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Using AI every day but still doing most of the work by hand? Edwin Choi, Founder & CEO of Jet Fuel Agency, explains how eCommerce teams move from basic prompting to AI agents that run, connect, and improve their own workflows.

Mr. Will and Edwin cover a three-level framework for building AI maturity, why teams should document their judgment calls before automating anything, and where agents deliver the most impact today, from competitor gap analysis to CRO testing.

KEY TAKEAWAYS

- AI adoption happens in three levels: communication (prompting LLMs well), skills (turning playbooks into repeatable processes), and agentic workflows (connected agents that trigger each other and run QA).
- Don’t automate too early. Document your team’s internal DNA, the judgment calls and strategies behind your work, so agents behave the way you intend.
- Competitor gap analysis is a strong first use case. Agents can crawl competitor ads, product detail pages, and keywords to surface opportunities.
- For CRO, combining historical test data with Microsoft Clarity session recordings shows where visitors drop off and generates new experiments.
- AI looks backward at existing data. Taste-making, the ability to anticipate trends and set a brand’s direction, becomes the most valuable marketing skill.
- Human oversight stays essential. AI prepares the data, and the strategist makes the final call.
- Measure success beyond time saved. Track output quality, employee retention, and whether the work is 10x better.

CONNECT WITH EDWIN

Website: https://jetfuel.agency/
LinkedIn: https://www.linkedin.com/in/choiedwin

Related resources from BellaVix:

https://www.bellavix.com/how-to-conduct-an-amazon-competitive-analysis/
https://www.bellavix.com/case-study/mastering-the-art-of-agency-strategy-elevating-amazon-account-performances-with-expert-techniques/

Selling on Giants is a podcast about the people, strategies, and decisions shaping eCommerce across Amazon, Walmart, DTC, and the broader digital marketplace.

#ecommerce #AIagents #AIautomation

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Holiday shopping is starting earlier, Amazon's Q4 costs are rising, and Walmart is closing the gap on fulfillment. Meanwhile, AI shopping is creating a new battle for product visibility.

In this October 12, 2026 episode of Selling on Giants, Mr. Will breaks down what Prime Big Deal Days revealed about holiday demand, the Amazon deadlines sellers cannot afford to miss, Walmart's latest marketplace moves, and why AI product cards may become the next Buy Box.

Did Prime Big Deal Days actually increase holiday demand?

U.S. online shoppers spent $9.86 billion on October 6 and 7, up 8.5% year over year, according to Adobe. That figure covers online retail broadly, not just Amazon. Will explains why pulling purchases into October isn't the same as incremental growth, and why brands must measure incremental demand and contribution margin before Black Friday.

What are Amazon's critical October deadlines for Black Friday and Cyber Monday?

Key holiday dates include October 14 for AWD arrival, October 21 for FBA minimal shipment splits, and October 28 for Amazon-optimized splits. Deal submissions close October 20, while peak fulfillment fees begin October 15 and run through January 14. These decisions can quietly erase Q4 profitability.

Are Amazon's new partial refund controls worth using?

Amazon now lets eligible FBA sellers configure partial refunds by return reason. Brands can compare recovery value against processing and disposal costs. The answer depends on SKU economics, not a blanket policy.

How is Walmart becoming a stronger Amazon competitor?

Walmart's new Brand Highlights bring enhanced images, video, and branded storytelling to eligible product pages. Its Stockton fulfillment center adds West Coast capacity, while a limited test explores placing third-party marketplace inventory directly inside Walmart stores for pickup and faster delivery. The opportunity is growing, but copying an Amazon strategy into Walmart still isn't a strategy.

What changes when AI agents and TikTok influence checkout?

Walmart, Shopify, Stripe, and others are supporting the emerging Personal Agent Protocol, while TikTok is introducing Buy Direct and an AI-powered Shopping Assistant. These developments point toward shopping journeys where a consumer starts with a conversation or video rather than a traditional search page.

Could AI product cards become the next Buy Box?

A small study involving 40 shoppers suggests consumers often choose products and offers from structured AI shopping cards. The numbers are early and directional, but the operator lesson is clear: accurate product attributes, strong imagery, competitive offers, availability, and reliable delivery matter as much as AI mentions.

The bottom line: More traffic does not fix weak margins. Faster delivery does not fix poor inventory planning. AI visibility does not fix a weak product offer. The brands that win are the ones connecting marketing decisions to operational discipline and real profitability.

Like and follow Selling on Giants for weekly coverage of Amazon, Walmart, TikTok Shop, retail media, and AI commerce.

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What if your product isn’t the problem?

What if your customers simply don’t see the problem the way you do?

In this episode of Selling on Giants, Mr. Will explores why some products struggle to sell even when the product itself is good—and why the answer may have less to do with traffic, advertising, or adding new SKUs than with seeing the customer’s problem from a different perspective.

The story starts with Bette Nesmith Graham, the entrepreneur who created Liquid Paper. Working as a secretary in the 1950s, Graham realized that typing mistakes did not necessarily need to be erased. She could simply paint over them.

The breakthrough was not the white paint.

It was reframing the problem.

That lesson applies directly to ecommerce.

Brands often respond to slow sales by launching more products, expanding their audience, adding keywords, or increasing advertising. But if the underlying positioning is unclear, more traffic and more products can simply create more ways to avoid solving the real problem.

Sometimes the answer is already sitting right in front of you—in customer searches, reviews, questions, and the language shoppers use to describe what they actually need.

In this episode, we cover:

• Why slow sales do not always mean you need another product
• What Bette Nesmith Graham’s Liquid Paper story teaches brands about problem-solving
• Why Amazon search data is a form of customer research
• How long-tail searches can reveal the problem behind the purchase
• Why customers may search for a situation rather than a product
• How customer language can reshape your positioning, listings, and advertising
• Why adding more audiences can make your messaging less effective
• How advertising can amplify a positioning problem instead of fixing it
• Why founders sometimes need to stop building and start listening
• How to identify the actual job your product is doing for customers

This episode is for ecommerce founders, Amazon sellers, brand operators, and marketplace teams trying to understand why a product is not converting despite having traffic, advertising, and a solid product behind it.

Your customers may not be buying what you think you are selling.

They may be buying comfort, convenience, relief, protection, confidence, or a solution to a very specific problem.

Before launching another SKU, adding another variation, or spending another dollar on traffic, ask a simpler question:

What problem is the customer actually trying to solve?

At BellaVix, we help brands turn marketplace data and customer behavior into clearer strategies for positioning, advertising, listings, and growth.

BellaVix has helped brands sell over $500 million on Amazon and is a Verified Ad Partner, but the real work starts with understanding what customers are actually looking for.

The key question:
Are you selling the product—or solving the problem behind the purchase?

Subscribe to Selling on Giants for weekly operator-level breakdowns on Amazon, Walmart, retail media, marketplace strategy, AI commerce, eCommerce growth, and what actually changes for brands responsible for profitability.

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