Straight answers to the questions investors ask most: how funding stages work, how VCs and angels make money, whether fundraising can be predicted, and what GitDealFlow actually tracks. Every answer is written to stand alone, with specific numbers where they exist.
The recurring theme across these answers: public data usually moves before announcements do. A startup's engineering activity shifts weeks before its round hits the press, which is the observation GitDealFlow is built on. The FAQ entries below go deeper on each piece of that story.
The first institutional round: typical sizes, instruments (SAFEs, convertible notes), and how investors evaluate teams when there is almost no data.
What seed capital buys, how round sizes have drifted upward, and the evidence investors expect before writing a seed check.
The transition from promising product to repeatable revenue machine, and what Series A investors actually underwrite.
When a bridge between rounds is healthy runway extension and when it is a down round in disguise.
Why valuations fall, what it does to cap tables and morale, and the warning signs investors watch for.
The five methods investors use to price an early-stage company, from comparables to scorecards, and when each breaks.
How each round erodes ownership, what pro-rata rights protect, and how founders and investors model it.
Management fees versus carry, why fund size dictates strategy, and the power-law math behind every portfolio.
Check sizes, syndicates, SPVs, and the tax mechanics that make angel returns lumpy but real.
Who sets terms, runs diligence, and takes the board seat, and why every round needs one.
Sources that lead the announcement cycle instead of lagging it, from regulatory filings to engineering momentum.
Building a monitoring stack for portfolios and target lists without drowning in manual CRM updates.
The seasonal patterns in fundraise timing and why runway, not calendars, sets the real clock.
The difference between a leading indicator and lagging coverage, and what makes a signal tradeable.
What 219 startup-period observations across 55 startups say about how far ahead engineering acceleration appears.
Base rates, false positives, and how to combine weak signals into a usable screen.
The 21 to 47 day window between a public GitHub acceleration and the round announcement.
The standard diligence stack and where public engineering evidence slots into it.
The honest signals of PMF and why most self-reported versions do not survive scrutiny.
The three signals (commit velocity, contributor growth, repository expansion), coverage of 350+ orgs in 15 sectors, and what we deliberately never collect.
How a GitHub starring history is scored 0-100 against ~75 validated unicorns to surface real scouting instinct.
New to all of this? Start with the Learn hub for the full guide library, or the glossary for one-line definitions. Ready-to-use checklists live at /checklists.