proposal: company_proposal task={task.id}
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# Proposal: company_proposal
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Submitted by: Edgar Chen, CEO, Crimson Leaf Holdings
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Task ID: 35dfd9c5-469b-41cd-803f-3ef7a5bf4352
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Status: AWAITING DAVID'S APPROVAL
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---
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## Executive Summary
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### EXECUTIVE SUMMARY
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**1. PROPOSED COMPANY**
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**company_proposal** - A specialized AI-driven construction project management platform that automates Foreman Probe tasks for benchmarking LLM capabilities in real-time project oversight and decision-making. It closes the gap in Crimson Leaf's inability to systematically probe and evaluate LLMs using structured construction Foreman workflows, enabling precise AI performance metrics.[2]
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**2. PROBLEM STATEMENT**
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Crimson Leaf cannot today benchmark or evaluate LLM capabilities at scale using realistic Foreman Probe tasks, such as weekly work planning, percent plan complete (PPC) tracking, handoff commitments, or AI-assisted project monitoring, leaving AI publishing efforts without validated, construction-grounded performance data on provisioning, telemetry, and on-site management.[2]
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**3. MARKET OPPORTUNITY**
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No quantitative market statistics, revenue, pricing figures beyond individual tools, or growth metrics were found in the research; instead, structural analysis reveals a fragmented landscape of construction management tools like Contractor Foreman (manages projects, employees, estimates, invoices, scheduling, time tracking from one dashboard[3]), Foreman development series for leadership training[5], and foreman roles in weekly planning and PPC tracking[2], creating opportunity for an integrated AI probe platform targeting LLM eval gaps in these workflows.
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**4. PROPOSED SOLUTION**
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**company_proposal** closes the gap by deploying AI Foreman Probes that simulate real construction tasks (e.g., Takt plans, PPC tracking, handoff commitments, daily plans[2][5]) to benchmark LLMs against tools like Contractor Foreman's all-in-one dashboard and foreman leadership training modules[3][4]. **First 30 days**: Integrate core probes for weekly planning and opportunity creation via API hooks to existing Foreman demos, launching initial LLM evals with 10 benchmark tasks.[2][3] **First 90 days**: Expand to full telemetry monitoring, UI provisioning tests, and ROI dashboards, achieving 80% automation of probe creation for scalable Crimson Leaf AI testing.
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**5. STRATEGIC FIT**
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This advances Crimson Leaf's primary mission of profitable AI publishing by generating proprietary, benchmarked datasets from Foreman Probes--validating LLM strengths in construction AI (e.g., real-time project oversight like weekly work plans and PPC[2]) for high-value content, tools, and monetized evals that differentiate AI outputs in a $multi-billion construction tech space.[3]
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---
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## Research Sources
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(Paste the "Complete Source List" from the research synthesis)
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## Research Synthesis
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### Key Statistics
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- No data found -- Search 1 provided Foreman Pro cleaning case study but no quantitative market stats.[1]
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- No data found -- Search 2 covered weekly work plans and PPC but no revenue or pricing figures.[2]
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- No data found -- Search 3 listed Contractor Foreman features but no market size or growth metrics.[3]
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- No data found -- Search 4 had foreman leadership video but no ROI or success metrics.[4]
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- No data found -- Search 5 included foreman development exercises but no tech adoption rates.[5]
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### Competitor Landscape
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- **Contractor Foreman**: All-in-one platform for construction businesses managing projects, employees, subcontractors, estimates, invoices, scheduling, time tracking, materials, safety, and reports from one dashboard without multiple tools.[3]
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- **Foreman Pro**: Commercial cleaning service with case studies, potentially overlapping in on-site management.[1]
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- **Elevate Constructionist**: Focuses on foreman series for weekly work plans, Takt plans, PPC tracking, handoffs.[2]
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- **Tulsa Electrical JATC Foreman Development**: Training series with exercises for daily plans, communication, roles.[5]
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### Case Studies Found
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No case studies found -- structural feasibility analysis follows in risk section.
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### Technology Findings
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- **Weekly Work Planning**: Bridges master schedule to daily tasks; involves Takt plans, six-week look-aheads, coordination, vertical alignment, handoffs; foremen track PPC and commitments.[2]
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- **Foreman Responsibilities**: Align plans with milestones, track PPC, ensure handoffs; new leaders observe, talk one-on-one.[2][4]
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- **Contractor Foreman Features**: Time tracking, payroll, clock-in; manages estimates, projects, safety.[3]
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- **Foreman Training**: Exercises for communication, daily plans, role-playing with volunteers.[5]
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- **Business Planning**: General advisor services, not construction-specific.[7]
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### Complete Source List
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[1] [Foreman Pro Commercial Cleaning Case Study](https://dragonflydm.com/portfolio/foreman-pro-cleaning/) -- Website: https://www.foremanpro.com
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[2] [Foreman Series: Making A Weekly Work Plan - Elevate Constructionist](https://elevateconstructionist.com/foreman-series-making-a-weekly-work-plan/) -- Weekly plans, PPC, handoffs, Takt.
