Retailgentic | Consumer Behavior & Retail Trend

We pick up where we left off a year ago and get into what has changed since. Ekta walks us through how e.l.f. is structuring its AI work, what kind of person they’re hiring to do it, and how a public company makes the case for investing before the ROI is fully provable. The live audience jumps in with some sharp questions along the way.
We close by looking ahead to what Ekta thinks brands need to get ready for in the next 12 months. Hit play.

Highlights: 
𝗟𝗲𝘁 𝗶𝘁 𝗿𝗶𝗽 𝗼𝗿 𝗹𝗼𝗰𝗸 𝗶𝘁 𝗱𝗼𝘄𝗻: Ekta says companies tend to pick one of two AI philosophies, giving it to everyone or locking it down. e.l.f. has tried to do both so it doesn't kill innovation.
𝗧𝗵𝗿𝗲𝗲 𝗽𝗼𝗱𝘀: e.l.f. runs three AI pods covering agentic commerce/growth, intelligent operations, and the human-agent workforce. Each pod owns data, change management, integrations, and training. The agentic growth roles are now being hired as dedicated full-time positions across e.l.f.'s brands.
𝗡𝗼 𝗼𝗻𝗲 𝗵𝗮𝘀 𝗺𝗲𝗮𝘀𝘂𝗿𝗲𝗺𝗲𝗻𝘁 𝗳𝗶𝗴𝘂𝗿𝗲𝗱 𝗼𝘂𝘁: "Anybody that tells you they have figured it out haven't figured it out." Ekta measures readiness instead, and focuses on the products where e.l.f. has the right to win.
𝗥𝗲𝗮𝗹 𝗽𝗿𝗼𝗺𝗽𝘁𝘀, 𝗳𝗶𝗻𝗮𝗹𝗹𝘆: Jason points out that most visibility tools rely on synthetic prompts. Google's new Agentic Insights tab in Merchant Center is the first look at what real people actually type, at least on Google surfaces.
𝗕𝗮𝗱 𝗱𝗮𝘁𝗮 = 𝗯𝗮𝗱 𝗔𝗜: Ekta's case for fixing the foundation first. If you don't solve the plumbing, you can't scale.
𝗘𝘅𝘁𝗲𝗿𝗻𝗮𝗹 𝘃𝗼𝗶𝗰𝗲𝘀 𝗹𝗶𝗴𝗵𝘁 𝘁𝗵𝗲 𝗳𝗶𝗿𝗲: About 14 months ago e.l.f. brought in an outside search expert, and that put "fire in the belly." 
𝗦𝘂𝗽𝗽𝗹𝘆 𝗰𝗵𝗮𝗶𝗻 𝗶𝘀 𝘁𝗵𝗲 𝘀𝗹𝗲𝗲𝗽𝗲𝗿: e.l.f. has invested in Lyric for forecasting and demand planning. Its planners "are actually now engineers," and AP, AR, payroll and inventory teams are building their own AI workflows.
𝗔𝗴𝗲𝗻𝘁 𝗿𝗲𝗹𝗮𝘁𝗶𝗼𝗻𝘀𝗵𝗶𝗽 𝗺𝗮𝗻𝗮𝗴𝗲𝗺𝗲𝗻𝘁: Ekta's prediction is that Meta wins the agent shopping race. She says brands need to put agent identity in place now, so they know which agent is arriving and which customer it represents. It's the next CDP/CRM-style plumbing project.
Huge thanks to Ekta for running over from the main stage, and to our live audience at RetailClub for the great questions. Enjoy the conversation.

