Taking new agency clients
The GTM engineerbehind AIGTM agencies.
You sold clients an AI-powered outcome. Something has to actually run it: sourcing, enrichment, drafting, approvals, deliverability, reporting. I build that machine in your stack, under your brand, and hand it over documented — you keep every client relationship and I stay off your calls.
- Serial
- Entrepreneur, still building
- White-label
- Your brand, not mine
- Fixed
- Scope agreed before code
- Yours
- You own what I build
01Why agencies call me
The agency model scales by hiring.
You promised it wouldn’t.
Every new AI GTM agency hits the same wall around client five: the demo was software, the delivery is a person. That person is usually the founder.
What breaks
- Every client onboarded by hand, so client six costs the same as client one
- A vendor stack nobody owns: five tools, four logins, no pipeline between them
- Lists that look big and convert at zero, because ICP lives in someone's head
- AI-written emails that read like AI-written emails, and a domain paying for it
- Deliverability found out about after the first client complains about bounces
- No reporting layer, so QBRs get rebuilt in a spreadsheet the night before
- Nothing is idempotent — a rerun double-sends, a crash strands a record
- One operator is the single point of failure and cannot take a week off
What changes
Delivery stops being a person
The work your clients bought runs as a pipeline instead of a founder with twelve tabs open. What that pipeline covers is whatever we scope — but the shape of the change is always the same: manual steps become a system with a review gate in front of the parts that spend money or reach a prospect.
The next client is cheaper than the last
Onboarding becomes a path rather than a project, so client count stops being capped by the hours of whoever knows how it all works.
You own it, and it survives me
Everything lands in your repos and your vendor accounts, documented, with a walkthrough for whoever runs it. The measure of a good engagement is that you don't need another one.
None of this is a package. Which pieces you actually need comes out of the intro call and lands in a written scope with a fixed price — and if it grows, we re-price it in writing rather than arguing about what a bullet point on a website implied.
02What I build
The machine, module by module.
Most engagements are a subset. We scope what you need and leave what already works.
Sourcing and enrichment
ICP definitions that disqualify most of the market, provider waterfalls (Apollo, Clay, verification), dedupe and caching so you stop paying twice for the same contact.
Sequencing and deliverability
Domains, mailboxes, warmup gates, per-mailbox caps, and a sending layer that fails closed instead of torching the client's reputation.
AI drafting with a human gate
Per-prospect drafting worth reading, with a review queue in front of every send. Approval is a step in the pipeline, not a promise in the SOW.
CRM and data plumbing
HubSpot or Salesforce as system of record, your platform as the mirror. Idempotent writes, no double-sends, no stranded records after a crash.
Signals and intent
Job changes, hiring, funding, site visits, competitor mentions — routed into the sequence that should react to them instead of a dashboard nobody opens.
Reporting and client-facing surfaces
Per-client dashboards and QBR-ready numbers pulled from the pipeline itself, so the deck is a query and not a weekend.
Multi-tenant foundations
Client isolation, per-client config and credentials, and an onboarding path so adding a logo is a form, not a project.
Internal agent tooling
Coding and ops agents doing real work inside your repo under a review pipeline — the part everyone demos and few run in production.
03How it works
Intro call to handoff, in four steps.
- 01
Intro call, 20 minutes
Your clients, your stack, what you promised them. I'll tell you if this is a tooling problem you can solve yourself — that happens, and it costs you nothing to find out.
- 02
Scope and a fixed proposal
A written scope with the build sequence, the vendors involved, what it costs, and what I'm not doing. You approve it before anything starts.
- 03
Build in your stack
Your repos, your vendor accounts, your brand on it. Weekly working sessions, visible progress, no black box and no monthly deck.
- 04
Handoff that survives me
Documentation, a walkthrough with whoever runs it, and a defined support window. The goal is that you don't need me on retainer unless you want the capacity.
04Engagements
Two ways to start.
A fixed-scope build, or ongoing engineering capacity. Scope agreed in writing before anything starts, quoted after a free intro call.
Infrastructure build
typically 4–10 weeks
I build the machine end to end, in your stack, under your brand, and hand it over.
- Fixed scope and a fixed price agreed before the first commit
- Direct work in your repos and vendor accounts
- Sourcing → enrichment → drafting → approval → send → reporting, wired and tested
An agency with signed clients and a delivery model that doesn't survive the next five.
Fractional GTM engineer
monthly, cancel any month
Ongoing engineering capacity: extend the machine, add clients, fix what breaks.
- A set block of build time each month, scheduled with you
- New client onboarding and per-client configuration
- Provider changes, migrations, and deliverability upkeep
Agencies growing client count faster than they can hire an engineer.
05Fit
Who I work with
- New AI GTM agencies with signed clients and a stack held together by Zapier and hope
- Founders who sold an AI-powered outcome and are personally doing the manual work behind it
- Agencies stuck at the client count one operator can babysit
- Consultancies adding a GTM-automation line and needing it built once, properly
- Teams evaluating Clay, Smartlead, Instantly, HubSpot and unsure what to own vs. rent
Why me
I'm a serial entrepreneur who recently left a co-founded venture-backed startup to build with AI full time. In that seat I bought agencies across recruiting and marketing, so I know exactly where the delivery layer breaks. Today I'm building a multi-tenant GTM automation platform — a real multi-tenant system running sourcing, enrichment, drafting, approval gates, sending and reporting, mostly written by AI agents under a review pipeline I designed. I'm not running an agency and I'm not pitching your clients. I build the machine and you keep the relationship.
06Who I am
Daniel Pao
I’m a serial entrepreneur — most recently a co-founder at a venture-backed startup, which I left to go all-in on AI while the window is open.
In that seat I bought agencies across recruiting, marketing, and a few other functions. The strategy was usually fine; the delivery layer was people. A retainer, an account manager, a junior doing the work by hand, a monthly deck.
So I built the software version: a multi-tenant GTM automation platform, multi-tenant, running sourcing through reporting, most of the code written by agents inside a review pipeline I designed. Agencies started asking me to build theirs. That’s this.
Short version
- Serial entrepreneur, companies built from zero
- Bought and managed agencies across multiple functions
- Building a multi-tenant GTM platform, mostly agent-written
- Ships in your repos, under your brand
- Not an agency — I don't want your clients
Next step
Start with a free 20-minute intro call
Bring your stack and your client list. We work out what I'd build first, and I'll tell you if you don't need me.