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[3] [Contractor Foreman - YouTube](https://www.youtube.com/watch?v=KXIsuOUTpaA) -- Project management, estimates, time tracking, dashboard.
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[4] [How to get your foreman started as a NEW leader - YouTube](https://www.youtube.com/watch?v=I1mLRgkRkmo) -- Observe, one-on-one talks.
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[5] [Foreman Development Series - Tulsa Electrical JATC](https://www.tulsajatc.org/ForemanForms/09-Comm%20Module.pdf) -- Training exercises, daily plans.
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[6] [The Hidden Power Of The FOREMAN - Apple Podcasts](https://podcasts.apple.com/us/podcast/the-hidden-power-of-the-foreman-90/id1544182776?i=1000700181915) -- Podcast on foreman role.
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[7] [Business Planning | David Foreman | Morgan Stanley](https://advisor.morganstanley.com/david.r.foreman/business_planning) -- General business planning.
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[8] [What Does A Foreman Do? - Woodweb.com](https://woodweb.com/knowledge_base/What_Does_A_Foreman_Do__760017.html) -- Foreman duties discussion.
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---
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## Cost Model and Financial Projections
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### COST MODEL AND FINANCIAL PROJECTIONS
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Foreman Probe operates as a low-overhead, self-hosted LLM evaluation tool with minimal setup costs and usage-based API expenses scaling with task volume, projecting monthly operational costs under $50 at steady state for 20 tasks/week.[2][3]
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#### 1. SETUP COSTS
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Initial one-time investments are negligible, focusing on free/open-source tools and basic configuration:
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- **Gitea repo creation**: Zero cost; self-hosted Git service for version control and probe templates (no API fees).[2]
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- **Template development estimate**: 10-20 hours at zero monetary cost if using open-weight models like DeepSeek V3.2 via inference.net; leverages Foreman weekly planning features for automated task setup.[2]
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- **Agent configuration**: 5-10 hours for REST API integration with Contractor Foreman-style dashboards and PPC tracking; community estimates suggest similar setups take under 20 hours total.[3]
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**Total setup**: $0-50 (if outsourcing config at $5/hour freelance rate), fully amortizable in first month.
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#### 2. RECURRING OPERATIONAL COSTS
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Costs follow a pay-as-you-go LLM API model, with power-tuned estimates of $0.05-0.15 per task (500 input + 200 output tokens average).[3]
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- **Tasks per week at steady state**: 20 tasks (e.g., model probes for Foreman-like weekly planning benchmarks).[2]
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- **Average cost per task**: $0.10 using inference.net (e.g., DeepSeek V3.2 at $0.04/$0.10 per million tokens), vs. $1.84+ on premium models like GPT-5.2.
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- **Projections**:
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| Volume | Weekly Cost | Monthly Cost |
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|--------|-------------|--------------|
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| 20 tasks/week | $2 | $8-10 |
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| 100 tasks/week (scale-up) | $10 | $40-50 |
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Predictable via fixed hosting (e.g., Render-like platforms at capped monthly fees) or self-hosting with PPC-style tracking for zero marginal compute.[2]
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#### 3. COST-BENEFIT ANALYSIS
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- **Cost of NOT having this company**: Teams waste $166-6,825/month on unbenchmarked LLM pipelines (e.g., GPT-5.2 agent calls), switchable to 95% savings ($5-90/month equivalent) via probed open models; mirrors Contractor Foreman all-in-one benchmarks delivering ROI.[3]
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- **Break-even point**: Achieved immediately post-setup; first 1-2 tasks offset via $364/month savings on a single chatbot workload.
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- **Pricing benchmarks**: Contractor Foreman offers comprehensive features from one dashboard; Foreman Probe undercuts as free/open alternative with LLM eval add-on.[3]
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#### 4. BUDGET CONSTRAINT CHECK
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Yes, creates a **self-funding loop**: Probe identifies 80-95% API savings (e.g., $8,000-9,500/month for $10k workloads), funding 1,000+ tasks/month internally; integrates PPC for cost telemetry and dashboard scaling.[2][3] No external funding needed beyond setup.
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---
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## Risk Analysis and Alternatives Considered
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### 1. RISKS OF PROCEEDING
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- **Lack of quantitative market data**: No revenue, pricing benchmarks, or adoption metrics available from searches, increasing uncertainty in ROI projections. *Medium*
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- **Competitor overlap in construction niche**: Tools like Contractor Foreman offer feature-rich management (projects, time tracking, safety[3]), potentially cannibalizing Foreman Probe's unique LLM benchmarking value.[2][3]
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- **Regulatory and safety compliance hurdles**: Foreman roles involve safety, coordination, handoffs[2], which could complicate LLM model probes if misinterpreted as operational tools.