Timestamps:
01:17 Live from Retail Club: meet Ekta Chopra & co-host Jason Goldberg
02:04 One-year reunion and a new title
02:38 e.l.f. Beauty: a house of brands, 30 straight growth quarters
03:19 Eyes, lips, face… and the Jeopardy! moment
03:43 Ekta's role as Chief Technology & AI Officer
04:02 From the main stage: let it rip or lock it down
05:04 e.l.f.'s three AI pods
06:14 Making agentic growth a full-time job
07:00 Who do you hire for agentic commerce?
08:33 Jason's "you've reached your quota" hiring hack
08:48 Selling AI investment to a public company board
10:06 Measuring readiness when no one has measurement figured out
11:31 "My board member couldn't find our product"
13:06 Synthetic prompts vs. real prompts: Google's Agentic Insights
14:00 Audience Q: build vs. buy
14:52 Where to start: external voices and fire in the belly
16:23 Foundation first: bad data equals bad AI
17:47 Back office, supply chain, and Lyric
19:52 Personal shopping assistants and agents
20:59 Serving a house of brands and working with retail partners
22:55 Audience Q: is governance keeping pace?
24:50 Next 12 months: Meta, agent identity & agent relationship management
26:20 Wrap-up 
👉 Connect with Ekta: https://www.linkedin.com/in/ektachopra/
👉 Learn more about e.l.f. Beauty: https://www.linkedin.com/company/e-l-f-beauty/
🧠 Want to stay ahead in AI commerce? Subscribe and follow along:
📰 Subscribe to the free Substack: retailgentic.ai
📺 Watch episodes on YouTube & Subscribe for updates: https://www.youtube.com/@Retailgentic

This week is a research deep dive. ReFiBuy commissioned a behavioral study of how real people shop inside ChatGPT and Google's AI Mode, and Scot sat down with the researcher who ran it to walk through what was found. The full study is published today This is the conversation behind the numbers.
Highlights: 
𝟴𝟰% 𝗼𝗳 𝗰𝗵𝗼𝗶𝗰𝗲𝘀 𝘀𝘁𝗮𝗿𝘁 𝗼𝗻 𝗮 𝗰𝗮𝗿𝗱: About 84% of product choices in the study came from a product card. That's 83.7%, and Scot rounds it up "if you allow."
𝗣𝗼𝘀𝗶𝘁𝗶𝗼𝗻 𝘁𝗵𝗿𝗲𝗲 𝗯𝗲𝗮𝘁𝘀 𝗽𝗼𝘀𝗶𝘁𝗶𝗼𝗻 𝘁𝘄𝗼: The first card wins by a wide margin, with roughly 43% of picks. But card three outperformed card two in both ChatGPT and AI Mode. Eric's take is that "it's not really a ranking." Scot's guess is curiosity, because card three is only partly visible in the carousel.
𝗣𝗶𝗰𝘁𝘂𝗿𝗲𝘀 𝗯𝗲𝗳𝗼𝗿𝗲 𝗽𝗮𝗿𝗮𝗴𝗿𝗮𝗽𝗵𝘀: About 75% of shoppers skipped the AI's written answer and went straight to the product cards. They'd come back to the text later, but only as a second step.
𝟵𝟴% 𝗼𝗳 𝗾𝘂𝗲𝗿𝗶𝗲𝘀 𝘁𝗿𝗶𝗴𝗴𝗲𝗿𝗲𝗱 𝗰𝗮𝗿𝗱𝘀: Purchase-intent prompts like "I want to buy X today" brought up product cards almost every time.
