Public Engineering Diligence Workflow

The five-step formula

Every signal you see on the dashboard, in the API, or inside the MCP server flows from these five steps. The bot filter and two-period confirmation are not optional, they are what separates an acceleration signal from acceleration noise.

1. Step 1

   Pull 14-day commit volume per organization

   From the public GitHub REST API. No private repos. No scraping. The bot filter excludes Dependabot, Renovate, GitHub Actions, and any account name matching the substring 'bot' before any aggregation runs.

2. Step 2

   Compute percentage delta against the prior 14-day window

   Each organization is measured against its own historical baseline, not the population. A 100% delta means the team doubled its merge cadence relative to its own prior fortnight. Cross-org comparison is meaningless; self-comparison is the whole point.

   In plain terms: we compare a team to its own normal, not to other teams. A 100% jump means they shipped twice as much code as their usual fortnight. That can be useful for diligence, but it is not proof of a future raise.

3. Step 3

   Apply two-period confirmation

   An acceleration breakout must persist into a second 14-day window before the engine treats it as actionable. This removes hackathon spikes, launch-week bursts, and single-contributor onboarding noise, the three sources of false positives that trip up first-pass momentum trackers.

4. Step 4

   Score contributor concentration with the Gini coefficient

   The Gini coefficient measures commit distribution across contributors over the same 14-day window. It helps distinguish broad team activity from a single-contributor spike. Treat it as context for a diligence read, not as a standalone prediction.

   In plain terms: the Gini coefficient is just a fairness score for who is doing the work, is this a whole team accelerating, or one person doing everything? A real team accelerating is a far stronger buy signal than a single hero coder, and we only flag the team pattern.

5. Step 5

   Classify the breakout into one of five signal types

   Engineering Hiring Burst, Infrastructure Buildout, Deploy Frequency Spike, Framework Migration, or Deceleration. The labels make the observed activity easier to inspect. They do not predict a financing event or prescribe an investment decision.

   In plain terms: we tell you which kind of observed move it is, such as team growth, infrastructure work, or a slowing pace. The label guides what to inspect next. It is not a timing estimate.

The green lines are the plain-English read of each step, what it means for the deal, not how the code runs. You never touch the code; you read the verdict.

Where this sits on the sophistication ladder

Eugene Schwartz mapped advertising claims onto five levels in Breakthrough Advertising (1966). Markets climb the ladder as buyers grow tired of repetition. Venture deal sourcing has been at Level 4 for a decade, the explicit choice we made was to ship a Level 5 product, where the mechanism is named, published, and reproducible by the buyer.

1. Level 1

   Make the bare claim

   “Find startups before everyone else.”

   First-to-market positioning. No mechanism. No proof. Markets at this stage will buy on the promise alone, but venture deal-flow stopped being a Level-1 market three decades ago.

2. Level 2

   Bigger, louder version of the same claim

   “The most comprehensive private-company database.”

   Tracxn, CB Insights, PitchBook all sit here. The claim is a quantity claim, bigger, more, faster. The buyer has heard it twenty times this quarter and stopped reading the headline.

3. Level 3

   Claim a unique mechanism

   “Proprietary AI scoring algorithm.”

   Harmonic, Glasswing, SignalFire Beacon. They name a mechanism but the mechanism is opaque, the buyer cannot verify it, reproduce it, or argue with it. The mechanism becomes a marketing asset, not a working tool.

4. Level 4

   Elaborate the mechanism

   “12-factor proprietary signal model trained on 2M datapoints.”

   More words around the same opaque core. The buyer feels persuaded but still cannot reproduce the result. The market begins to discount elaboration without proof.

5. Level 5

   Name the mechanism, publish the formula, identify with the buyer’s worldview

   “The Commit-Velocity Acceleration Engine.”

   The buyer is sophisticated. They have heard every claim, watched the elaboration arms race, and learned that the only mechanism worth trusting is one they can run themselves. We name it. We publish the formula. We hand them the regression code. The mechanism becomes shared vocabulary, and the conversation moves from “convince me” to “let me reproduce this.”

   ← We are here

How to falsify the engine

A Level-5 claim has to come with an off-switch. Here are three tests that, if any of them fail, would force us to retract the corresponding part of the mechanism. We publish them so the buyer can run them.

This section is for the buyer who wants to check our work, or hand it to an analyst who will. If the statistics below are not your language, that is fine, nothing here is something you have to run. In one sentence: each test is a way to prove the signal is real and not luck, and we publish them precisely because we expect them to hold.

• Claim: Observed public engineering activity is useful as a diligence signal, not a financing forecast.

  Test: Inspect the public activity, compare it against the published methodology, and corroborate it with independent diligence before deciding what to do next.

• Claim: Two-period confirmation reduces one-window noise

  Test: Compare an activity spike with the following public activity window. If it fades, treat it as noise rather than an actionable signal.

• Claim: Contributor concentration adds useful context

  Test: Inspect whether activity is broad across a team or concentrated in one account, then use that context in a wider diligence review.

Why we can publish the formula

The mechanism is published, sourced, and reproducible. We sell the live aggregation, the rhythm, the dashboard, the agent integration not the secret. The buyer who can reproduce our regression in a notebook is the buyer who trusts us most.