How PRIMS Works in Practice
A requirements-to-implementation pipeline that leverages AI strengths while keeping humans in control of decisions.
AI Empowers Shift Left, Humans Lead
AI excels at pattern recognition, integration understanding, and quality assessment. PRIMS leverages these strengths while the framework manages granularity and fidelity. Humans lead discussions; AI proposes options. Feedback loops refine until approval.
AI Proposes
- ✓Feature decomposition into stories
- ✓Story decomposition into tasks
- ✓Contract extraction and re-proposals on feedback
- ✓Deterministic code generation from approved specifications
Humans Decide
- ✓Stakeholder alignment and initial shaping
- ✓Review, approve, reject, or request refinement
- ✓Promote, demote, or capture contractual obligations
- ✓Theoretical approval before code generation
PR gates verify adherence, not decisions. Trust has to be earned.
PRIMS knows this.
The Requirements Pipeline
From diverse inputs to validated specifications. AI consolidates; humans decide.
Feature Synthesis
Multi-source ingestion consolidates requirements, tech specs, user stories, and constraints into validated feature specifications.
Contract Extraction
AI extracts contractual obligations with lifecycle tracking. Hierarchical filtering prevents over-extraction and downstream cascade failures.
Artifact Generation
From a single decomposed source of truth, tailored audience-specific artifacts can be generated. Technical, business, and compliance stakeholders each get what they need.
Multi-Audience Artifact Generation
Comprehensive one-size-fits-all documentation risks effective engagement. Audience-specific artifacts mean stakeholders get exactly what they need, when they need it—resulting in fewer excuses and delays.
| Discovery | Implementation | Validation | |
|---|---|---|---|
| Technical | API contracts | Implementation details | Test scenarios |
| Business | User value | Metrics & ROI | Acceptance criteria |
| Compliance | Regulatory mapping | Security validation | Audit trails |
Story generation is a valid handoff point. Teams can take validated stories and implement using their preferred methods. The same pipeline could extend to data science and process engineering domains.
Development Team Choices
Once specifications are validated, development teams choose their path. PRIMS supports multiple approaches—the method is not mandated.
High-Scoring INVEST Stories
Traditional implementation using well-structured stories with clear acceptance criteria. Teams work from specifications without AI pairing.
Prescriptive AI Pairing
AI-led paired programming with minimal improvisation. Execution follows approved specifications closely, supervised by humans.
The choice is the development team's. PRIMS ensures whatever path is chosen starts from validated, unambiguous specifications.
What PRIMS Does Not Do
PRIMS does not guarantee correctness.
AI synthesis produces fit-for-purpose outputs. Correctness remains a human judgment.
PRIMS does not remove accountability.
Decisions are captured and attributed. The system makes accountability visible, not absent.
PRIMS does not replace engineering judgment.
AI surfaces options; humans choose. The friction is intentional.
Early Access
PRIMS is in active development. We are looking for opportunities with teams who want to go faster but value trust and predictability over raw speed.
Get Started