CODITECT Deep Research Prompts
Overview
Structured prompts for conducting deep research to inform CODITECT product suite development. Each prompt is designed to extract actionable intelligence for maximum value creation.
CATEGORY 1: MARKET INTELLIGENCE
1.1 Competitive Positioning Analysis
OBJECTIVE: Analyze the AI coding assistant market to identify CODITECT differentiation opportunities
CONTEXT:
- CODITECT targets regulated industries (healthcare, financial services)
- Current pricing: Individual $15, Team $250, Enterprise $1,300/month
- Key differentiator: "20x ROI in 20 days" with compliance built-in
RESEARCH TASKS:
1. Map the current competitive landscape:
- GitHub Copilot (features, pricing, enterprise adoption)
- Cursor (technical architecture, growth trajectory)
- Codeium (enterprise positioning, compliance claims)
- Amazon CodeWhisperer (AWS integration depth)
- Tabnine (on-premise/privacy positioning)
2. Identify feature gaps in regulated industry support:
- Which competitors have SOC2 certification?
- HIPAA BAA availability?
- FDA 21 CFR Part 11 compliance claims?
3. Analyze pricing models and packaging:
- Per-seat vs. usage-based trends
- Enterprise discount structures
- Annual contract incentives
OUTPUT FORMAT:
- Competitive matrix (feature x competitor)
- Pricing comparison table
- White space opportunities for CODITECT
- Recommended positioning statement
1.2 Total Addressable Market Sizing
OBJECTIVE: Quantify the TAM/SAM/SOM for AI-native work automation in regulated industries
CONTEXT:
- CODITECT financial model assumes 10 starting customers scaling to 900K+ by month 60
- Target verticals: Healthcare, Pharma, Financial Services, Medical Devices
RESEARCH TASKS:
1. Size the overall AI coding tools market (2024-2028 projections)
2. Segment by industry vertical:
- Healthcare IT spending on developer tools
- Financial services automation budgets
- Pharma/biotech R&D software spend
3. Estimate regulated industry subset:
- Number of developers in HIPAA-covered entities
- Number of developers in FDA-regulated companies
- Number of developers in SOC2-required organizations
4. Calculate penetration rates:
- What % of developers currently use AI coding tools?
- What is adoption rate in regulated vs. non-regulated?
OUTPUT FORMAT:
- TAM/SAM/SOM waterfall with assumptions
- Market growth rates by segment
- Penetration model for CODITECT's first 3 years
1.3 Enterprise Buyer Journey Mapping
OBJECTIVE: Map the decision-making process for AI tool adoption in regulated enterprises
CONTEXT:
- CODITECT needs to convert Individual users to Team/Enterprise
- Enterprise represents highest LTV ($13,000) but only 5% mix target
RESEARCH TASKS:
1. Identify stakeholders in enterprise AI tool decisions:
- Who initiates evaluation? (Developer, Manager, CTO?)
- Who has budget authority?
- Who has security/compliance veto?
2. Map the typical evaluation process:
- RFP requirements for developer tools
- Procurement timelines
- Pilot program structures
3. Understand compliance gate requirements:
- Security questionnaire common questions
- Third-party risk assessment criteria
- Vendor management requirements
4. Identify deal accelerators:
- What shortcuts exist for faster procurement?
- Role of existing vendor relationships
- Impact of certifications (SOC2, ISO27001)
OUTPUT FORMAT:
- Buyer journey map (awareness → purchase)
- Stakeholder influence matrix
- Compliance requirements checklist
- Recommended sales enablement assets
CATEGORY 2: PRODUCT DEVELOPMENT
2.1 AI Agent Architecture Patterns
OBJECTIVE: Research optimal architectures for CODITECT's multi-agent orchestration
CONTEXT:
- CODITECT is classified as "Autonomous Agent" (not workflow)
- Key differentiator vs. Cursor/Copilot: dynamic task decomposition
- Must support regulated industry audit requirements
RESEARCH TASKS:
1. Analyze state-of-the-art agent architectures:
- Anthropic's recommended patterns (orchestrator-workers, evaluator-optimizer)
- OpenAI's Assistants API patterns
- LangGraph/LangChain agent patterns
- AutoGPT/BabyAGI learnings
2. Evaluate orchestration strategies:
- Single-agent vs. multi-agent tradeoffs
- Token economics for different patterns
- Latency vs. accuracy tradeoffs
3. Research compliance-compatible patterns:
- Audit trail requirements in agent systems
- Determinism vs. creativity balance
- Human-in-the-loop checkpoint patterns
4. Identify implementation libraries/frameworks:
- Production-ready vs. experimental
- Enterprise adoption evidence
- Maintenance/community health
OUTPUT FORMAT:
- Architecture decision record (ADR) template
- Pattern comparison matrix
- Recommended architecture for CODITECT
- Implementation roadmap
2.2 Developer Experience Optimization
OBJECTIVE: Research DX patterns that drive activation and retention
CONTEXT:
- Model assumes 33% monthly churn improving to 20%
- Time-to-value must be < 24 hours
- Self-serve everything (CAC constraints)
RESEARCH TASKS:
1. Analyze onboarding patterns of successful dev tools:
- Linear's "5-minute signup to first issue"
- Vercel's "deploy in seconds"
- Stripe's "Hello World" documentation
2. Research activation metrics:
- What correlates with long-term retention?
