast that the fun moved to challenging them to be creative.
Daniel is one of those founders who has clearly built the thing himself, and it shows in the answers. We learned about a thousand things from this one. Enjoy the conversation.
Timestamps:
02:57 Welcome Daniel Vitiello, CEO & co-founder of Cooklist
03:10 Grocery, CPG, and retailer-hosted agents: the pod's favorite topics
04:46 The $1 check and the handwritten letter for loyalty data
05:46 Why 2017 was the moment
06:12 Inside the Cooklist app: home inventory and the AI chef
07:35 AI as the thread: Kurzweil, GPT-2, and the AI Chefs TikTok series
09:37 B2C to B2B, and the synergies of running both
12:05 The cat food problem
13:34 The core identity system: hummus, three ways
15:58 Search and select vs. review and accept
16:23 The spark for B2B: Target, Techstars, and saying no
18:45 Recipe commerce and meal-pairing merchandising
20:19 Funding: RevTech, Mercury Fund, and profitability
21:56 Freemium, pro, and advertising in the app
22:48 700 stores, 10 million shoppers
24:28 The flagship deployment: live in 41 days
25:56 Ontology, context engineering, and interviewing the retailer
27:03 Non-determinism and the eval system
29:06 Entry points: sparkles, suggested prompts, and PDP workflows
31:01 How the catalog and inventory get in
33:41 Procedures: the weekly flyer and the fish rule
35:55 Cost, speed, and the token-efficient stream
37:38 Model agnostic: scoring Opus against Sonnet
38:15 Instacart, Storefront Pro, and winning head-to-head
39:47 Retail media and Criteo
40:22 Agentic search and the "taco night" problem
42:02 Agentic merchandising: 1,000 Fourth of July bundles
42:55 Proactive carts, and the 50% who finish in the store
43:43 Smart fridges and forecasting demand
44:44 Where to find Daniel
👉 Connect with Daniel: https://www.linkedin.com/in/dkvitiello/
👉 Learn more about Cooklist: https://cooklist.com/
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