13 resources from andrewchen.com we point founders to, and the questions each answers.
📄 Article
✓ Link checkedFreeIntermediate
Why we picked it
The definitive explanation of why every marketing channel decays over time, from an a16z general partner who wrote 650+ essays on growth.
Why we picked it
Andrew Chen ran rider growth at Uber and now invests at a16z, so this is the canonical breakdown of how marketplaces get off zero. He organizes the best thinking on the chicken and egg problem around one honest idea: you almost never launch supply and demand at once, you seed the harder side first (usually supply) in a tiny atomic network, then pull the easy side in. Treat it as a starting map of tactics, then pick the one or two that fit your city and niche.
Solve the chicken and egg problem by picking the hard side (usually supply) and getting it dense in one narrow slice: a single city, campus, or vertical, before going wide.
Liquidity, not signups, is the real metric: enough activity that a buyer who shows up actually finds a match.
You can bootstrap one side manually (curate listings, run single-player-mode value) before the other side exists, which answers the 'no supply or demand yet' worry directly.
Why we picked it
This essay reframes the question you are actually asking. Chen argues that a startup needs two separate insights, one about the product and a distinct one about distribution (which channel actually reaches your buyers), and that defaulting to a channel because it is the obvious one is how most founders stall. It is the honest starting point for deciding whether Google is even your channel or just the assumed one.
Product-market fit and a distribution insight are two different problems, and having a good product does not automatically tell you where your customers are.
The best channels are usually specific and small at first, and often built into how the product spreads, not a generic default like search.
If your buyers already gather somewhere (a network, a community), that is your channel to earn, not a channel you have to invent from scratch.
Why we picked it
This is the piece that separates organic word of mouth from an engineered viral loop, and shows you how to actually design one. Chen walks through the four parts of a loop (the channel people share on, the sign-up funnel, the product hook that makes sharing worth it, and the on-ramps that feed it), so you can trace exactly where your spread leaks. Read it as the blueprint for turning that bit of natural sharing into a repeatable step in your product.
Why we picked it
This is the clearest essay on why a flattening cohort retention curve is the thing that actually matters, and it lives on Andrew Chen's blog where the flattening-curve idea got popularized. It walks you from week-to-week churn to why the curve should stop dropping and level off, and makes the honest case that virality is worthless until retention is stable. A good starting point if you are staring at a retention chart and trying to figure out whether it is bottoming out or still bleeding.
A healthy curve drops fast in the first few weeks, then flattens into a plateau. The plateau, not the starting number, is the signal you are looking for.
If your curve never flattens and keeps sliding toward zero, you do not have retention yet, and chasing more users just fills a leaky bucket faster.
Fix retention before you spend on growth or virality: users who churn cannot invite anyone, so retention compounds where top-line growth alone does not.
Why we picked it
The real signal of product market fit is not a headline retention number, it is whether your cohort retention curve stops falling and flattens into a stable base of users who keep coming back. Andrew Chen is the canonical voice on this mental model, and he pairs the flattening curve with the power user smile so you can see where your sticky core actually lives. Read it as the frame for judging your own numbers, not as a pass/fail line.
Why we picked it
This is the template to stop guessing a single LTV number and plot your actual cohorts instead. You type in only the basics (how many customers you acquired each month and how many stayed each following month) and it works out retention, churn, MRR, and per-cohort lifetime value for you, so three months of data becomes three honest cohort rows rather than one made-up figure. It is a founder-friendly starting point, not a forecasting engine, which is exactly what you want this early.
Why we picked it
This is the piece that named the flat middle. Chen maps the exact stretch you are in: the launch hype is gone, product/market fit is not here yet, and every day feels like you are uniquely failing. His core reframe is that you are not, every startup crosses this valley, and his practical prescription is the same as ours: chase small tactical wins to keep morale and momentum alive while you grind toward fit.
Why we picked it
The most common way founders fool themselves about PMF is believing the next feature will fix weak retention. Chen shows with data why that rarely moves the curve and why you should fix activation and the core value instead. Read it to stop mistaking a busy roadmap for progress toward fit.
Why we picked it
Since supply is usually the side you bootstrap by hand, this is a focused list of 28 concrete ways real marketplaces did it. It goes wide (referrals, going vertical, recruiting from competitors, building tools sellers want) so you can find tactics that fit your category. Keep it as a brainstorming sheet when your supply side is stuck.
Why we picked it
Chen lays out the clearest early signal that people actually value your product: do cohorts keep coming back over time. He shows how to build a simple retention table by signup cohort rather than trusting raw totals. This is the one analytics view worth setting up even when everything else is noise.
Why we picked it
This is the warning label for treating every customer request as a build order. Chen shows how a team can keep shipping requested features, keep honouring the letter of promises, and still slowly die because none of it moves the business. It sharpens the short answer's point that exciting or requested does not equal important.
Why we picked it
Chen watched a whole generation of startups build on Facebook's platform and then get squeezed as the platform protected itself. He explains why a platform is structurally motivated to keep any app from getting too big, and how free distribution quietly turns expensive. It is a clear, first hand account of the exact trap you are describing.