- "Aha moment" identification techniques
- Cohort analysis best practices
3. Study habit formation in developer tools:
- Daily active use drivers
- Notification/reminder strategies
- Community/social features
4. Evaluate personalization approaches:
- Learning user preferences
- Adaptive UI/UX
- Smart defaults
OUTPUT FORMAT:
- Onboarding flow wireframes
- Activation metric framework
- Retention playbook
- A/B test roadmap
2.3 Integration Ecosystem Strategy
OBJECTIVE: Define CODITECT's integration strategy for platform stickiness
CONTEXT:
- Integration depth = switching cost = reduced churn
- Must support IDE, CI/CD, project management, compliance tools
RESEARCH TASKS:
1. Map essential integrations:
- IDE: VS Code, JetBrains, Vim/Neovim, Eclipse Theia
- CI/CD: GitHub Actions, GitLab CI, Jenkins
- PM: Jira, Linear, Asana
- Compliance: Drata, Vanta, Secureframe
2. Research integration architectures:
- MCP (Model Context Protocol) patterns
- Plugin/extension development patterns
- OAuth/API best practices
3. Analyze marketplace strategies:
- Zapier's partner program
- Salesforce AppExchange economics
- VS Code extension marketplace
4. Identify regulated industry specific integrations:
- EHR systems (Epic, Cerner)
- Clinical trial management
- Financial compliance platforms
OUTPUT FORMAT:
- Integration priority matrix
- Architecture for integration platform
- Partner program structure
- Revenue share models
CATEGORY 3: COMPLIANCE & SECURITY
3.1 FDA 21 CFR Part 11 Implementation
OBJECTIVE: Research requirements and implementation patterns for FDA compliance
CONTEXT:
- CODITECT targets pharmaceutical, medical device, and biotech companies
- Must enable customers to maintain their 21 CFR Part 11 compliance
- Competitive differentiator opportunity
RESEARCH TASKS:
1. Analyze 21 CFR Part 11 requirements:
- Electronic signatures
- Audit trails
- System validation (IQ/OQ/PQ)
- Access controls
2. Research AI-specific FDA guidance:
- FDA's approach to AI/ML in medical devices
- Software as Medical Device (SaMD) implications
- Predetermined change control plans
3. Identify implementation patterns:
- Audit trail data models
- Signature workflow architectures
- Validation documentation templates
4. Analyze competitor approaches:
- How do enterprise dev tools address FDA?
- What validation services exist?
- Consulting firm partnerships
OUTPUT FORMAT:
- 21 CFR Part 11 compliance checklist
- Technical architecture for audit trails
- Validation documentation templates
- Go-to-market strategy for pharma
3.2 HIPAA Technical Safeguards
OBJECTIVE: Research HIPAA implementation requirements for healthcare AI tools
CONTEXT:
- Healthcare is a primary CODITECT vertical
- Must support PHI handling in development workflows
- BAA requirement for enterprise deals
RESEARCH TASKS:
1. Analyze HIPAA Technical Safeguards:
- Access controls
- Audit controls
- Integrity controls
- Transmission security
2. Research AI-specific considerations:
- LLM data handling requirements
- Prompt/response logging compliance
- Training data implications
3. Identify implementation patterns:
- Encryption at rest/transit
- Access logging architectures
- De-identification techniques
4. Analyze BAA requirements:
- Standard BAA template components
- Negotiation common terms
- Subcontractor chain management
OUTPUT FORMAT:
- HIPAA safeguards implementation checklist
- Technical architecture for PHI protection
- BAA template
- Healthcare sales playbook
3.3 SOC 2 Type II Certification Path
OBJECTIVE: Research SOC 2 certification requirements and timeline
CONTEXT:
- SOC 2 is table stakes for enterprise deals
- Must achieve Type II within first 18 months
- Enables faster procurement cycles
RESEARCH TASKS:
1. Analyze SOC 2 Trust Service Criteria:
- Security (required)
- Availability
- Processing Integrity
- Confidentiality
- Privacy
2. Research certification process:
- Type I vs. Type II differences
- Timeline expectations
- Cost ranges
- Auditor selection criteria
3. Identify common control requirements:
- Technical controls
- Administrative controls
- Physical controls
4. Evaluate compliance automation tools:
- Vanta, Drata, Secureframe comparison
- Evidence collection automation
- Continuous monitoring approaches
OUTPUT FORMAT:
- SOC 2 readiness assessment
- Control framework mapping
- Implementation timeline
- Vendor recommendations
CATEGORY 4: GROWTH & GTM
4.1 Product-Led Growth Mechanics
OBJECTIVE: Research PLG patterns for developer tools with enterprise expansion
CONTEXT:
- Model assumes 250% M1-3 growth through PLG
- Individual → Team → Enterprise land-and-expand
- Must achieve viral coefficient > 1.0
RESEARCH TASKS:
1. Analyze successful PLG dev tools:
- Notion's growth mechanics
