If you’re new, welcome! If you’re a regular, thanks for being here as we navigate this AI shift in eCommerce. I share what I’m testing and what’s actually moving the needle. Where’s the vault you ask? Every previous edition is saved here.

In this edition (shortcuts):
🗞️ The Nano Banana for Video Is Here💥🚀
Would You Let AI Run Your Ad Account Live? 🛠️
Alexa now enables AutoBuy
News Worth Reading
AI Related Events worth Tracking
SellerLingo Launch

Remember the Nano Banana moment?

Last August it was a fun toy. By November it was Pro. By February it was the default behind almost every AI product image you saw on Amazon. The whole shift happened in six months, and the sellers who started early were generating clean A+ hero shots while everyone else was still asking "but is it any good yet."

Last week, the same thing happened for video.

Google announced Gemini Omni at I/O on May 19. The first model, Gemini Omni Flash, is already rolling out. It accepts any input (image, audio, video, text) and generates video back. Watch the launch reel here: Introducing Gemini Omni.

But the announcement is not the story. The story is what it does.

Every AI video tool before this had the same fatal flaw for product content. You'd render a clip, tweak the prompt, render again, and your product would morph. The bottle was teal, then blue, then a slightly different bottle. The hero became a stranger between edits. You could not finish a video without watching the product drift off model.

Omni edits like a conversation. Each instruction builds on the last.

Google's signature demo is a violinist. Across three rounds of edits, the face, the posture, and the way she holds the instrument all stay locked. Change the environment, swap the lighting, push in for a tighter angle. The person stays the same person.

Now apply that to a product. Your hero SKU on a wood floor. "Now put it on a kitchen counter." "Now show steam rising." "Now render the whole thing as cinematic realism, then as watercolor, then as claymation." Same product. Same shape. Same label. The iteration loop finally stops fighting you.

The deeper move under the hood: you can swap a product, prop, outfit, or reference image without rebuilding the whole video. The original camera path, the contact shadows, and the surrounding scene all stay in place. That is the unlock. You change one thing at a time and the rest holds.

The story of AI product images was never "they got better." It was "the iteration loop got fast enough that you could actually finish one." That is exactly what just happened to video.

A Sponsored Brands video, a short social ad, a 6-second clip for your A+ content. Until now those required either a real shoot or a brave gamble on a fresh render every time. Omni reduces all of that to a chat window where your product holds together.

There are honest caveats. The full tool runs on the paid Google AI Plus, Pro, and Ultra tiers in the Gemini app and Google Flow. The free door is YouTube Shorts and the YouTube Create app. The developer API is "coming weeks." Every output is watermarked with SynthID. And the model is days old, so verify the physics on your category (liquids pouring, fabrics draping) before you trust it for paid placements.

The one thing I would do this week: watch the launch reel and look at the violinist demo with seller eyes. If your product can hold across three edits the way her face does, your video cost just dropped to a chat window.

That is the Nano Banana moment for video. It will not feel huge today. It will feel obvious in three months.

Know anyone who needs an AI-first agency to build cool, creative videos for E-commerce? Forward them this newsletter and let them connect with us at [email protected].

Time for the controversial one. Amazon shipped the Ads MCP Server (open beta since February). Connect Claude, ChatGPT, or Gemini straight to your live ad account, and just talk to it. "Pause these. Raise bids on those. Build me a new Sponsored Products campaign." It turns your sentence into API calls and does it. On the spot. 50+ tools across SP, SB, SD, DSP, and AMC.

It is genuinely impressive. It is also exactly where I get nervous.

Here is the part nobody likes to say out loud. When you chat with the MCP, the change is live the second it acts. No file to look at first. No diff. No record of what changed or why. If it misread you, the mistake is already in your account. Put two people or two sessions on the same account and you have chaos with no paper trail.

So here is what my team does instead. We connect Claude to BigQuery through the CLI, pull the numbers, and have Claude generate a bulk file based on a chat. A human reviews the file. Then we upload it. Nothing touches the account until we say so.

Two philosophies. Pick a side.

The Ads MCP (chat and it does it)
🔶 Pro: Fast. Conversational. One sentence can build a whole campaign.
🔶 Pro: Official, 50+ tools, broad coverage across every ad type.
🔶 Con: Changes go live as you chat. There is no artifact to review first.
🔶 Con: No clean audit trail. Hard to diff, hard to roll back, easy to lose the thread across sessions.

