FOUNDER
Who is John Sillings?

John grew up in New York and followed a path that, from the outside, looked textbook “Wall Street.”

He spent nearly a decade in equity analysis, starting his career on Wall Street and eventually logging time at multiple hedge funds and at US Trust / Bank of America in wealth management.

His day job:

• Analyze public companies across virtually every sector

• Build detailed financial models

• Make buy/sell recommendations on stocks

• Sit down with 1,000+ management teams, CEOs, and founders of both large and small public companies

Early on, he loved it.

He got paid to read, think, model businesses, and talk to talented operators. But somewhere around year seven, the game started to feel repetitive. He’d analyzed “every kind of business under the sun”, and the itch to build something himself kept getting louder.

So he did what a lot of great founders do: he started on nights and weekends.

From Analyst to YC-Backed Founder (Three Times with the Same Co‑Founder)

John’s first startup was Art in Res (YC W20), an online marketplace for art.

He didn’t leave his job right away. He shipped v1 on the side, tested demand, and kept iterating until it was clear he was meant to build, not just analyze.

Art in Res went through Y Combinator, grew, and was eventually acquired.

Along the way, John found something just as important as product‑market fit: a co‑founder he could build with repeatedly.

That co‑founder is John Friel. Together, “the Johns” have now built three companies:

• Art in Res – YC‑backed art marketplace (acquired)

• Mini Exhibitions– virtual events platform used by logos like Spotify, Stripe, Amazon, and more

• Manifolds – the software John wishes he’d had at every PLG and growth role he worked in after YC

Between these companies, John sharpened his growth craft inside other high‑caliber startups:

• Superset – a startup studio where he drove growth across 12 portfolio companies

• Invert – biotech startup, Head of Growth

• Checksum – devtools startup, briefly Head of Growth

• Replicate – ML platform where he worked on growth until the company was acquired by Cloudflare

In each role, one pattern kept repeating: PLG products were generating tons of signups—but most teams had no idea who those users actually were.

COMPANY
Manifolds

Manifolds is the culmination of that pattern.

At its core, Manifolds de‑anonymizes PLG signups in 30 seconds to 2 minutes.

If someone signs up for your product—often with a personal email like [email protected]—Manifolds works to answer:

• Who is this person, really?

• Where do they work?

• How senior are they?

• Is this a Fortune 500 opportunity or a solo tinkerer?

For companies running PLG, the stakes are enormous.

You might have millions of users, but a tiny slice—fewer than 50 contracts in some cases—accounts for most of your revenue. Hidden in the flood of free signups are:

• Engineering leaders at Meta

• Data teams at Airbnb

• Innovation groups at JPMorgan

…quietly kicking the tires, evaluating your product, and leaving.

John’s view is simple: you shouldn’t find out about those users months later in a CRM export, if ever.

You should know within minutes.

Problem & Solution

The problem:

PLG has a superpower and a blind spot.

The superpower: anyone can try your product without talking to sales.
The blind spot: you end up with a sea of anonymous users, and you only truly recognize the 5–10% who eventually convert.

That means you’re:

• Over‑serving low‑value users who happen to raise their hands

• Under‑serving high‑value teams who never trigger a classic MQL

• Flying blind on which campaigns and channels are actually bringing in your best customers

John saw this at Replicate and other devtools/infra companies: tons of activity, very few “known” users, and an outsized concentration of revenue in a handful of large accounts.

What Manifolds does:

Manifolds pulls in structured data from the public web about each new signup:

• LinkedIn presence and work history

• Role, seniority, and function (e.g., CTO vs IC engineer vs PM)

• Company information (size, industry, stage, tech stack clues)

• Other signals derived from online activity and presence

Then it:

• Builds a detailed “manifest” for each user

• Classifies their value (e.g., Fortune 500 staff engineer vs student hacker)

• Triggers alerts when high‑value users sign up

So when someone from Meta, Airbnb, or JPMorgan lands in your product, your team knows—fast.

