Architect of the Post-Labor Institutional Agency

Built the 65-analyst agency
in 28 days.

15,635 manual analyst hours replaced in 28 days. 122,000+ institutional investors across VC, PE, Growth Equity, Infrastructure, Hedge, Credit, and Real Estate — tracked, matched, and injected into client CRMs autonomously. $7-10M+ anchor checks for fund managers raising $50M+.

I replaced a $1.5M annual labor cost with 13 autonomous GCP data trains. 65 analyst-equivalent throughput. $200/mo cloud bill. The $1.5M doesn't exist on my P&L—because I codified it into a machine.

$61.75M+

Raised under direct advisory (Fund I-III)

15,635h

Manual research replaced in 28 days

122K

Active institutional subscribers

$200/mo

Cloud bill for 65-person equivalent output

The Dual Threat

Two skills. One operator.

Most execs know capital or code. I deploy both. That's not a pitch — it's a structural advantage you can't hire for twice.

Institutional Distribution

B2B tech companies spend millions trying to crack the LP market. Their sales teams sound like outsiders because they are. I own the largest investor relations audience globally — 121,500+ fund managers, allocators, and LPs who already trust the brand.

This isn't a marketing channel. It's a pre-built, proprietary pipeline of institutional capital and buyers that plugs directly into your P&L.

$61.75M+ raised under direct advisory (Fund I–III clients)
$1.26M/month avg GP velocity — 2x industry benchmark
Engagement 20-30% above tier-one financial media

Autonomous Infrastructure

I built 13 autonomous data trains on GCP Cloud Run that produce the output of a 65-analyst research floor — for a $200/month cloud bill. The engine monitors global LP activity across VC, PE, Growth Equity, Infrastructure, Hedge, Credit, and Real Estate with a focus on $7-10M+ anchor commitments. LP signals flow from BigQuery to client HubSpot CRMs via programmatic upsert cron jobs — zero manual data entry.

103,000+ rows written to BigQuery in 28 days. 15,635 manual analyst hours replaced. The entire platform was built in under a month by one engineer.

13 Cloud Run trains: SEC EDGAR, 13F, Board Minutes, Shadow Wealth, Liquidity Events
Autonomous CRM sync: programmatic HubSpot lead injection (weekly cron)
NIST CSF 2.0 secrets management, OIDC auth, zero-downtime deploys

How I Engage

Three ways to deploy me.

I'm looking for one of these roles. The right fit depends on what problem keeps your CEO up at 2am.

01

Operating Partner

For PE/VC firms that need a portfolio-level operator who can walk into a company, diagnose the revenue leak, and fix the plumbing — not just advise on it.

Revenue infrastructure, LP relations, portfolio value creation
02

Head of GTM

For FinTech or data companies trying to sell into institutional capital. Your sales team sounds like outsiders because they are. I bring the audience, the credibility, and decades of closing.

Distribution strategy, institutional sales, audience monetization
03

Product Strategy

For companies building AI/data products for private markets. I've shipped a SaaS app that threatens Pitchbook, Preqin, and Dakota — at $99/month. I know what fund managers actually pay for. Most product teams don't.

Product-market fit, data architecture, competitive positioning

The Engine

This isn't a slide deck. It's production code.

I build automated data trains that extract proprietary signals from SEC filings, board minutes, and LP commitment data. Here's what runs under the hood.

adam@lpblueprint ~ /data-pipeline

// The "Post-Labor" Math: $1.5M labor cost → $200/mo cloud bill

// 13 autonomous trains, 1 engineer, 15,635 hours replaced in 28 days

$ bq query 'SELECT COUNT(*) FROM sourcing_agent.*'

[OK] 103,492 rows written since Feb 1, 2026

[OK] 78,562 LP contacts | 12,629 signals | 9,550 recommendations

[OK] 15,635 manual hours replaced (65 FTE equivalent)

$ gcloud scheduler jobs list --filter="state=ENABLED"

[OK] 13 Cloud Scheduler jobs active | $1.5M labor cost displaced in 28 days

[OK] SEC Form D, 13F, Board Minutes, Shadow Wealth, Liquidity Events

[OK] Autonomous HubSpot injection: Sunday 9PM ET (cr-weekly-crm-sync)

$ curl app.lpblueprint.com/api/admin/deadman-switch

[OK] status: ALL_GREEN | trains_checked: 10 | stale: 0

[OK] Last heartbeat: <8h ago (all trains healthy)

[OK] Uptime: 99.7% across all data pipelines

$

78K+

Verified LP contacts in the platform

103K

BQ rows written in 28 days

$200/mo

Cloud bill for 65-FTE output

Background

Not your typical executive.

Deep B2B sales background. Built and sold a social media consultancy. #1 Amazon bestselling author. Promoted 100+ punk shows. Grew up in the DIY scene and never left.

I built LP Blueprint from a failed VC fundraise into the largest investor relations publication globally — 121,500+ subscribers, 9M+ annual page views, engagement rates that consistently outperform tier-one financial media.

Then I built the SaaS platform to match. Real-time LP check tracking. Verified contacts. Proprietary data pipelines. The whole thing runs on infrastructure I deployed myself.

I didn't learn this in a boardroom. I learned it the hard way — and then I watched 147+ fund managers learn it the same way, one painful quarter at a time.

Let's talk.

If you need someone who can close a $50M allocation and debug your API webhook in the same week — I'm that person.