Full-Stack B2B Marketer.
I Also Ship the Code.
Paid and inbound, lifecycle and CRM, and the operations layer under them. At PingPong I took one cross-border payments line from $2M to $250M+. Where the tool did not exist I built it, and every one is on a live URL you can open right now. Open to AI-Native Growth, AI GTM and Marketing Ops roles.
- Full funnel, paid to retention
- GTM systems, CRM, attribution
- Lifecycle and email systems
- SEO, GEO and content engines
- AI agents that run the above
U.S. Bank
Gusto
TikTok
Clover
Jeeves
PingPong
BlackwallU.S. BankGustoTikTokCloverJeevesPingPongBlackwall
Agent teams that split the work, check each other, and escalate to a person.
AI wired into the growth operation you already run: CRM, routing, reporting.
Performance media, inbound and campaigns, measured so finance agrees.
Custom AI to spec: an internal tool the team uses, or a product customers buy.
Scaled one cross-border payments line at PingPong.
I owned paid acquisition and lifecycle for it as Marketing Manager, Ads & Lifecycle, from October 2021 to September 2023. A regulated cross-border product, so speed could never cost us the audit trail.
- $2M → $76M in year one, past $250M+ by year two. Annual revenue through the line: inbound in year one, then an account-based motion built with sales in year two.
- LinkedIn CPL $300+ → ~$160. Google registrations $90+ → ~$35, with volume held through both.
I run the programs and
build the AI that runs them
I'm Daniel Liu, a marketer who wandered too close to operations and campaigns, discovered AI automation along the way, and decided to stay.
A decade later that detour is the whole job: I sit where GTM judgment meets hands-on technical execution, connecting campaigns, CRM, tracking, lifecycle, reporting and AI automation into one revenue engine a CFO can audit.
Six workstreams,
one AI-native growth system
I owned all six end to end, in the stack and the regions they actually ran in, and rebuilt each one around the part a model can now carry.
Acquisition and lifecycle across NA, EU and SEA. I took the cross-border payments line from $2M to $250M+ over two years.
Learn more → 02 User AcquisitionPaid across Google, Meta, LinkedIn and programmatic. LinkedIn CPL $300+ → ~$160, Google registrations $90+ → ~$35. Earlier, a $10M annual media buy at ToLocal.
Learn more → 03 Email & LifecycleI build behavior-triggered journeys from signup to retention, keyed to account state and not a weekly list pull. KYC submissions climbed from roughly 10% to 35–40%.
Learn more → 04 SEO / GEO & ContentI run technical SEO and an editorial workflow that carries a draft from a blank NeuronWriter score to the 70s–80s. Generative engine optimization is the other half.
Learn more → 05 Marketing Ops & AnalyticsI cut lead handoff from ~12 hours to 1–2 minutes across 200+ governed workflows, and got the monthly report under five minutes from one to two hours, with a model flagging what needs a human.
Learn more → 06 Partner & AffiliateI carried six years of B2C affiliate into a B2B fintech program: I set the commission tiers, vetted the partners, wired per-partner attribution and screened for fraud before payout.
Learn more →Working prototypes and one production tool
Every one of these started as a problem slowing down work I was running. I built the fix myself, in code, with AI carrying the part that used to eat the week. All of them are live on a public URL.
Ad copy that clears policy before you export it
React
TypeScript
Vite
Tailwind
Gemini 2.5 Flash
DeepSeek
VercelReads your site for the voice, writes for Google, Meta, LinkedIn and Bing, and checks every line against policy while it writes.
Catch the non-compliant phrase before legal does
ReactTypeScriptViteTailwindGemini FlashVercelPaste a fintech draft, pick the jurisdiction, get every risky phrase quoted against the clause it trips.
Find the policy violation before the platform does
ReactTypeScriptViteTailwindVercel FunctionsHeadline, body, URL and creative, all checked against ~84 platform clauses and your own rules. You get a safety score with every risk explained, before upload.