The bulk file (data, then a file, then you upload)
🔶 Pro: Complete traceability. The file is a saved, reviewable, diffable record of every change.
🔶 Pro: Nothing goes live until a human approves it. The guardrail is built in.
🔶 Con: More steps. Slower. Needs the BigQuery and CLI plumbing in place.
🔶 Con: Not the instant magic of just talking to your account.

I am firmly in the bulk file camp. The file is the guardrail. But I know sharp operators who love the speed of the MCP and happily accept the risk.

So tell me where you land. Hit reply with "chat" if you would let the MCP run live, or "bulk" if you want the file and the paper trail. I will share the split in a future issue.

A new Alexa related feature showed up. It is called Auto Buy. A shopper taps "Add to Auto Buy" on your product page, sets a max price ("$27.99 or less, the 90 day low"), a start date, and an expiry. Then they leave. When your listing hits that number, Amazon executes the purchase on their behalf. No return visit. No second decision.

Vanessa Hung was one of the people that noticed this and shared this screenshot.

The button is rolling out inside the new Alexa for Shopping experience, right next to the "Ask Alexa" prompt chips. If you haven't seen it on your own ASINs yet, go look. Some categories already have it. Others are days away.

The reason it matters: every Auto Buy rule is essentially a conditional purchase order sitting in a queue. A loyal repurchase customer can set the rule once and stop coming back to comparison shop. That has structural consequences for how you read your own search and demand data (see Voices below for two sharp takes).

For now, the only action item for you: open one of your hero ASINs and check whether the button is on the page. Knowing it is there changes how you read the rest of this issue.

Andrew Bell on the new Alexa search stack. He took apart 659 result sets and 12,000 product cards across 48 categories and concluded that "fit beats popularity" in Position 1: feature and title overlap drives 94% of top placements, not star rating alone. He also argues that Alexa generates more searches than before, not fewer, because one human request now fans out into many machine generated queries underneath. Read part one of his blueprint.

Read together, the two pieces frame the same question from opposite sides. Demand is queueing, and searches are multiplying. Which means search volume is no longer a clean read on demand. Worth thinking about before you make confident calls on what your data is telling you this quarter.

🔶 Anthropic Released Claude Opus 4.8. Sharper judgment, more honesty about its own work, and a fast mode roughly 2.5 times quicker than 4.7. Pricing stays the same.

🔶 Dynamic Workflows Lands in Research Preview. Alongside Opus 4.8, Anthropic shipped a new agentic surface for Claude Code where one task can spawn up to 1,000 parallel subagents.

🔶 Anthropic Teases "Mythos-Class" Models. Buried in the Opus 4.8 announcement: a new "Mythos" family of models is already in development. No specs, no date, but the name is on the record now.

🔶 Amazon Licenses Its AI Shopping Engine to Other Retailers. AWS launched the Agentic Shopping Assistant with Kate Spade as first customer. Same tech that drove roughly $12B of incremental Amazon sales last year is now available to competitors.

🔶 Google Ships Antigravity 2.0 at I/O 2026. Agent-first developer platform with a desktop app, CLI, SDK, and a new $100/month AI Ultra tier. Gemini 3.5 Flash is the new default model and runs roughly 4 times faster than other frontier models.

🔶 Amazon Brings Natural Language Campaign Setup to the 2026 Upfront. Full-Funnel Campaigns let advertisers spin up cross-surface campaigns (sponsored ads, streaming TV, display, audio) from a single prompt, with AI-assisted creative and audience strategy included.

May 27, 2026, Seoul
My session: Getting Ready for Conversational AI: How Rufus Is Reshaping Product Discovery. Click to read the takeaways!

15×5 Hacks Webinar, 1200+ Registrations!

Wow! So honored to be voted #4 on this hack series!

According to Nick Penev this one had the best hacks so far with 1200+ peeps who signed up for it ... 17 Amazon speakers shared 17 hacks in a short 5 minute format in 90 minutes competed for eCom Hot Sauce prize!

You can watch the full recording here: https://lnkd.in/dgJC9rXE

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