product-loop

Solid

Discovery, specification, launch, and learning for a product in one loop. Build-or-stop calls, MVP wedges, demand tests, customer interviews, PRDs, requirements, user journeys, acceptance, positioning, onboarding, rollout, pricing, pivots.

AI & Automation 4 stars 1 forks Updated yesterday MIT

Install

View on GitHub

Quality Score: 80/100

Stars 20%
23
Recency 20%
100
Frontmatter 20%
70
Documentation 15%
100
Issue Health 10%
80
License 10%
100
Description 5%
100

Skill Content

# Product Loop One product decision cycle in four phases: **Discover** what deserves building, **Specify** what must be true, **Launch** to a bounded audience, then **Learn** whether the bet paid. Enter at the phase the evidence supports and stop at the next decision, rather than running all four by default. ## Phase Selection | Situation | Phase | | ------------------------------------------------------------- | -------- | | The problem, demand, or wedge is still unproven | Discover | | Discovery is validated and behavior must be pinned down | Specify | | The change is built and needs a staged audience | Launch | | The experiment, launch, or sales attempt has produced results | Learn | Entering the wrong phase is the common failure: writing requirements for an unvalidated problem, or claiming lessons from a launch that never shipped. Name the phase and its evidence before starting. ## Ground Rules These apply to every phase. - Separate observations, supplied evidence, inferences, and assumptions. Never convert enthusiasm into proof. - Treat market size, demand, willingness to pay, and competitor claims as current facts that require primary evidence. - Do not invent quotes, logos, metrics, demand, research, legal requirements, availability, or support capacity. - Do not contact customers, create accounts, mutate a CRM or analytics, publish pages, buy ads, or spend money witho...

Details

Author
fmind
Repository
fmind/dotfiles
Created
4 months ago
Last Updated
yesterday
Language
Go
License
MIT

Integrates with

Similar Skills

Semantically similar based on skill content — not just same category