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Product Understanding

Understand your product as it exists right now: what is specified, where it is implemented, why it changed, what may be affected, and how to fix drift.
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One Product Map for Humans and AI

Reqode turns product knowledge into connected artifacts, so teams can answer product, architecture, implementation, and change questions without rebuilding context manually.

Structured specs

Requirements, data entities, API operations, user interfaces, wireframes, tests, revisions, and branch-effective views.

Software units

A catalog of subsystems, units, files, dependencies, implementation guidelines, and unit-to-spec relations.

Change reasons

Change Requests connect goals, branches, affected specs, revisions, affected subsystems, and AI session summaries.

Problem signals

Findings and alignment checks show where code, specs, unit ownership, or architecture rules need attention.
Ask the Product

AI Expert answers with evidence

AI Expert is a read-only assistant for product investigation. It can start from a module, requirement, data entity, UI, API operation, software unit, implementation file, or a natural-language question.

It returns a structured answer with referenced artifacts, related source files, limitations, and recommended next actions.

Questions teams can ask

How does this flow work today?
Which specs, units, and files define this behavior?
Why was this API or UI behavior changed?
What could break if we change this rule?
Should the fix be in code, specs, units, or a Change Request?
Traceability

Trace from intent to files and back

Reqode connects specifications to source code through Software Units. A unit groups implementation files that represent one logical part of the system.

Teams can move from product behavior to specs, units, files, commits, findings, and next actions. Developers can also start from a file and trace back to product intent.

Product Understanding Workflow

Start from the thing the team already has: a question, a spec, a file, a Change Request, an Issue, or a Finding.

1

Choose a starting point

Use a module, requirement, API operation, UI, data entity, unit, source file, Change Request, Finding, issue, or test.

2

Explore the product map

Move through catalogs and relations to see current behavior, architecture, implementation, known problems, and change history.

3

Ask AI Expert

Use AI Expert when context spans multiple artifacts or code areas and the team needs references and source files.

4

Decide next action

Keep the answer, update specs with AI Analyst, hand off keys to a coding agent, adjust unit links, or create a Change Request.

5

Preserve the decision trail

Use Change Requests for meaningful changes so reasons, affected specs, branches, and AI sessions stay visible.

6

Verify after action

Use alignment checks and Findings to confirm that specs, units, files, and product behavior still match.

Product Knowledge Use Cases

Product understanding is not one workflow. It is a set of everyday questions across planning, implementation, QA, review, and support.

Onboard faster

New developers and analysts can inspect modules, artifacts, units, files, and known findings without waiting for a long handover.

Answer how it works

Ask AI Expert to explain current behavior with references to requirements, APIs, UIs, data entities, units, and source files.

Understand why it changed

Open Change Requests, affected specs, revisions, branch context, and linked AI sessions to reconstruct product decisions.

Plan product changes

Investigate affected requirements, API operations, UI screens, data entities, units, tests, risks, and implementation options.

Start from code

Trace a source file back to its software unit, linked specs, product behavior, and unit-specific implementation guidelines.

Investigate mismatches

Open Findings to see evidence, severity, affected artifacts, and solution paths for code, specs, units, or architecture.

Useful Across the SDLC

Different roles ask different questions, but they should work from the same product and implementation memory.

Product and analysis

Understand current behavior, affected areas, decision history, and controlled AI Analyst spec changes.

Architecture and development

Inspect unit catalog, dependencies, file ownership, subsystem guidelines, related specs, and MCP handoff context.

QA and review

Connect test planning, affected specs, Findings, alignment results, issue links, and release readiness.

Management and support

See active changes, open risks, branch state, current intended behavior, known problems, and planned fixes.

Before and After Reqode

The biggest shift is that product knowledge becomes operational: searchable, traceable, branch-aware, and usable by AI agents.

Without Reqode

  • Knowledge lives in docs, tickets, chats, and code comments.
  • AI agents infer intent from partial repository context.
  • Reviewers reconstruct why code changed by reading PRs and asking people.
  • Spec-code mismatches become tribal knowledge.

With Reqode

  • Product behavior is represented as connected artifacts.
  • AI Expert answers questions with references and source files.
  • Change Requests preserve the reason and scope of changes.
  • Findings and verifiers turn drift into actionable work.

Understand first. Change with confidence.

Reqode helps teams understand the product as it is, why it changed, where it lives in code, what may break next, and how to move forward.

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