Decide with complete context. Execute under control. Verify with evidence.
SDD keeps human decisions, agent actions, requirements, risk, tests, and proof inside one traceable project model.
SDD does not stop at generating content. It controls why a change exists, how it moves, and what proves the result.
See the whole project before changing it.
Every decision retains its source, rationale, reviewer, and downstream impact.
Turn approved intent into controlled action.
Human and agent work stays attached to the governing requirement and its evidence obligations.
Prove what happened, then improve the next decision.
Findings return through controlled feedback, never as an untracked automatic change.
SDD mirrors existing sources, adds project knowledge and traceability, then updates enterprise systems through explicit controlled actions.
Artifact identity is stable. Approval, coverage, and execution status remain separate signals.
A controlled statement of what must be true and why it matters.
The precise behavior, boundary, and acceptance conditions that answer the requirement.
A traceable unit of work or finding linked to the contract it changes or resolves.
A hazard, impact, mitigation, and verification path carried with the project.
A repeatable check and its execution evidence against the intended result.
Inspect how each governed record changes the project model and strengthens the final proof.
Start from the original reason for change before it is reduced to tickets, procedures, or test work.
Conversation, uploaded document, issue, ticket, MCP Add Intent, or operational finding.
SDD searches project memory, related items, vocabulary, duplicates, and previous decisions.
Intent record with source, author, rationale, candidate links, and suggested requirement direction.
The original context remains connected to every later requirement, change, and proof artifact.
Make the need precise enough to review, approve, implement, test, and audit.
Approved intent, imported requirement, business rule, process constraint, or regulatory obligation.
SDD applies category, hierarchy, lifecycle state, ownership, and review policy.
Controlled requirement with status, parent/child links, rationale, and change history.
Approval evidence explains why controlled execution may start and what scope it covers.
Translate the requirement into a process, product, or software contract with acceptance boundaries.
Approved requirement, project knowledge, architecture context, procedures, and historical decisions.
SolveRequirement and SolveSpecification create linked specifications and acceptance criteria.
Specification, acceptance criteria, assumptions, and implementation boundary.
Each specification remains traceable to the requirement and to the tests that will prove it.
Bring risk analysis into the same memory as requirements and validation, instead of rebuilding it at the end.
Requirement, process step, equipment, compliance context, hazard, failure mode, or tester remark.
SDD links risks to controls, mitigations, verification rows, and impacted artifacts.
Risk-control model with trace links to protocols, test cases, and evidence.
Validation can show which control answers which risk and where it was verified.
Prepare controlled execution with the right version, prerequisites, tools, data, suites, cases, and steps.
Specifications, risk controls, prerequisites, required tools, required data, and release context.
SDD versions test suites, test cases, protocols, TCF/TPO imports, and execution setup.
Protocol content and execution session ready for controlled testing or process verification.
The protocol is generated from source data instead of being manually reassembled.
Record manual or automated execution without separating step design from results, comments, and evidence.
Test case, versioned steps, expected result fields, execution session, tester comments, and evidence files.
SDD keeps each step and result together, tracks comments, deviations, found issues, and status.
Run results with pass/fail/N/A status, detailed answers, evidence, and issue links.
Execution evidence stays aligned with the designed step and its requirement/risk origin.
Produce documents and matrices from the same linked records used to manage the validated process.
Runs, approvals, releases, reference documents, risks, requirements, suites, cases, and history.
SDD assembles controlled exports, traceability matrices, revision records, and approval metadata.
DOCX, PDF, XLSX, traceability matrix, version history, and audit-ready evidence package.
The final proof references the source history instead of describing itself or disconnected documents.
Each group gets a different outcome, but the same source of truth.
Govern validated processes from business demand to release and verification evidence.
They get status that is based on linked requirements, issues, tests, and approvals instead of slideware or manual reporting.
Turn intent, meetings, and domain knowledge into requirements that can be reviewed.
They stop losing business nuance between conversation, ticket, specification, implementation, and validation.
Keep architecture decisions and project conventions available to every agent and contributor.
They get fewer isolated AI changes because agents work from persistent project memory and best-practice prompts.
Solve requirements, specifications, procedures, and issues with the business context already loaded.
They spend less time reconstructing why work exists and more time producing controlled, traceable changes.
Prove process requirements and acceptance criteria coverage with executable tests, test runs, and evidence.
They get a living coverage model instead of a spreadsheet rebuilt at the end of the validation effort.
Review traceability, risk controls, approvals, and evidence without chasing teams.
They get audit-ready proof that is continuously built as the validated process evolves.
Connect releases, process changes, pull requests, commits, test runs, and deployment evidence.
They get a cleaner answer to what changed, why it changed, and how it was validated.
Turn process findings, production findings, or user feedback into traceable issues and change requests.
They get problems linked back to the original demand and forward to the fix and validation evidence.
These are the detailed sales-page slides: who acts, what the SDD agent uses, what data is touched, and what proof comes out.
Three practical ways SDD connects enterprise sources, requirement cycles, and controlled execution actions.
Mirror Polarion requirements into SDD so regulated teams can keep the enterprise source while creating controlled specifications, tests, and proof in the validation workspace.
Improve the requirement cycle by connecting intent, review, specification, acceptance criteria, tests, and execution evidence instead of managing each step as a separate document activity.
Run controlled SDD actions from the console so AI-assisted implementation, traceability updates, and validation work stay attached to the project model.
Each card is intentionally narrow: one phase, one problem, one SDD fix, one proof chain.
Create the control model before execution accelerates.
Management, architects, implementation teams
PMO, architects, process owners
Quality, PMO, auditors
Auditors, quality, management
Convert informal demand into structured, reviewable requirements.
Product owners, SMEs, analysts
Business analysts, QA
Analysts, architects
Product owners, PMO
Make requirements implementable and testable.
Quality, analysts, implementation teams
Requirements engineers, PMO
Architects, implementation teams
QA, product owners
Turn specifications into controlled work, process updates, and traceable implementation changes.
PMs, scrum masters, tech leads
Implementation teams, PMO, DevOps
Implementation teams, AI agents
Developers, release managers
Build proof continuously while the process is executed.
QA, analysts
QA automation, implementation teams
Testers, validation leads
Validation, quality
Connect controls, releases, and audit evidence.
Quality, safety, validation
Compliance owners, auditors
Auditors, customers, quality
Release managers, quality
Keep learning loops connected to the original business demand.
Support, QA, implementation teams
Product owners, quality, PMO
Architects, tech leads
IT, security, platform teams