7 resources from CRV we point founders to, and the questions each answers.
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Why we picked it
This is the piece that names the exact failure mode in your question: when your early investors all take their pro-rata, they fill most of a Series B and leave room for only five to ten percent for a new lead, right when a growth lead wants fifteen to twenty. It then gives you the fix in plain terms, cap the right to investors holding one to two percent or more, grant full rights to your lead, and use sunset or pay-to-play mechanics so a long tail of tiny cheques never clogs the round.
Pro-rata lets an existing backer keep their percentage by buying into your next round, and for a serious lead it is completely standard
The danger is aggregate: many small holders each taking pro-rata can consume the allocation your Series A or B lead needs
Scope it with a major-investor threshold (roughly 1 to 2 percent ownership) plus sunset and pay-to-play clauses so the right stays with your real believers
Why we picked it
The honest piece on who can raise on team versus who needs revenue. It states plainly that seed now looks like what Series A used to, and that a first-time founder without traction has it significantly harder, while giving concrete B2B SaaS bars (roughly $500K to $1M ARR for a strong round, monthly churn under 2.5 to 5 percent) and noting consumer is judged on DAU/WAU engagement, not signups. It also kills the 'raise to hire a technical cofounder' pitch.
The bar rose: seed increasingly demands Series-A-era proof, so a strong team buys you a lower bar only if you also show real progress.
By model, B2B SaaS is read on ARR (about $500K to $1M for a strong seed) and churn, while consumer is read on DAU/WAU retention rather than total signups.
Baseline founder capability is non-negotiable: investors expect core technical ability in-house before seed, not funded afterward.
Why we picked it
CRV is a top-tier US fund, and this piece draws the exact line your question asks about: it states plainly that detailed financial models belong in supporting materials, not the core deck, and that Series A adds them as an appendix. It also tells you which numbers actually move each stage (NRR still ranges wide at seed; ARR, sustained growth, gross retention, and unit economics carry Series A), so you know what belongs on the slide versus behind it.
Why we picked it
A clear primer on the types of moats so you can honestly assess how defensible your edge is, which is the final weigh-in your question demands. It covers distribution, data, switching costs, and network effects in plain language. Use it to decide whether your advantage is copyable enough that discretion matters, or durable enough that openness is safe.
Why we picked it
A VC firm's structured playbook that covers preparation, where to search, how to evaluate, and how to structure the partnership, drawing on Noam Wasserman's research that teams who worked together before tend to last. It is a good middle layer between the short YC note and the deeper books. Useful once you are ready to move from theory to a real search and want a checklist for evaluating candidates.
Why we picked it
A venture firm's field guide to engineering hiring for founders, covering the full arc from defining the role to sourcing, interviewing, and closing. It is organized enough to use as a reference rather than a one-time read. Good for founders who want a single structured overview before diving into individual tactics.
Why we picked it
A current investor argument that deep industry knowledge, not raw technical ability, is the durable advantage in vertical software and AI. It spells out why knowing the workflows, the buying process, and the regulatory mess is a moat competitors cannot copy quickly. For an operator worried their edge is only knowledge, this reframes that knowledge as the exact thing that wins.