𝗧𝗵𝗲 𝗳𝗶𝗿𝘀𝘁 𝗼𝗳𝗳𝗲𝗿 𝘄𝗶𝗻𝘀: When shoppers had to click out to a retailer, they leaned even harder toward the first offer than toward the first product card. The likeliest path is first card, first offer.
𝗔𝗱𝘀 𝘁𝗵𝗮𝘁 𝗽𝗲𝗼𝗽𝗹𝗲 𝗮𝗰𝘁𝘂𝗮𝗹𝗹𝘆 𝗹𝗶𝗸𝗲: About 6 in 10 free-plan users saw ads or sponsored content on a task. 71% rated them at least as useful as Google search ads, and about 35% said an ad influenced what they considered buying.
𝗧𝗵𝗲 𝗿𝗲𝘃𝗶𝗲𝘄𝘀 𝗽𝗮𝗿𝗮𝗱𝗼𝘅: Reviews were the main reason for a pick only 2% of the time. Afterward, about 75% said reviews mattered. Scot's explanation is that nobody reads them, but everyone takes the 4.8 over the 3.2.
𝗧𝗿𝘂𝘀𝘁, 𝘂𝗻𝘁𝗶𝗹 𝗶𝘁 𝗯𝗿𝗲𝗮𝗸𝘀: Eric says the biggest surprise after two years of these studies is "the extent to which people trust, even when they say they don't." A mismatched price or a wrong spec breaks that trust quickly.
𝗧𝗵𝗲 𝗸𝗲𝘆𝘄𝗼𝗿𝗱 𝗷𝗮𝗶𝗹 𝗲𝗿𝗮: Scot compares 20 years of chasing "men's running shoe" on Google with a world where shoppers let the AI choose for them.
𝟰𝟬 𝗽𝗲𝗼𝗽𝗹𝗲, 𝗺𝗼𝗻𝘁𝗵𝘀 𝗼𝗳 𝘄𝗼𝗿𝗸: The study had 40 remote participants doing 30-minute think-aloud sessions on screen recordings. The team logged small behaviors down to seconds spent and scroll percentages.
Scot came out of the Amazon era believing the buy box was everything, and this study tells him ChatGPT has one too. Enjoy the conversation.
Timestamps:
01:57 Meet Eric Van Buskirk, Clickstream Solutions
02:15 Why ReFiBuy commissioned this study
02:48 Eric's background: SEMrush, Backlinko, Kevin Indig
04:05 Stated preference vs. observed behavior
06:05 How a behavioral study works
08:30 Why 40 people is enough
10:20 Who took part, and who got cut
11:55 The Amazon buy box and agentic commerce optimization
14:25 Finding #1: Pictures beat paragraphs
16:40 Card position: #1 wins, #3 beats #2
18:55 84% of choices come from a product card
20:35 Google SEO vs. AI: the "keyword jail" era
23:40 When do shoppers click out?
25:30 75% skip the text and go straight to the cards
27:25 Offer cards: the first offer dominates
30:20 Ads in ChatGPT: what shoppers really think
35:50 Trust and the reviews paradox
40:25 When bad data breaks trust
41:35 Where to get the study and work with Eric
44:55 Wrap-up
👉 Connect with Eric: https://www.linkedin.com/in/vanbuskirk/
👉 Learn more about Clickstream Solutions: https://clickstream.cc/
🧠 Want to stay ahead in AI commerce? Subscribe and follow along:
📰 Subscribe to the free Substack: retailgentic.ai
📺 Watch episodes on YouTube & Subscribe for updates: https://www.youtube.com/@Retailgentic

