I Tracked 369 Startup GitHub Orgs for Six Months. Here's What Predicts a Series A.

Six months ago I started watching public GitHub for a leading indicator that VCs were missing.

The thesis was simple. Hedge funds spent the last decade extracting alpha from satellite imagery, credit card panels, and shipping data. The venture-capital equivalent – public engineering activity on GitHub – has been sitting in plain sight, ignored by most institutional sourcing teams, who still rely on Crunchbase, warm intros, and Twitter.

I built a crawler. I pointed it at 369 startup organizations across 15 sectors. I let it run weekly for six months. Here is what I learned.

What the Signal Actually Looks Like#

The single most predictive indicator is not commit volume. It is commit velocity *change*.

A startup that ships 200 commits per week and continues to ship 200 commits per week tells you nothing. A startup that goes from 80 commits to 240 commits inside 14 days tells you something is happening. Often it is a fundraise close. Often it is a launch. Sometimes it is both.

We track three signals together:

1. Commit velocity (14-day window) – total commits to the org's most active repo
2. Contributor growth (30-day window) – change in the count of unique contributors
3. New repo creation (30-day window) – fresh repos appearing in the org

When all three accelerate inside the same two-week window, we classify the startup as "accelerating". In our backtest across Q3 and Q4 of 2025, roughly 70% of accelerating startups announced a fundraise within six weeks of the signal firing.

The Four Signal Types#

Not every acceleration looks the same. We classify them into four pre-fundraise patterns:

Engineering hiring burst. Contributor count jumps 40 percent or more inside 30 days. Often pre-Series A – the company has signed term sheets, started hiring, and the new engineers are pushing first commits. We catch this earlier than LinkedIn employee counts because contribution lands before "Senior Engineer at Acme" gets posted.

Infrastructure buildout. Commits to ops, infra, deploy, and observability repos spike. The company is preparing to scale. Usually accompanies a Series A or Series B that is funding go-to-market expansion.

Deploy frequency spike. Commits per day double. Often a sign of a launch run-up. The team is shipping fixes and features fast. Sometimes followed by a product launch and a press cycle, sometimes by a fundraise where the metrics make the deck.

Framework migration. The team is migrating to a new stack – Next.js, Bun, a new ORM, fresh CI. This often happens 60 to 120 days before a Series A. It is the engineering equivalent of cleaning your apartment before parents visit. Our hypothesis: founders know due diligence is coming and want a clean codebase to walk an investor through.

Where the Signal Fails#

Honesty: the signal is bad for AI-pure startups. They commit constantly regardless of stage. Signal-to-noise is poor. We exclude AI-only orgs from the strongest classification tier and weight other features more heavily.

The signal is also useless for stealth startups that do not open-source. If your dream company is in stealth, GitHub gives you nothing.

And the signal is not investment advice. It tells you who to talk to. It does not tell you who to wire money to. The decision still requires founder conversations, product evaluation, market analysis, and competitive teardown. Engineering velocity is a sourcing signal, not an investment thesis.

What Does NOT Predict a Round#

Things that look meaningful in the data but turn out to be noise:

- Star count. Vanity. A 30,000-star repo means it had a viral moment. It does not mean revenue. - Fork count. Lagging indicator at best. By the time forks accumulate, the round is closed. - Single-repo commit volume. Founders cosplay productivity. One person committing 400 times a week to one repo is a productivity tell, not a fundraise tell. - The GitHub trending tab. If a project is trending, the round is already 80 percent allocated. You are too late.

The signal is in *change*, not in *level*.

The Public Watchlist (Q3 2026 Predictions)#

Today I published the 10 startups our model predicts will raise in Q3 2026. It is dated. It is bookmarkable. It is falsifiable. Come back in 6 months and check.

Each card on the watchlist links to the underlying GitHub org so you can audit the signal yourself. The free /predict tool lets you score any other startup with the same engine in seconds.

I am publishing this in public on purpose. Backtests are easy to fake. Live forward-tested predictions are hard to fake. The only way to build trust in an alternative data source is to show your work and let the future judge it.

How to Use This in Practice#

If you are a VC, scout, or angel:

1. Subscribe to the free weekly digest at gitdealflow.com. Five breakouts every Monday morning, in your inbox before any other source has them.
2. Bookmark the Q3 2026 watchlist. When something on the list raises, you will know we called it.
3. Use the /predict tool before every founder meeting. Two seconds of GitHub-signal context can save a 30-minute call with a company whose engineering momentum is already cooling.

If you are a founder:

1. Run /predict on your own org. Know what your public engineering signal looks like to investors before the next pitch.
2. If you are pre-fundraise and your signal is steady or decelerating, fix it before you start the round. Investors who use alt-data are reading this in real time.
3. If you are stealth, you are invisible to this signal. Trade-off acknowledged.

What is Next#

We refresh the dataset every Monday at 09:00 UTC. New watchlists every quarter. Methodology updates published at /methodology when the underlying classification thresholds change.

If you find a startup we should be tracking that is not in the index yet, the /predict tool tells you so directly and lets you submit it.

The first VC to systematically use engineering-velocity data as a sourcing input has already won the next decade of seed-stage deal flow. The question is who that is going to be.