Steven Ou.

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v3.0 Now with applied AI

A CTO who ships.

Three-time founding CTO. Self-taught since age eleven. Scales consumer and enterprise platforms from zero to nine-figure revenue. Ships AI into production.

See capabilities↓ See case studies
No consulting-speak No slide-deck theater Just product
Brands running on what I've built at Cavalry
Harry's Built Naadam Dolls Kill
Laundry Sauce Geologie CAMCO
Cavalry backed by
SV Angel Bling Capital
Capabilities

What I do best.

Four capabilities, all backed by twenty-seven years of shipping real software to real users.

01

Build from zero.

Full product stacks — web, mobile, backend, data, internal tools — stood up from scratch. No legacy crutches. No incumbent playbook.

web · ios · android · infra · data
02

Ship fast.

Still hands-on after twenty-seven years. Drives the AI line by line — every line signed off as it's written, not after a PR lands. Speed compounds across a career; quality doesn't slip.

shipping since 1999
03

Turn AI into product.

Takes what works and ships it into production — with the security, integrations, and reliability enterprise buyers actually need. Five years on this exact problem.

llm orchestration · deterministic policy engines · production systems
04

Operate technology as a business.

A founder's P&L discipline, a platform-builder's architectural depth. Technology as the engine of the business, not a line item beneath it.

p&l ownership · board engagement · security & compliance · org design
Compatibility

System requirements: met.

My preferred stack. Not a constraint.

Philosophy
Developer velocity over everything.
Languages
Ruby · JavaScript · TypeScript
Frameworks
Rails · Hotwire · Stimulus · Sidekiq · Svelte
Data
PostgreSQL · Snowflake · Valkey
Infrastructure
AWS (ECS, RDS, S3, CodeDeploy) · Docker
CI/CD
GitHub · GitHub Actions
AI
OpenAI · Anthropic · Gemini
AI Tooling
Claude Code · Conductor
Compliance
SOC 2
Case studies

Three deployments. Same operator.

Past performance only. Future promises are for pitch decks.

Case 03 · Current
2021–Present
Cavalry AI
Co-Founder · CTO
60–80%
Autonomous resolution
600k+
Tickets automated
360%
Harry's support ROI
0
Unauthorized actions
AI support, actually resolved. Not the 20% workflow-tool baseline.
Problem
Enterprise e-commerce has tried DIY AI tooling and lost faith. Workflow-based chatbots top out near 20% resolution. Buyers have stopped believing AI support can work at all.
Approach
Purpose-built OS layer: stochastic LLMs paired with a deterministic policy engine that enforces eligibility and executes every resolution in the real systems of record. The LLM handles understanding and language; it cannot act outside policy. Production-grade integrations across Shopify, Zendesk, Gorgias, Klaviyo, Recharge — and more. Not a chatbot. An operator.
Outcome
Agents resolve 60–80% of complex support cases autonomously. 3–4× the workflow-tool baseline. In production at Harry's, Naadam, Dolls Kill, Laundry Sauce, Geologie — among others.
Case 02 · Exited
2012–2020
Touch of Modern
Co-Founder · CTO
$100M+
Annual revenue
15M+
Registered users
100+
Employees
$17M
Capital raised
A $100M+ commerce platform. Built from line 1. I never stopped writing it.
Problem
Stand up an e-commerce platform that merchandises 250+ new products daily, scales to millions of users, and defends margin against Amazon-class incumbents. No legacy stack. No incumbent playbook.
Approach
Standard retail software can't run cross-dock fulfillment. Built the full technology stack in-house: web, native iOS and Android, merchandising, a proprietary OMS for cross-dock fulfillment, logistics, data infrastructure, internal tooling. Technology positioned as the competitive moat. Nearly every business function kept in-house by design.
Outcome
Scaled to $100M+ revenue and 15M+ registered users. Two consecutive years on the Inc. 5000. Recognized by Forbes 30 Under 30 and Inc. 30 Under 30 Rising Stars.
Case 01 · Foundation
2010–2012
Skyara & RAVN
Co-Founder · CTO
i/o ventures
Incubator
2
Companies, back-to-back
Day 1
Started at graduation
Wall Street
Offer declined
v1.0 of the operator. Where I cut my teeth.
Problem
Hyperlocal services and discovery, pre-product-market-fit for the entire category. Build it from a dorm room. Prove the unit economics or move on.
Approach
Two companies, back-to-back. Skyara (local services), then RAVN. Selected into the I/O Ventures incubator class. Walked away from a Wall Street offer. Built instead.
Outcome
Validated that the unit economics in the category wouldn't scale. Pivoted into v2.0: Touch of Modern. Carried the full-stack foundation forward, and the co-founders with it.
Changelog

Shipped recently.

A working career, in reverse chronological order.

v3.0.0
2021–now
Cavalry AI. Built and shipped nearly the entire platform: OS layer, agent runtime, integrations — all of it. Autonomous customer support at 60–80% resolution, well above what pure-LLM or pure-workflow systems reach.
v2.0.0
2012–2020
Touch of Modern. Built the full platform: web, iOS, Android, merchandising, fulfillment, data. Scaled to $100M+ in revenue and 15M+ users. Shipped every day for eight years.
v1.0.0
2010–2012
Skyara & RAVN. Founded two companies out of I/O Ventures. Learned what scales and what doesn't. Carried the foundation forward into v2.0.
v0.1.0
2006–2010
University of Pennsylvania, B.A. Economics. Summer research at ITG (quant trading), capital markets at Chinatrust, systems development at CineNow Singapore. Landed a Wall Street offer. Turned it down to start Skyara.
v0.0.1
1999 · Age 11
Initial commit. First line of code. Self-taught. Never stopped.
Roles

Senior, two ways.

Most popular
Exec
Venture CTO
For companies where the CTO is expected to write code, not just lead the team.
  • Owns technology, platform, and applied AI end-to-end
  • Hands on the codebase from day one through scale
  • Full-time, founding-shaped. Not fractional.
LinkedIn
IC
Principal / Staff Engineer
For companies that need the builder without the exec layer.
  • Applied AI in production, not in a sandbox
  • Force-multiplier for an existing senior team
  • Focused engagement. No exec scope.
LinkedIn
FAQ

Frequently asked.

Are you actively looking for new roles?
Currently building Cavalry AI. Open to conversations about the right thing. Usually a category I haven't worked in, or a problem I can't put down once I hear it.
What does a Venture CTO engagement look like?
Full ownership of technology, platform, and applied AI. Hands-on through early deploys; org-building once the team scales. Not fractional. Not advisory. Operating as the actual CTO.
What stage / size company fits best?
Pre-product through Series C. Where the problem is still ambiguous, the team is still small enough that the CTO ships, and applied AI is part of the product.
What won't you work on?
Crypto. Defense. Anything where "AI" is the marketing.
Do you still write code?
Every day. I design the architecture and drive the AI line by line. By the time a PR opens, I've already approved the work — I'm not just reacting to whatever the agent dropped in. The typing happens through AI now. The judgment doesn't.
What's your AI development workflow?
Claude Code on Opus, run inside Conductor with parallel worktrees. Human-in-the-loop across multiple threads simultaneously. That parallelism is the productivity unlock, not the model choice.

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