- Slack's workplace virality
- Figma's collaboration hooks
2. Research viral loop patterns:
- Invitation mechanics
- Shared artifact virality
- Social proof elements
3. Study freemium optimization:
- Free tier feature selection
- Conversion triggers
- Usage limit psychology
4. Identify expansion revenue patterns:
- Seat expansion triggers
- Usage-based upsells
- Feature-based upgrades
OUTPUT FORMAT:
- Viral loop design document
- Freemium tier recommendation
- Expansion playbook
- Growth experiment roadmap
4.2 Enterprise Sales Motion
OBJECTIVE: Research enterprise sales processes for developer tools
CONTEXT:
- Enterprise represents highest LTV ($13,000) but requires sales motion
- Must complement PLG with sales-assisted conversion
- Compliance focus creates natural enterprise conversation
RESEARCH TASKS:
1. Analyze enterprise dev tool sales processes:
- Datadog's sales + PLG hybrid
- Snyk's security-led enterprise motion
- GitLab's open source to enterprise
2. Research sales team structure:
- When to hire first AE?
- SDR vs. AE ratios
- Sales engineering requirements
3. Study enterprise deal mechanics:
- Pilot program structures
- Proof of value frameworks
- Procurement acceleration tactics
4. Identify compliance-led sales strategies:
- Security questionnaire as conversation starter
- Compliance certification as deal closer
- Risk reduction positioning
OUTPUT FORMAT:
- Sales process design
- Hiring plan recommendation
- Deal stage definitions
- Sales enablement asset list
4.3 Pricing Strategy Optimization
OBJECTIVE: Research pricing strategies for maximizing revenue while maintaining growth
CONTEXT:
- Current pricing: Individual $15, Team $250, Enterprise $1,300
- Annual discount: 20%
- Model assumes 30% annual contracts
RESEARCH TASKS:
1. Analyze competitor pricing evolution:
- How have Copilot/Cursor prices changed?
- What prompted changes?
- Market response analysis
2. Research pricing models:
- Per-seat vs. per-active-user
- Usage-based components
- Outcome-based pricing potential
3. Study willingness-to-pay:
- Developer tool price sensitivity
- Enterprise budget benchmarks
- Value metric alignment
4. Identify packaging strategies:
- Feature bundling approaches
- Good/better/best tiers
- Add-on monetization
OUTPUT FORMAT:
- Pricing model recommendation
- Packaging strategy
- Price testing methodology
- Revenue impact projections
CATEGORY 5: TECHNOLOGY DEPTH
5.1 LLM Optimization for Regulated Industries
OBJECTIVE: Research LLM techniques optimized for accuracy in regulated contexts
CONTEXT:
- Regulated industries require high accuracy (cannot afford hallucinations)
- Must balance speed, cost, and quality
- Audit trail requirements for AI decisions
RESEARCH TASKS:
1. Analyze accuracy improvement techniques:
- Retrieval-Augmented Generation (RAG) patterns
- Fine-tuning vs. prompting tradeoffs
- Ensemble approaches
2. Research determinism strategies:
- Temperature/sampling parameter tuning
- Prompt engineering for consistency
- Caching/memoization patterns
3. Study explainability requirements:
- Chain-of-thought documentation
- Citation/attribution patterns
- Uncertainty quantification
4. Evaluate model selection:
- Claude vs. GPT-4 vs. open source for regulated
- Latency vs. accuracy benchmarks
- Cost optimization strategies
OUTPUT FORMAT:
- LLM architecture recommendation
- Accuracy improvement roadmap
- Explainability framework
- Model selection criteria
5.2 Eclipse Theia Platform Deep Dive
OBJECTIVE: Research Eclipse Theia architecture for CODITECT IDE component
CONTEXT:
- CODITECT may leverage Theia for custom IDE experiences
- Must support deep AI integration
- Enterprise customization requirements
RESEARCH TASKS:
1. Analyze Theia architecture:
- InversifyJS dependency injection
- Extension contribution points
- Monaco editor integration
2. Research AI integration patterns:
- Theia AI extension capabilities
- Language Server Protocol for AI
- Chat/agent UI patterns
3. Study enterprise deployment:
- Cloud hosting patterns (Gitpod, Codespaces)
- On-premise deployment
- Security hardening
4. Evaluate build/distribution:
- Custom branding approaches
- Extension bundling
- Auto-update mechanisms
OUTPUT FORMAT:
- Theia architecture decision record
- AI integration design
- Deployment architecture
- Build pipeline specification
5.3 Multi-Agent Orchestration Scalability
OBJECTIVE: Research scalability patterns for production multi-agent systems
CONTEXT:
- CODITECT's orchestrator-workers pattern needs scale for enterprise
- Token economics: 15x multiplier for multi-agent
- Must maintain audit trails at scale
RESEARCH TASKS:
1. Analyze production agent architectures:
- How does Devin handle complex tasks?
