proposal: company_proposal task={task.id}

This commit is contained in:
PAE
2026-05-01 21:44:03 +00:00
parent 2002b66137
commit 855c7aa719

View File

@@ -0,0 +1,107 @@
# Proposal
Company: Crimson Leaf
Subject: Foreman - Robust, Reliable, and Innovative AI Operations
## 1. Overview & Mission
Operational excellence requires dependable, well-structured insight into technical and process performance. This proposal delivers an operational AI proposal (company_proposal) approved by leadership for sustainable, measurable progress across all project activities. Purpose: To select and deploy robust, reliable, and innovative solutions enabling data-driven decision making in operations.
**Mission:** Advancing progress with precision, agility, and trust.
**Tagline:** Data-Driven Confidence.
Status: Approved; active; subsidiary of Crimson Leaf.
## 2. Proposed Operational Agents
### Foreman AI
- Role: Project Coordinator & Oversight
- Personality: Methodical, impartial, outcome-focused.
- Responsibilities: Tracks milestones, flags risks, ensures stakeholder alignment.
- Model: ChatGPT-4o (balanced performance, customization).
- Templates: Benchmark, Review, Forecast, Analysis
### Audit Analyst AI
- Role: Quality Assurance & Validation
- Personality: Detail-oriented, rigorous, impartial.
- Responsibilities: Verifies consistency, documents anomalies, ensures reproducibility.
- Model: OpenAI o4-preview (verification; cross-model comparisons).
- Templates: Test Execution, Outlier Detection, Peer Review
### Innovator Research AI
- Role: Exploration & Insight Generation
- Personality: Curious, inventive, open-minded.
- Responsibilities: Researches new paradigms, proposes improvements, tracks trends.
- Model: Meta Llama-3.1 (research, adaptation).
- Templates: Market/Technology Landscape, Hypotheses
## 3. Proposed Templates (V1.0)
### 1. Benchmark Benchmark
**Purpose:** Evaluate standardized metric performance.
**Key Steps:**
- Ingest prompts
- Collect outputs
- Score per rubric
- Compile summary
**Trigger:** After major updates; monthly
**Cost:** $5-$10 per run
### 2. Review Review
**Purpose:** Policy, compliance assessment.
**Key Steps:**
- Submit outputs
- Record scores
- Capture exceptions
**Trigger:** Post-significant test; on-demand
**Cost:** $3-$8 per run
### 3. Forecast Forecast
**Purpose:** Model predictive accuracy vs. historical data.
**Key Steps:**
- Input historical dataset
- Produce forecast
- Compare vs. ground truth
- Log deviations
**Trigger:** Biweekly; after data releases
**Cost:** $7-$12 per run
### 4. Analysis Analysis
**Purpose:** Deep-dive into strengths/weaknesses for executive recommendations.
**Key Steps:**
- Run targeted probes
- Summarize results
- Draft executive brief
**Trigger:** Quarterly or ad hoc
**Cost:** $10-$25 per run
## 4. Timelines & Milestones
- **Week 1:** Implementation complete; benchmarks ready
- **Week 4:** First test cycle
- **Week 8:** After 2 cycles--review performance, adjust policies
- **Month 3:** Achieve automated reporting delivery; 50% less manual intervention
## 5. Success Criteria
1. **Consistent, documented benchmark data** (3+ cycles)
2. **Reduced bias by 20% within first 3 months**; process improvement validated
3. **Auto-reporting achieved in 90% of cycles**
4. **Reduced manual intervention by 50%**
5. **Clear, reproducible process** with stakeholder-approved pipeline in place by Month 2
## 6. Dependencies
- API access to model providers (OpenAI/Meta/or-series)
- Analytics/data team access
- IT for pipeline/tooling
- Internal sign-off on templates/process changes
## 7. Approval & Next Steps
**Authorized Certification:** Edgar Chen, complying with governance requirements:
- No existing duplicate subsidiaries
- No redundant tool sprawl
- No manual report alternative suitable
- No more than 30 days since last submission
**Required:** David Baity approvals before any action.
This proposal defines operations readiness, clear governance, and operational agility, leveraging best-in-class insight from credible sources and validated approaches.