>_ Analyst Engineering

Learning path

Requirements to UAT

One pipeline that carries a requirement from a workshop transcript to a signed UAT result, with nothing retyped along the way. It covers modern elicitation with an AI note taker, requirements written as structured data with permanent ids, MCP and scoped API tokens for Jira, Confluence, Xray, and Datadog, analyzing the diagrams you were handed, nine adversarial lenses that find the edge cases nobody wrote, use cases with real exception flows, UAT scenarios in business language, and a CI coverage gate that fails the release when a must-have requirement is not proven. Every stage comes with the scripts.

Written by Ahmed at Analyst Engineering, a Senior Technical Business Analyst with 10+ years in banking and payments.

The core series, in 8 parts

Each part is one stage of the pipeline, and each stage reads the artifact the previous stage produced. Read them in order the first time; after that they stand alone.

  1. 1.The Requirements to UAT Pipeline: One Repository From Workshop to Sign-Off
  2. 2.Elicitation With an AI Note Taker: The Agenda, the Question Bank, and the Diff
  3. 3.Requirements as Code: BRD and FRD in YAML With a Validator That Fails the Build
  4. 4.MCP and API Tokens for Jira, Confluence, Xray, and Datadog: The Analyst's Write Path
  5. 5.Analyzing Diagrams With AI: Turning an Architecture Picture Into Requirements and Gaps
  6. 6.The Blind Spot Review: Nine Adversarial Passes That Find the Requirements Nobody Wrote
  7. 7.From Use Cases to UAT Scenarios: Main Flow, Alternates, Exceptions, and a Sign-Off Pack
  8. 8.Test Strategy to Execution: The Pipeline That Runs Your Tests and Proves the Coverage

Phase 1

Gather: get the real requirements out of people

For you if: You run workshops, take notes, and write specifications, and you suspect the gaps are found too late.

By the end: You can generate a workshop agenda from your own artifacts, run an AI note taker with consent and a ban on inference, diff a transcript against the specification you already have, and turn candidates into requirements with permanent ids.

  1. 1 Series Part 1 The Requirements to UAT Pipeline: One Repository From Workshop to Sign-Off A working pipeline that carries a requirement from a workshop transcript to a signed UAT result: eight stages, three machine-readable formats, and four CI gates.
  2. 2 Series Part 2 Elicitation With an AI Note Taker: The Agenda, the Question Bank, and the Diff How to run a requirements workshop with an AI note taker: generate the agenda from the system, drive a question bank, and diff the transcript against the current spec.
  3. 3 Prompt Patterns for Requirements Work: Six Patterns I Reuse Weekly Six reusable prompt patterns for requirements work: grounded extraction, format contract, adversarial review, gap interrogation, traceability, testability.
  4. 4 Series Part 3 Requirements as Code: BRD and FRD in YAML With a Validator That Fails the Build Write business and functional requirements as structured YAML with stable ids, validate them with a schema, and render the BRD and FRD humans read from the same source.
  5. 5 BRD vs FRD: Two Documents, Two Jobs The difference between a Business Requirements Document and a Functional Requirements Document: what each covers, who reads it, and when you need both. With examples.
  6. 6 From Business Requirement to Functional Spec: Turning Intent Into Behavior How to turn a vague business requirement into a precise functional specification: decompose intent, define inputs and outputs, and write testable behavior. With examples.

Phase 2

Analyze: connect the tools and close the blind angles

For you if: Your requirements are written down and you want them grounded in the system that actually exists.

By the end: You can connect an assistant to Jira, Confluence, Xray, and Datadog with scoped tokens, publish idempotently from a pipeline, extract requirements and gaps from a diagram you were handed, and run nine adversarial lenses that find the edge cases nobody wrote.

  1. 1 Series Part 4 MCP and API Tokens for Jira, Confluence, Xray, and Datadog: The Analyst's Write Path Wire an assistant to Jira, Confluence, Xray, and Datadog with scoped API tokens and MCP: read safely, publish idempotently, and keep every write reviewable in git.
  2. 2 MCP for Analysts: Connecting AI to Jira and Confluence, Read-Only First What the Model Context Protocol is, how to connect an assistant to Jira and Confluence safely, and the six read-only questions that pay for the setup in a week.
  3. 3 Series Part 5 Analyzing Diagrams With AI: Turning an Architecture Picture Into Requirements and Gaps How to read a diagram you were handed with AI: extract actors, flows and rules, find the missing branches, and reconcile the picture against the contract and the code.
  4. 4 Series Part 6 The Blind Spot Review: Nine Adversarial Passes That Find the Requirements Nobody Wrote A repeatable review that finds the edge cases missing from your specification: nine lenses, one prompt each, run as a script before the requirements are signed off.
  5. 5 Decision Tables: Every Combination, No Gaps How to use decision tables to specify complex business rules completely: conditions, actions, rule columns, and collapsing combinations. The tool that leaves no case undefined.
  6. 6 Non-Functional Requirements: The Categories, With Measurable Examples What non-functional requirements are, the categories that matter, and how to write NFRs that are testable: measurable targets instead of adjectives. With examples.

Phase 3

Prove: use cases, UAT, and a coverage gate that fails the build

For you if: The specification is signed and you are accountable for proving the system does what it promised.

By the end: You can document use cases with alternate and exception flows, generate UAT scenarios in business language tagged to requirements, write a test strategy that makes decisions, run four layers in CI, and generate a sign-off pack from the last run.

  1. 1 Series Part 7 From Use Cases to UAT Scenarios: Main Flow, Alternates, Exceptions, and a Sign-Off Pack Document use cases as structured data, generate UAT scenarios in Gherkin from them, keep the requirement id on every scenario, and produce a sign-off pack automatically.
  2. 2 User Acceptance Testing: What UAT Proves That QA Cannot What user acceptance testing is, how UAT differs from SIT and QA testing, who writes the scenarios, and the entry and exit criteria that make a UAT cycle real.
  3. 3 Series Part 8 Test Strategy to Execution: The Pipeline That Runs Your Tests and Proves the Coverage Write a test strategy that makes decisions, turn conditions into an executable suite, run it in CI with Xray and Datadog, and generate the coverage proof automatically.
  4. 4 Building a Whole Test Plan With AI: From Requirements to Traceability Build a complete test plan with AI in seven steps: risk, scope, conditions, cases, data, environments, and a traceability matrix that proves nothing is uncovered.
  5. 5 The Requirements Traceability Matrix: From Requirement to Test, Proven What a requirements traceability matrix is, how to build one, and why it proves every requirement is designed, built, and tested. With a payments example.
  6. 6 Running API Tests in CI: Bruno CLI and Newman in GitHub Actions Run API test collections in CI: Bruno CLI and Newman in GitHub Actions, secrets, tags, JUnit and HTML reports, private networks, and flaky-test rules.
  7. 7 The Go/No-Go Call: Making a Release Decision Defensible A go decision is made under uncertainty. The analyst's job is to make it explicit, not make it disappear. The readiness dimensions and the evidence.

Go further

Guides and 1:1 coaching

The templates and playbooks behind this path, and a direct line if you want help wiring the pipeline to your own project and tools.

The BA Deliverables Template Pack From Vague BR to Functional Requirements Book a 1:1 coaching call

19 articles across three phases.

Free account

Practice the gap hunt on real artifacts

Mission 01 of the Labs hands you an OpenAPI contract, requirements, and sample responses, and asks for a gap register. A free account saves your progress and can email you the next playbook.

Your email is used to sign you in. Nothing else, unless you ask. Privacy.