Pull a creator's whole catalog, get the transcripts out
ReactTypeScriptVite
Express
Neon PostgresGemini 2.5 Flash
FFmpeg
Playwright
Resend
StripeVercelPoint it at a Douyin or TikTok profile; it comes back with the whole catalog transcribed, translated and in a spreadsheet. It runs on your own session, which is what keeps the account safe.
Applications, resumes and interviews in one workspace
React 19TypeScriptViteExpress 5
PrismaGemini 2.5DeepSeek
GPT-4o · WhisperStripeVercelOne pasted job description becomes a tracked application, a resume run through a four-pass tailoring engine with its ATS read-out, and interview prep built from the same context.
Run client Meta accounts through the API, with a person on every change
React 19TypeScript
Next.js 16
Meta Graph APIOpenAIGeminiVercelAn agent drafts the campaign, the ad sets, the creative and the copy, then reads results back. Anything that touches a live account passes a guardrail, a named approver and a typed confirmation.
See the real tech stack behind any competitor's URL
Next.js 16React 19TypeScriptDeepSeekPlaywright
BrowserlessStripeVercelFingerprints the bundles, reads DNS and email posture, maps subdomains, then opens the site in a real browser. Every finding is evidence-backed.
Read the strategy your competitors put into market
PythonDeepSeekPlaywrightMeta Graph API
Ads TransparencyStripeVercelPulls a rival's whole ad library and returns the campaign anatomy: market, message, funnel posture. Spend stays out, unestimated.
In their words
Which role are you hiring for?
Enterprise ABM, international launches, lifecycle growth, and the sales partnership around them. I ran all four as one funnel, with numbers that reconcile to finance.
Scope: the B2B cross-border payments line at PingPong (2021–2025), scaled $2M to $250M+, with AI now carrying the reporting and the repeatable execution. Earlier, VP of Marketing at ToLocal, a team of 7 on a $10M annual media budget at 80%+ ROI.
Agent-native go-to-market: research, enrichment, campaign build and reporting run as multi-model agent pipelines, with a person setting direction, not moving rows. Often posted as GTM Engineer, AI GTM Lead or MarTech Lead.
Scope: nine AI GTM tools designed and shipped solo, every one on a live public URL. Currently Senior Marketing Manager at ThinkingAI, leading GTM systems and marketing ops.
Workflow architecture, routing logic, attribution hygiene and website governance. I build the systems every other team reads its numbers from, so sales, marketing and finance open the same figure on the same morning.
Scope: Senior Digital Marketing Manager, Growth & Ops at PingPong (2023–2025), sole owner of a governed 8-tool GTM stack and all of Marketing for 6+ months.
What I'm building now, at ThinkingAI
I run marketing at ThinkingAI as a Senior Marketing Manager. Alongside that, since June 2026, I have been putting AI into the marketing system they already had, from zero. These are the projects that came out of it.
One loop, run on
every system I own
Diagnose
Find the real constraint before spending on top of it.
PingPong, 2021: spent nothing new until the tracking could be trustedInstrument
One cleaned dataset everyone reads. Definitions before dashboards.
8 standing reports, one dataset, every team on the same numberAutomate
The judgment stays human. The busywork doesn't.
200+ workflows: lead handoff ~12h → 1–2 minutes ThinkingAI, 2026: the same loop now runs as reusable multi-agent systems →Scale
Add budget only on instrumented ground.
Cross-border payments line: $2M → $76M → $250M+Let's talk about the role
Hiring for AI-native growth, AI GTM, or marketing ops and systems? Tell me about the team, the role, and the operating problems you actually need solved. I'll tell you honestly whether I'm the right operator for it.
Open to full-time roles in AI-native growth, AI GTM, and marketing ops and systems. Currently Senior Marketing Manager at ThinkingAI, so you get a straight answer either way. Tell me your start window in the form and I'll tell you mine in the reply.