- Cognition Labs' orchestration patterns
- Enterprise agent deployments
2. Research scalability patterns:
- Horizontal vs. vertical scaling
- Async task execution
- Rate limiting/backpressure
3. Study observability requirements:
- Distributed tracing for agents
- Token usage monitoring
- Error cascade detection
4. Evaluate infrastructure:
- Serverless vs. containers
- Queue-based orchestration
- State management patterns
OUTPUT FORMAT:
- Scalability architecture
- Infrastructure recommendations
- Monitoring framework
- Cost projection model
CATEGORY 6: OPERATIONAL EXCELLENCE
6.1 Customer Success for Developer Tools
OBJECTIVE: Research customer success patterns that reduce churn
CONTEXT:
- Model targets 33% → 20% churn improvement
- Must scale with customer base (900K+ customers)
- Cannot be high-touch for Individual tier
RESEARCH TASKS:
1. Analyze dev tool customer success:
- How does Datadog handle scale?
- Stripe's developer support model
- Community-driven support patterns
2. Research automation opportunities:
- Chatbot/AI support tiers
- Self-service knowledge bases
- In-product guidance systems
3. Study health scoring:
- Leading indicators of churn
- Product analytics requirements
- Intervention trigger systems
4. Evaluate community building:
- Discord/Slack community patterns
- User-generated content curation
- Ambassador programs
OUTPUT FORMAT:
- Customer success org design
- Health scoring framework
- Automation roadmap
- Community strategy
6.2 Infrastructure Cost Optimization
OBJECTIVE: Research cloud cost optimization for AI-intensive workloads
CONTEXT:
- Model assumes 5% of revenue for cloud storage
- LLM inference is major cost driver
- Must maintain margins at scale
RESEARCH TASKS:
1. Analyze LLM cost structures:
- Token pricing trends
- Self-hosted vs. API tradeoffs
- Caching/deduplication opportunities
2. Research infrastructure patterns:
- Multi-cloud arbitrage
- Spot/preemptible instances
- Reserved capacity planning
3. Study optimization techniques:
- Model distillation for cost
- Request batching
- Speculative execution
4. Evaluate vendor negotiations:
- Volume discount structures
- Committed use contracts
- Startup credits programs
OUTPUT FORMAT:
- Cost model with projections
- Optimization opportunity matrix
- Vendor strategy
- ROI for infrastructure investment
Usage Instructions
Prompt Execution Priority
Immediate (Week 1-2):
- 1.1 Competitive Positioning Analysis
- 2.2 Developer Experience Optimization
- 4.1 Product-Led Growth Mechanics
Short-term (Month 1):
- 2.1 AI Agent Architecture Patterns
- 3.3 SOC 2 Type II Certification Path
- 4.3 Pricing Strategy Optimization
Medium-term (Quarter 1):
- 3.1 FDA 21 CFR Part 11 Implementation
- 3.2 HIPAA Technical Safeguards
- 5.1 LLM Optimization for Regulated Industries
Expected Output Integration
- Feed research outputs into product roadmap
- Update financial model assumptions based on market data
- Create executive summaries for investor updates
- Build sales enablement from competitive intelligence
Document Version: 1.0
Created: February 5, 2026
Author: Hal Casteel with assistance from Claude 4.5
For: CODITECT Product Development