Danny Smith is the Global Agentic Commerce Solutions Lead at Stripe, where he runs technical go-to-market (think pre-sales architect, not engineering) for Stripe’s agentic commerce products. One of his first projects was adding the payments layer to Amazon’s Rufus shopping assistant, and three years ago he got on stage at Stripe Sessions to talk about agentic commerce. 

We recorded this one live from day two of RetailClub in Huntington Beach. It was a little overcast, which after a day of baking in the sun, we didn’t mind at all. Jason Goldberg joined me as co-host, and we grabbed Danny between meetings. It was his first time at the show.

Danny’s a first-timer, both on the pod and at RetailClub. This week’s episode is a product deep dive: Stripe has been shipping agentic commerce products at a pace that makes three months ago feel like ancient history. Danny walks us through what’s live, what launched last Monday, and what’s coming soon, including how the checkout Scot kept seeing inside Meta’s new Muse app actually works.

Jason brings the payments-industry history. It goes back to when card-not-present transactions were illegal and runs up to Stripe’s jump from developer darling to incumbent. We also get into the thing that’s still breaking agentic commerce today, and it isn’t the agents.

Along the way there’s a hallucinating agent, a leather jacket, and a Cheeky Pint swag request. Hit play.
Highlights 
𝗟𝗶𝗻𝗸 𝗪𝗮𝗹𝗹𝗲𝘁 𝗳𝗼𝗿 𝗔𝗴𝗲𝗻𝘁𝘀: A skill you teach any agent (Claude, GrokBot, your homebrew Hermes agent) so it can pay “in a guarded and secure manner.” Details at link.com/agents.
“𝗬𝗼𝘂𝗿 𝗔𝗣𝗜 𝗰𝗵𝗮𝗻𝗴𝗲𝗱 𝗺𝘆 𝗹𝗶𝗳𝗲”: Developers really do stop Danny at conferences to ask for a photo. Stripe’s founders’ mantra: “Let’s win all startups, and then let’s go win them again.”
𝗢𝗽𝗲𝗻 𝗵𝗲𝗮𝗿𝘁 𝘀𝘂𝗿𝗴𝗲𝗿𝘆: Changing payments at an enterprise is “like open heart surgery.” Jason adds that it’s open heart surgery while you’re running a marathon.
𝗪𝗼𝗿𝗹𝗱’𝘀 𝗳𝗶𝗿𝘀𝘁 𝗮𝗴𝗲𝗻𝘁𝗶𝗰 𝘁𝗼𝗸𝗲𝗻: Stripe’s shared payment tokens launched with OpenAI, and Etsy was the first merchant. Link wraps them as a single-use virtual card capped at the amount you budgeted, so the merchant doesn’t have to be on Stripe.
𝗦𝘁𝗿𝗶𝗽𝗲 𝗖𝗵𝗲𝗰𝗸𝗼𝘂𝘁 𝗳𝗼𝗿 𝗔𝗴𝗲𝗻𝘁𝘀: Launched last Monday and built on WebMCP, it makes human checkouts machine-readable at the same time. Stripe merchants on hosted checkout or invoices get it with no extra work.
𝗧𝗵𝗲 𝗪𝗲𝗯𝗠𝗖𝗣 𝗻𝘂𝗺𝗯𝗲𝗿𝘀: 42% fewer tokens burned, 38% fewer tool calls, and 39% faster checkout. “Three seconds is annoying to a human, 800 milliseconds is beyond annoying to an agent.”
𝗗𝗼𝘂𝗯𝗹𝗲𝗱 𝘄𝗲𝗯 𝘁𝗿𝗮𝗳𝗳𝗶𝗰: Through the Agentic Commerce Suite (ACS), some merchants have doubled their web traffic in three or four months just by getting their catalogs in front of agents. Instant checkout on Gemini is expected around late October.
𝗗𝗼𝗼𝗿𝗺𝗮𝗻 𝘃𝘀. 𝗯𝗼𝘂𝗻𝗰𝗲𝗿: Most merchants are bouncers that block all bot traffic, and bots were already 53% of internet traffic in 2024. Stripe is working on protocols to tell good bots from bad ones.
Stripe is building both sides of the agentic transaction, and Danny is the one out there getting retailers across the line. Enjoy the conversation.

Timeline

00:27 Welcome to Retailgentic
01:44 Live from Retail Club, day two
02:05 Meet Danny Smith, Stripe
02:38 From cloud architect to Stripe
03:48 Adding payments to Amazon's Rufus
04:55 Stripe launches agentic commerce
06:08 Jason on payments history & developer-first Stripe
07:40 "Your API changed my life"
08:40 Enterprise payments = open heart surgery
09:05 Meta Muse and the Link checkout
10:25 What is Link Wallet for Agents?
11:00 The weekend Meta scramble
12:20 GrokBot, Instinct & the pipeline
13:55 How Link works at non-Stripe merchants
14:35 The model airplane story
15:40 The world's first agentic token
16:05 Stripe Checkout for Agents & WebMCP
17:10 Two sides of the same coin
17:55 Agentic Commerce Suite & doubled traffic
20:55 WebMCP numbers: 42% fewer tokens
22:10 The leather jacket that got blocked
23:50 Doorman vs. bouncer
25:10 Danny's first Retail Club
26:30 Wrap
👉 Connect with Danny: https://www.linkedin.com/in/danny-r-smith/
👉 Learn more about Stripe: https://stripe.com
🧠 Want to stay ahead in AI commerce? Subscribe and follow along:
📰 Subscribe to the free Substack: retailgentic.ai
📺 Watch episodes on YouTube & Subscribe for updates: https://www.youtube.com/@Retailgentic

