By Karthi Sepulohniam (Subramaniam), Head of Asia Pacific & Australia, Partners for Growth
Partners for Growth AI Series – Episode 3
Featuring Wai Hong Fong, Chieftain / Co-Founder and Yanlin Wang, CFO, StoreHub
The best AI lessons come from the people shipping it.
This is the third instalment of our AI Series, where we sit down with technology leaders across our ecosystem to understand how they’re using AI in ways that are practical, non-obvious, and genuinely changing how they operate.
For this episode, I sat down with Wai Hong Fong, Chieftain & Co-Founder, and Yanlin Wang, CFO, at StoreHub, a payments and commerce platform serving merchants across Southeast Asia, with operations in Malaysia, Singapore, Thailand, the Philippines, and Japan. StoreHub has been a PFG portfolio company since 2024. I expected a conversation about engineering productivity but instead what I got was a live demo of how StoreHub is using Claude as a company-wide operating system.
“Nobody Looks at the UI Anymore”
Early in the conversation, Wai Hong showed me how his team works day to day. They’ve moved almost entirely out of the Claude web interface and into Claude Code, the command-line tool originally designed for software engineers.
Instead of using Claude Code to write code, they’re using it as a unified layer across every system the company runs on: from finance to product, engineering to customer success.
From a single terminal, Wai Hong can pull data from Salesforce, query Google Workspace, access Airwallex for financial data, send messages on Lark, build Google Sheets, run research across the web, and synthesize it all into structured documents. All without switching between applications.
He walked me through it live. During our call, he pulled up a quarterly revenue view by currency, asked Claude to create a Google Sheet from the data, and shared it, all without leaving the terminal. Without logging into Salesforce login, no manual exports and no formatting in Sheets. The kind of task that would normally take an analyst thirty minutes was done in under two, as a side thought during a conversation.
As Wai Hong put it: “The difference between code and non-code is just syntax. A financial model, a project document, and a software code are all just structured information. Once you see it that way, Claude Code stops being a developer tool and becomes an operating system for knowledge work.”
The Morning Brief: A Personal Command-and-Control System
Every morning, Wai Hong runs what he calls a “morning brief”: an automated summary that pulls together his commitments, tracks promises made to and by his direct reports, and drafts follow-up messages on Lark. Each message is tailored to the recipient: a gentle nudge for one person, a more direct tone for another, emojis and all.
Behind this sits a system of project folders, each with its own context file that acts as a notebook for Claude. Short-term memory in the terminal session, long-term memory in the files. On his most intensive days, Wai Hong runs 1,000 to 2,000 prompts. That’s not a typo.
“Nancy”: The AI Finance Employee
Then Yanlin, StoreHub’s CFO, shared her side of the story.
Three months ago, Yanlin had no coding background. Today, she’s built an AI agent she calls “Nancy”, a forecasting tool that pulls historical sales data from Salesforce, renewal data from Chargebee, and payroll data from internal files, then generates a financial forecast.
What used to require a finance team building and maintaining complex spreadsheets now takes five minutes. Yanlin works with Nancy to refine assumptions, and the model updates itself. She’s building a system that automatically flags deviations between forecast and actuals and surfaces them for review.
The engineering productivity story is well documented by now. What’s more interesting here is that a CFO with no technical background built her own forecasting tool, tailored to how she thinks about the business, without waiting for an engineering team to prioritise it.
Gen 1 vs Gen 2: A Framework for the AI Shift
Wai Hong offered a useful framework for thinking about where we are in the AI adoption curve.
Gen 1, roughly the past twelve to eighteen months, was defined by AI writing code. Tools like Cursor emerged, then Claude Code. Engineering teams saw step-change improvements in velocity. Products that would have taken months were shipped in weeks.
Gen 2, which began only a few months ago, was triggered by the expansion of context windows to one million tokens and the release of Claude Code to general availability. This unlocked the agentic workflows Wai Hong demonstrated – not just code generation, but entire operational systems built and run through AI.
The question StoreHub is now focused on is what happens when you combine Gen 1 foundations (the ability to build products at speed) with Gen 2 capabilities (the ability to run a business through AI). Wai Hong believes the compounding effect of the two will separate the companies that pull ahead from those that fall behind.
The Takeaway
StoreHub isn’t experimenting with AI. They’ve restructured how the entire company operates around it. From the CEO’s morning brief to the CFO’s forecasting agent to the gamified adoption system, AI is woven into how decisions are made, how people are managed, and how work gets done.
It’s a reminder that the companies getting the most from AI aren’t just adding it to existing workflows. Rather, they’re rethinking the workflows themselves.
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This is Episode 3 of AI: Where Innovation Meets Execution, a series where we profile how technology companies and investors across our ecosystem are deploying AI in practical, non-obvious ways. If you’re building something interesting with AI and want to be featured, reach out to us at karthi@pfgrowth.com.
Featured companies may be clients or portfolio companies of PFG. No compensation has been provided for inclusion. This content is for informational purposes only and does not constitute investment advice or a recommendation.
The views expressed are my own and do not necessarily reflect those of my employer.
This content is for informational purposes only and does not constitute an offer to sell or a solicitation of an offer to buy any securities. Any such offer will be made only to qualified investors through confidential offering documents. All investments involve risk, including the possible loss of principal. Past performance is not indicative of future results.