Originally, John stitched together versions of this workflow using tools like Clay, Zapier, and Apify at multiple startups. At some point, it became obvious:

If he’d happily have bought this product six times, others would too.

So he and Friel built Manifolds.

ICP and Use Cases

John is very clear about who Manifolds is for. The best‑fit companies tend to:

1. Run PLG – Users can sign up and use the product without talking to sales.

2. Have a power‑law in deal value – A small number of accounts are worth 10–100x the average user.

3. See lots of personal email signups – Especially common for developers and technical teams.

The primary users are sales and marketing teams at PLG companies who want to:

• Spot high‑value signups early

• Route them into a more hands‑on, sales‑assisted journey

• Stop “spray and pray” and get smart about who they’re serving

Beyond pure lead identification, customers are already using Manifolds to:

• Fight fraud and fake accounts

• Power event outreach (who actually cares enough to attend?)

• Enrich board decks with real user/company insights

• Run deeper marketing analytics on who each campaign is attracting

• Compare conversion across personas (PMs vs CTOs vs IC devs)

Once you know who your users are, these secondary use cases almost emerge naturally.

GTM: Linkedin and Highly Qualified Outbound

Manifolds is bootstrapped, and John is intentionally building it like a tight, high‑leverage product, not a spray‑and‑pray SaaS.

Two channels matter most right now:

• LinkedIn content – John posts consistently, speaking directly to sales and marketing leaders who live with this problem every day.

• Cold outbound – Cold calls, cold emails, and LinkedIn DMs to carefully selected accounts.

The key isn’t volume—it’s qualification.

John spends real time upfront identifying companies that:

• Have PLG signups

• Sell into enterprise or mid‑market

• See lots of personal email signups

• Are likely missing out on large, high‑value opportunities hiding in that noise

If you’re a founder or head of growth who fits that profile, his outreach doesn’t feel like generic SaaS spam. It feels like:

Product Roadmap & Vision

Right now, Manifolds tells you who just signed up and why they matter.

The next step is making that intelligence available everywhere your team works.

Over the next year, John wants Manifolds to:

• Enrich CRMs (so Salesforce / HubSpot records come preloaded with deep user context)

• Push structured user data into analytics tools like Google Analytics and PostHog

• Sync into your data lake, so product and revops teams can slice and learn from it

Philosophically, he thinks of Manifolds as a “set of Legos” for growth and operations:

• Growth teams can pipe the data into routing rules and scoring models

• RevOps can build smarter playbooks

• Product teams can analyze which personas activate and retain best

Users are already applying it in ways John didn’t fully anticipate—anti‑fraud automations, event operations, board reporting. That emergent creativity is exactly what he wants.

Underneath all of it is a very YC‑ish belief:

Why John Stands Out

Spending time with John, you start to see a consistent pattern in how he operates:

• He intentionally chases variety and complexity. From wealth management to hedge funds, from YC art marketplace to devtools to biotech growth, and now to Manifolds, he’s repeatedly chosen environments where he has to learn new domains fast.

• He’s attracted to founder‑style work. He doesn’t want a job where every day is the same spreadsheet. He wants new problems every week—accounting in the morning, product in the afternoon, sales and marketing by evening.

• He builds the tools he wishes he’d had. Manifolds isn’t a theoretical idea; it’s a workflow he hacked together 5–6 times because nothing on the market did the job.

• He understands both sides of the table. Years of meeting public‑company CEOs and founders gave him pattern recognition on what durable companies look like. Now he’s applying that in the trenches as a bootstrapped founder.

• He has a growth operator’s bias. His worldview is rooted in talking to users, building opinionated workflows, and turning messy, unstructured signals into clear, actionable systems.

He isn’t trying to replace PLG or gate everything behind sales.

He’s building the intelligence layer that lets PLG companies stay self‑serve while still capturing the outsized value of their best users.

TL;DR

After nearly a decade on Wall Street and multiple startups with the same co‑founder, YC alum John Sillings is now building Manifolds, a de‑anonymization engine that turns anonymous PLG signups into rich, prioritized user profiles in under two minutes so teams never miss their highest‑value opportunities.

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