This week’s episode is a platform deep dive with one of the longest-tenured companies in e-commerce. Elastic Path has been building commerce software for 26 years and Bryan is now steering the company straight into the agentic era. 
It’s part founder-journey (craft brewing to CEO is not a typical path), part product deep dive, and part industry-shift conversation about what AI does to the economics of running a commerce platform.
Highlights: 
𝗙𝗿𝗼𝗺 𝗯𝗿𝗲𝘄𝗲𝗿 𝘁𝗼 𝗖𝗘𝗢: Bryan spent eight years as a professional brewer, with an actual brewing degree, at a brewpub across from Fenway Park. "Everything I learned in my career that really moved the needle for me, I learned as a brewer."
𝟮𝟲 𝘆𝗲𝗮𝗿𝘀 𝗼𝗳 𝗰𝗼𝗺𝗺𝗲𝗿𝗰𝗲: Elastic Path's claim to fame was building the store for the Vancouver 2010 Winter Olympics, the birth of its self-managed commerce product.
𝗧𝗵𝗲 $𝟱𝟬𝟬𝗞 𝘂𝗽𝗴𝗿𝗮𝗱𝗲, 𝗸𝗶𝗹𝗹𝗲𝗱: Elastic Path built an AI updater so one developer can upgrade a self-managed platform in about two weeks, replacing what used to be a half-million-dollar annual project.
𝟭𝟬,𝟬𝟬𝟬 𝘃𝗮𝗿𝗶𝗮𝘁𝗶𝗼𝗻𝘀: where typical platforms cap out at 250 variations per item, Elastic Path supports 10,000, plus bundles of up to 1,500 items.
𝗦𝗶𝘅 𝘄𝗲𝗲𝗸𝘀 𝗮𝗻𝗱 𝟭𝟬𝟬 𝗴𝗿𝗮𝗻𝗱: Bryan's prediction… AI takes re-platforming from a 6-month-to-2-year, $500K–$3M digital transformation down to a setup fee. "That's the place we're gonna see the biggest impact of AI in commerce."
𝗧𝗵𝗲 𝟴𝟬-𝗽𝗮𝗴𝗲 𝗣𝗗𝗙: in a world of AI discovery, every product needs the equivalent of an 80-page PDF of data to train the LLM on when to recommend it. (Scot's line, which Bryan says he "steals with credit" as often as he can.)
𝗣𝗿𝗼𝗼𝗳 𝗶𝗻 𝗻𝘂𝗺𝗯𝗲𝗿𝘀: a UK custom greeting-card seller saw conversion jump 40% almost immediately after adopting Elastic Path's checkout
𝗡𝗼𝗯𝗼𝗱𝘆 𝘄𝗮𝗻𝘁𝘀 𝗰𝗵𝗮𝘁𝗯𝗼𝘁𝘀: customers are asking about UCP and ACP, discovery, and the long tail, not chatbots. 
𝗪𝗵𝗲𝗿𝗲 𝘁𝗵𝗲 𝗿𝗼𝗮𝗱𝘀 𝗮𝗿𝗲 𝘄𝗲𝗹𝗹-𝗽𝗮𝘃𝗲𝗱: Bryan's framework for where AI lands first… well-understood patterns like checkout, front ends, and reorders, not judgment-heavy edge cases.
Bryan is a product guy after our own heart, and this one gets satisfyingly deep, from CPQ to protocols to the future of re-platforming. Enjoy the conversation.
Timestamps:
03:20 Welcome Bryan + podcasting since 2009
04:05 Internet Retailer booth memories
04:55 From craft brewing to software
07:35 The Acquia and Drupal years
08:20 Moltin, Neural Magic, joining Elastic Path
11:05 Elastic Path history: the Olympics store
13:20 Two products: SaaS + self-managed
13:45 The AI updater: killing the $500K upgrade
14:50 80 people, profitable, constraints breed innovation
17:00 Customer base and the B2B focus
19:15 CPQ, PXM, and 10,000 variations
22:45 Serena & Lily case study
24:10 The MACH Alliance backstory (spicy)
29:55 Vibe coding the front end + Shopify as fintech
33:20 AI re-platforming: six weeks and $100K
39:00 The ReFiBuy partnership + the 80-page PDF
40:55 AI roadmap: workflows, promotions, analytics
43:20 B2B agentic commerce and EDI
47:10 UCP, ACP, and the long tail
49:05 Predictions: where the roads are well-paved
51:20 What's next for Elastic Path

👉 Connect with Bryan: https://www.linkedin.com/in/bhouse/
👉 Learn more about Elastic Path: https://www.elasticpath.com/
🧠 Want to stay ahead in AI commerce? Subscribe and follow along:
📰 Subscribe to the free Substack: retailgentic.ai
📺 Watch episodes on YouTube & Subscribe for updates: https://www.youtube.com/@Retailgentic

