Strategic Recommendation: Prompt Execution Strategy
Executive Decision
Question: Should you run the Master Prompt as-is or break it down?
Answer: BOTH — but in a specific sequence.
Rationale
The Master Prompt Problem
| Issue | Impact | Evidence |
|---|---|---|
| Size | Context window saturation | 7,500 lines = ~150k tokens |
| Scope | Attention dilution | 12+ domains in single prompt |
| Depth vs. Breadth | Shallow outputs | Can't go deep on any single topic |
| References | Noise ratio | ~2,000 lines of footnotes |
Running the master prompt as-is will produce:
- High-level overview across all domains ✓
- Production-ready code in specific areas ✗
- Actionable implementation details ✗
- CODITECT-specific customization ✗
The Modular Prompt Advantage
| Benefit | Impact |
|---|---|
| Focused context | Full attention on single domain |
| Deeper outputs | Production-ready artifacts |
| Iteration capability | Refine specific areas |
| Parallel execution | Multiple team members simultaneously |
Recommended Execution Strategy
Step 1: Master Prompt for Strategic Orientation (1x)
Run the full master prompt once with a specific framing:
**INSTRUCTION**: Do NOT generate detailed code or configurations.
Instead, provide:
1. A prioritized implementation roadmap (phases, milestones, dependencies)
2. Critical technology decision summary (with your recommendations)
3. Risk assessment for each major component
4. Integration points between components
5. Estimated effort (weeks) for each major deliverable
Format as executive briefing document, max 3,000 words.
Purpose: Get the strategic landscape view and validate your understanding.
Time: 30-45 minutes Output: Strategic roadmap document
Step 2: Tier 1 Research Prompts (5x in parallel)
Execute these independently (can be parallelized across team members):
| Prompt | Owner | Output | Time |
|---|---|---|---|
| PROMPT 1: LangGraph Workflow | AI Team | Workflow engine code | 4 hrs |
| PROMPT 2: OpenFGA RBAC | Security | Authorization model | 3 hrs |
| PROMPT 3: immudb Audit | Platform | Audit layer code | 3 hrs |
| PROMPT 4: DeepSeek-R1 | MLOps | LLM deployment | 5 hrs |
| PROMPT 5: Airbyte Hub | Data | Connector configuration | 4 hrs |
Purpose: Generate production-ready technical specifications.
Total Time: ~19 hours (5 hours if parallelized) Output: 5 deployable technical modules
Step 3: Integration Synthesis (1x)
After Tier 1 research completes, run a synthesis prompt:
**CONTEXT**: [Paste summaries from each Tier 1 prompt output]
**TASK**: Design the integration architecture that connects:
1. LangGraph workflow engine
2. OpenFGA authorization
3. immudb audit trail
4. DeepSeek-R1 inference
5. Airbyte data ingestion
**REQUIREMENTS**:
- Event-driven communication patterns
- Shared state management approach
- Error propagation strategy
- Observability instrumentation
- Deployment sequencing
**OUTPUT**: Integration architecture document with sequence diagrams.
Purpose: Ensure components work together cohesively.
Time: 2-3 hours Output: Integration architecture specification
Step 4: Tier 2 Research Prompts (7x, prioritized)
Execute in priority order based on business needs:
| Priority | Prompt | Dependency |
|---|---|---|
| P1 | NeuralProphet Forecasting | Data ingestion |
| P1 | Month-End Close Workflow | LangGraph engine |
| P1 | Open Finance Brazil | Airbyte connectors |
| P1 | PostgreSQL RLS | None |
| P1 | NLG Variance | DeepSeek-R1 |
| P2 | Dagster Orchestration | Airbyte |
| P2 | Brazilian ERPs | Airbyte |
Purpose: Build out vertical-specific capabilities.
Total Time: ~32 hours Output: 7 additional technical specifications
Step 5: Product Pack Assembly (1x)
Combine all outputs into cohesive product packages:
**CONTEXT**: [Paste all Tier 1 + Tier 2 outputs]
**TASK**: Package these components into the CODITECT FP&A Automation Pack:
1. Define module boundaries and interfaces
2. Create pricing tier feature matrix
3. Write customer-facing documentation
4. Design onboarding workflow
5. Specify support escalation paths
**OUTPUT**: Product package specification ready for engineering handoff.
Purpose: Transform technical specs into shippable product.
Time: 4-6 hours Output: Product release specification
Execution Timeline
Week 1:
├── Day 1-2: Master Prompt strategic run
├── Day 3-5: Tier 1 Prompts (parallel)
└── Day 5: Integration synthesis
Week 2:
├── Day 1-3: Tier 2 Prompts P1 batch
├── Day 4-5: Tier 2 Prompts P2 batch
└── Day 5: Product pack assembly
Week 3+:
└── Engineering implementation begins
Total Research Investment: ~60 hours Parallelized Timeline: 2 weeks Output: Complete technical specification for FP&A Automation Pack
What NOT to Do
❌ Don't run the master prompt and expect production code
- 7,500 lines of prompt → high-level output, not production artifacts
❌ Don't skip the master prompt entirely
- Losing strategic context makes modular prompts disconnected
❌ Don't run all prompts sequentially
- Wastes time when many can run in parallel
❌ Don't expect first-pass outputs to be final
- Each prompt may need 2-3 iterations for production quality
Resource Allocation Recommendation
| Role | Assignment | Time Commitment |
|---|---|---|
| AI Engineer | Prompts 1, 4, 10 | 12 hours |
| Security Engineer | Prompts 2, 3 | 6 hours |
| Data Engineer | Prompts 5, 6, 11, 12 | 18 hours |
| Platform Engineer | Prompt 9 | 4 hours |
| Product Manager | Prompts 7, synthesis, packaging | 14 hours |
| Tech Lead | Master prompt, integration, review | 10 hours |
Total Team Hours: ~64 hours across 6 people Calendar Time: 2 weeks (with parallel execution)
Success Criteria
The research phase is complete when you have:
- Strategic roadmap from master prompt review
- LangGraph workflow implementation (PROMPT 1)
- OpenFGA authorization model (PROMPT 2)
- immudb audit integration (PROMPT 3)
- Local LLM deployment guide (PROMPT 4)
- Airbyte connector configuration (PROMPT 5)
- Integration architecture document
- At least 3 Tier 2 prompts completed
- Product pack specification
- Engineering handoff document
Final Recommendation
Execute the hybrid approach:
- Run master prompt once for strategic orientation
- Decompose into modular prompts for production-quality outputs
- Parallelize execution across team members
- Synthesize into products after technical specs complete
This approach extracts maximum value from the comprehensive research while producing actionable artifacts for CODITECT product development.