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Human Docs Mirror

2 min read

Generated index of the human docs mirror. Each page is a mechanical transform of the canonical human doc.

Playbook mirror​

  • Human Overview — The interactive guide to the knowledge hub, helping you understand its structure and explore how ideas connect across the ecosystem.

    Playbook​

A living collection of contributor-built modules for building microproducts that turn data into value, moving from shared foundations into the analytics development lifecycle: frame, build, and operate.

Intro​

Start with the shared concepts and mission behind the Build Trilemma docs.

  • What Is a Microproduct? — The core definition: a focused product that turns data into value through an experience, workflow, or utility.
  • Our Approach — The four-step method we use to turn a problem into a microproduct: identify the problem, identify the data, build the pipeline, build the microproduct.
  • Mission — The reason this open knowledge hub exists and the outcomes it is meant to create.

Frame​

The planning layer of the analytics development lifecycle, organizing content around defining opportunities, understanding users, scoping microproducts, and analyzing whether an idea is worth building.

  • Frame — Validate whether a microproduct is worth building and feasible to deliver before execution.
  • Ideation — Identify demand, available data, and the minimum useful outcome before the product shape hardens.
  • Design — Translate requirements and learnings into concrete specifications before implementation.
  • Architecture — Choose the pipeline, storage, serving model, and operating constraints that can support the product.
  • Data Stack & Analytics Engineering — Apply software engineering discipline to data workflows so the product can be tested, refreshed, observed, and reused.

Build​

The development layer of the analytics development lifecycle, organizing content around designing, developing, testing, and deploying microproducts through iterative implementation.

  • Build — Execute, validate quality, and deliver a reliable MVP through focused delivery workflows.
  • Delivery Workflow — Translate validated scope into focused build tasks and working product slices.
  • QA Methodology — Use quality gates, behavior-driven checks, and review norms to keep AI-assisted builds reliable.
  • Release — Key release-readiness criteria, including a graph of how these relate to other components of the playbook.
  • Deploy Quickstart — Ship your microproduct for free using only GitHub and the Vercel Hobby plan.

Operate​

The operational layer of the analytics development lifecycle, organizing content around operating, observing, learning from, and improving shipped microproducts over time.

  • Operate — Own distribution, learning, and iteration after launch so the product keeps improving.
  • Resources — Curated references that help builders execute faster without changing the playbook hierarchy.
  • Authors — The people and organizations listed in the shared author registry for the docs.