Human judgment × AI execution.
That’s where I can create value.

Start with what your team needs. I’ll show you how I can help, and the work that proves it.

Selected evidence

A cross-section of how I work

A few ways I can help when the work is messy, important, or stuck.

4 cases

Component sourcing was slow, manually intensive, and dependent on supplier familiarity. The purchasing team was also relatively new to AI, so an open-ended chat interface added friction instead of making the work easier. I built a lightweight web portal connected to Google Gemini. Users could enter a product and quantity, refine the criteria that mattered, receive ten close matches, and generate a tailored inquiry email to the contact listed for each result asking about current cost and lead time.

Proof pointDesign target · 10+ ranked alternatives per searchRecorded design target

The critical reframe

“The opportunity was not simply better AI search. It was giving the team a familiar, controlled interface that embedded AI inside the sourcing workflow they already understood.”

I bring

Mapped the sourcing workflow, designed the user experience, defined the search controls, and determined what supplier communication should contain.

AI contributes

Expanded the product search, organized close matches, and drafted supplier-specific outreach from the user’s criteria and quantity.

Together

I made AI approachable and operationally relevant; Gemini supplied the search and drafting capacity behind the interface.

How I approached it

Translated the sourcing process into a guided web interface
Allowed users to refine searches around the criteria relevant to the purchase
Used Gemini to return ten close matching products with supplier context
Generated a reviewable outreach draft for each result using the requested quantity, product, cost, and lead-time questions

Where judgment mattered

I designed for the purchasing team’s actual comfort level and kept search criteria and supplier outreach under user control rather than forcing adoption through an unfamiliar conversational interface.

What changed

A functioning sourcing portal turned AI-assisted research and initial supplier outreach into a guided workflow the purchasing team could use without needing to become expert AI prompt writers.

A frequently requested storage concept began as a loosely defined opportunity. It still had to survive customer validation, structural testing, manufacturability decisions, packaging, installation, system setup, positioning, and launch before it could become a dependable commercial product. Over 17 months, I led the work from requirements and early prototypes through customer installs, production readiness, three launch SKUs, packaging validation, documentation, ecommerce setup, and an August 2025 launch. The first design changed substantially as testing exposed binding, latch, installation, structural, and packaging problems.

Proof pointRecorded · $146,665 launch-year revenue · 102% above forecastRecorded 2025 result · 514 units and 17.3% attach rate by March 2026

The critical reframe

“The job was not to protect the first design. It was to build a disciplined loop for finding what was wrong, making the right tradeoffs, and carrying those decisions all the way through the customer and operating experience.”

I bring

Owned the product-management continuity, made the commercial and customer tradeoffs, coordinated the cross-functional work, and remained accountable for physical testing and launch readiness.

AI contributes

Supported later component sourcing, structured meeting decisions and actions, and preserved continuity across the 2026 adaptation and cost-reduction work.

Together

I led the product and business decisions; AI accelerated research and program continuity without replacing engineering validation, supplier confirmation, or launch judgment.

How I approached it

Turned an ambiguous opportunity into testable customer, product, and commercial decisions
Used prototypes and customer installs to challenge assumptions and prioritize changes
Coordinated design, manufacturing, quality, purchasing, finance, marketing, ecommerce, suppliers, and customers
Built the BOMs, assembly process, packaging, guides, item setup, inventory, positioning, and launch readiness needed to commercialize reliably

Where judgment mattered

I repeatedly chose customer reliability and manufacturability over attractive features, rejecting ideas such as folding construction, dampened slides, flat-pack assembly, and broader factory changes when the evidence did not justify their cost or risk.

What changed

The product generated $146,665 in 2025 revenue, finishing about 102% above its revenue forecast. It reached 514 units within roughly seven months, achieved a 17.3% attach rate, and established the identity for a broader storage collection. A later redesign modeled an $80.10 per-unit cost reduction and gross-margin improvement from about 15% to 32%.

Marketing and Customer Service regularly needed product answers about cost, margin, inventory, and likely stockout timing. The source data existed in Salesforce and Shopify, but neither system gave these teams a simple, complete answer, so the questions kept coming back to me. I used Coefficient to bring live Salesforce and Shopify data into a structured spreadsheet that acted as the engine under the hood. I organized the fields and calculations around the questions people actually asked, then built a focused Gemini interface so Marketing and Customer Service could get current answers in plain language without learning the underlying systems.

Proof pointEstimated · 30 to 40 hours/year recoveredEstimated from 30 to 45 minutes of repeated questions avoided each week

The critical reframe

“The system closest to a transaction is not automatically the best place for someone to get an answer. The source systems needed a dependable logic layer and a simpler doorway for the people using the information.”

I bring

Defined the useful questions, selected the authoritative sources, designed the data model and calculations, and established what a trustworthy answer needed to contain.

AI contributes

Provided the approachable question-and-answer layer over the connected, continuously updated product data.

Together

I built and governed the information system; Gemini made it easy for other teams to use without depending on me.

How I approached it

Started with the recurring questions Marketing and Customer Service needed answered
Connected live Salesforce and Shopify data through Coefficient
Built a controlled spreadsheet layer for cost, margin, inventory, and stockout logic
Created a focused Gemini interface that made the resulting answers approachable and immediately available

Where judgment mattered

I determined which sources were authoritative, how the data needed to be joined, which calculations could be trusted, and what the answer needed to show before Gemini ever presented it.

What changed

Marketing and Customer Service could get product answers in real time instead of waiting for me to investigate, and I recovered an estimated 30 to 40 hours per year for higher-value product work.

A recurring merchandise program depended on decision knowledge that largely lived in one person’s head, creating risk during an ownership transition. I centralized fragmented forecasting, inventory, item data, and ordering logic behind a one-click Google Apps Script that produced a clean, complete CSV ready for immediate ERP upload.

Proof pointEstimated · ~25 hours/year avoidedEstimated across 4 annual ordering cycles

The critical reframe

“A handoff must preserve how decisions are made, not only the steps someone used to perform them.”

How I approached it

Separated procedures from judgment
Captured demand, inventory, and ordering logic
Defined how quantities, priorities, and exceptions were recognized
Produced repeatable workflows and vendor-ready outputs for the next owner

Where judgment mattered

I identified the tacit knowledge another person would otherwise have to relearn through mistakes or repeated escalation.

What changed

A new owner could execute the complete ordering workflow from one button instead of reconstructing logic and data from multiple locations, avoiding an estimated 25 hours of work each year.

Thanks for taking the time to see how I work and where I can be useful.

If I can help your team sort through ambiguity and move good work forward, I’d be glad to talk.

Start a conversation ↗Connect on LinkedIn ↗

benvanouse@gmail.com

Human judgment × AI execution.That’s where I can create value.

A cross-section of how I work

Human judgment × AI execution.
That’s where I can create value.