Review & scale

First principle

Scaling is reading the evidence and pouring fuel on what works. Do not scale before product, market, and channel actually fit. Most growth is just doing more of the few things that already convert — and cutting the rest.

Key steps

1. 1

   Review the evidence with AI

   Review this round's evidence with AI: what worked, what didn't, what the data says. See it clearly before you decide.

2. 2

   Confirm fit before scaling

   Before scaling, confirm fit: is there retention, is there repeat, are the unit economics positive? No fit, no fuel.

3. 3

   Double down on the winning channel and offer

   Pour resources into the channel and offer that already work, and do more of what is already converting.

4. 4

   Systematize and automate the winners

   Systematize and automate the parts that work so they run repeatably, reliably, and cheaply.

5. 5

   Cut losers, turn evidence into next intent

   Cut the parts that did not work, and turn what you learned this round into the intent you validate next round.

Copy-ready prompts

Here is the key data and context from my round:
- Channels and performance: [leads, paid, cost per channel]
- Retention/repeat: [data]
- Unit economics: [revenue per customer, cost per customer]
- My observations: [your own sense and findings]

Help me:
1. Judge objectively: have I reached product-market-channel fit? Give the basis.
2. Point out what is already converting and worth doubling down on, and what should be cut.
3. If there is no fit yet, tell me the single most important intent to validate next round.

The fit I have confirmed is: the working channel [channel] and the working offer [offer], with unit economics [data].

Help me build a concrete scale plan:
1. How to grow the volume on this channel and offer next.
2. Which parts must be systematized or automated first to support more volume.
3. Which non-working things to cut now, and where to redeploy the freed-up resources.