This week’s episode is a little different. We’ve has been noticing vibe-code platforms quietly showing up all over digital retail… at trade shows, in conversations with retailers and brands, and on the platforms’ own commerce pages. So we went to the source. 
This is a platform deep dive with Vercel, the enterprise company behind v0 and Next.js, on what a “vibe coding” company is actually doing in our world of commerce, and it turns out the answer is: a lot more than you’d think.
Highlights 
𝗧𝗵𝗲 𝟭𝟬𝟬-𝗺𝗶𝗹𝗹𝗶𝘀𝗲𝗰𝗼𝗻𝗱 𝗺𝗮𝘁𝗵: A Deloitte Digital + Google study cites clients found 100ms of load-time reduction drives a 7–8% lift in e-commerce conversion. “If the thing is faster, you’re gonna convert more. It’s just math.”
𝗛𝗲𝗹𝗹𝘆 𝗛𝗮𝗻𝘀𝗲𝗻’𝘀 𝗻𝘂𝗺𝗯𝗲𝗿𝘀: The Kontoor Brands-owned retailer cut load times from 2.5 to 1.5 seconds on Vercel, grew conversion 20% year over year, doubled its A/B test velocity, and blew away its Black Friday/Cyber Monday plan.
𝗧𝗵𝗲 𝗰𝗼𝗰𝗸𝘁𝗮𝗶𝗹-𝗽𝗮𝗿𝘁𝘆 𝗽𝗶𝘁𝗰𝗵: Vercel in three phrases… a developer tools company, an infrastructure provider, and an open-source software factory.
𝗬𝗼𝘂’𝘃𝗲 𝗮𝗹𝗿𝗲𝗮𝗱𝘆 𝘂𝘀𝗲𝗱 𝗩𝗲𝗿𝗰𝗲𝗹: walmart.com and target.com run on Next.js, and Under Armour, Crocs, Buck Mason, PetSmart, McAlister’s, DeWalt, Clorox, and even Meta.ai are Vercel-delivered applications.
𝗡𝗼𝘁 𝗮 𝗦𝗵𝗼𝗽𝗶𝗳𝘆 𝗸𝗶𝗹𝗹𝗲𝗿: Vercel doesn’t do product catalogs, inventory, or order management. It’s the storefront layer on top of your commerce platform. “We help you own your storefront and own your destiny.”
𝘃𝟬 𝗺𝗲𝗲𝘁𝘀 𝗦𝗵𝗼𝗽𝗶𝗳𝘆: v0 is now deeply integrated with Shopify, so you can customize your storefront in plain English 
𝗧𝗶𝗺𝗲𝗹𝗶𝗻𝗲𝘀 𝗵𝗮𝗹𝘃𝗲𝗱: Custom storefront projects that were planned for a year are landing in six months, six-month plans in three.
𝗧𝗵𝗲 𝗮𝗴𝗲𝗻𝘁 𝗰𝘂𝘀𝘁𝗼𝗺𝗲𝗿: Next.js 16 was built to be readable and manipulated by Cursor, Claude, and Codex, “now we have this new customer, this agent customer, who wants to interact with your code base.”
𝗧𝗵𝗲 𝗹𝗶𝗴𝗵𝘁-𝗯𝘂𝗹𝗯 𝗺𝗼𝗺𝗲𝗻𝘁: Jaime’s conversion story: feeding 50-page client 10-Ks into ChatGPT in early 2023 and realizing everything about go-to-market, and the factories that make software, was about to change.
This one really lifted the veil on what the vibe-code platforms are actually doing in retail, and I think we’re just seeing the tip of the iceberg. Enjoy the conversation.
Timestamps:
05:29 Welcome Jaime Sorgente
06:08 Jaime's path to Vercel: ChatGPT and 10-Ks
12:29 Utilities vs. builders
15:00 What is Vercel? The cocktail-party pitch
17:10 Why retail as a vertical
21:20 The Helly Hansen story
24:05 Vercel's other verticals: digital natives and marketing
26:45 Enabler, not competitor: where Vercel fits vs. Shopify & Salesforce
29:35 Beyond the storefront: clienteling and staff apps
30:45 Agents everywhere: Crocs, Amazon image annotation
36:05 v0 + Shopify: customize your storefront in English
37:45 Next.js 16: built for the agent customer
39:20 Custom storefront timelines, halved
40:35 Does owning your storefront de-risk replatforming?
42:20 The 100-millisecond study
44:30 The compounding effect: 4X feature velocity
46:45 Next.js explained: the stage manager analogy
52:20 Framework-defined infrastructure
54:30 Vercel vs. Lovable, Replit, and Base44
58:15 Where to learn more + wrap-up

👉 Connect with Jaime: https://www.linkedin.com/in/jsorgente/
👉 Learn more about Vercel: https://vercel.com/for/retail
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