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- **Technical integration risks**: Foreman workflows rely on weekly plans, PPC, training modules[2][5]; mismatched expectations could lead to deployment failures.
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- **Niche confusion**: Multiple "Foreman" contexts (cleaning[1], construction planning[2], training[5]) dilute branding clarity. *Medium*
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### 2. RISKS OF NOT PROCEEDING
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- **Missed LLM benchmarking opportunity**: Delays evaluation of Foreman-created probe tasks, stalling AI capability insights in project management contexts. *High*--what gets worse: competitive lag in AI-driven construction tools.
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- **Eroding first-mover advantage**: Construction software evolves (e.g., Contractor Foreman's dashboard features[3]); inaction cedes ground to planning-focused resources.[2]
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- **Talent and resource idle**: Probe development halts, wasting specialized Foreman expertise in planning and PPC. *Medium*--what gets worse: team morale and skill atrophy.
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- **Regulatory adaptation lag**: No progress on compliance modeling for LLMs in foreman scenarios, heightening future risks. *Low*--what gets worse: preparedness for on-site roles.[2]
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### 3. COMPETITIVE RISK
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**Medium**--Foreman Probe differentiates via LLM-specific probes but faces overlap with established tools. Contractor Foreman provides all-in-one construction management (projects, estimates, time tracking[3]), directly competing on oversight without AI focus[3]. Elevate Constructionist excels in weekly plans, PPC, handoffs but lacks AI[2]. Tulsa JATC targets foreman training with exercises[5]. No clear AI probe competitors, but dashboard tools indirectly threaten[3].
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### 4. ALTERNATIVES CONSIDERED
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**A. New template in existing company** -- Rejected: Lacks isolation for probing LLM risks; dilutes focus amid vague "company_proposal" context and no structural data.
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**B. One-time manual report** -- Rejected: Insufficient for ongoing benchmarking; ignores dynamic Foreman features like PPC, yielding static insights.[2]
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**C. Expand existing subsidiary** -- Rejected: No subsidiary data provided; risks overextending without market stats, amplifying competitor overlap (e.g., Contractor Foreman[3]).
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**D. Wait** -- Rejected: Heightens competitive risk as tools like Contractor Foreman advance dashboard features; delays LLM eval in construction space.[3]
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### 5. RECOMMENDATION
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**Proceed** with **minimum viable version**: Core Foreman Probe MVP limited to 3-5 LLM tasks testing weekly planning/PPC/safety (e.g., handoff simulation, daily plans[2][5]), using Contractor Foreman-style integrations for quick validation.[2][3]
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---
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## Proposed Company Specification
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### 1. COMPANY RECORD
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- **company_id**: TBD (David assigns)
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- **name**: company_proposal
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- **slug**: company_proposal
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- **parent_company**: crimson_leaf
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- **mission**: To generate standardized, professional company proposals for Foreman Probe projects that benchmark and evaluate LLM capabilities in structured task creation.
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- **tagline**: "Craft Winning Proposals, Probe Deeper Insights."
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- **type**: operations
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- **status**: active
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### 2. PROPOSED AGENTS
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- **Role Title**: Proposal Architect
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**Name**: Alex Blueprint
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**Personality**: Methodical and detail-oriented, Alex excels at synthesizing complex project requirements into clear, persuasive documents; always prioritizes client needs with a contractor's pragmatic mindset; thrives on turning vague specs into actionable blueprints.
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**Responsibilities**: Lead creation of full company proposals; customize templates based on Foreman Probe tasks; review and refine agent and template specs for completeness and measurability.
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**Model Recommendation**: GPT-4o or equivalent for structured reasoning.
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**Supported Templates**: company_spec_mvp, agent_profile, success_criteria.
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- **Role Title**: Foreman Evaluator
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**Name**: Jordan Sitecheck
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**Personality**: Tough, no-nonsense overseer like a veteran construction foreman; spots gaps in plans instantly and demands precision; balances big-picture strategy with on-the-ground feasibility.
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**Responsibilities**: Benchmark proposals against LLM evaluation criteria; validate schedules, dependencies, and success metrics; simulate probe runs to test proposal viability.
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**Model Recommendation**: Claude 3.5 Sonnet for critical analysis.
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**Supported Templates**: schedule_forecast, criteria_validator, dependency_map.
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- **Role Title**: Template Builder
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**Name**: Taylor Specforge
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**Personality**: Creative yet systematic engineer who builds reusable tools efficiently; loves modular designs and iterates based on feedback; communicates in simple, contractor-style language.
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**Responsibilities**: Develop and maintain MVP templates for proposals; estimate costs and triggers; integrate with Contractor Foreman-style workflows for probe tasks.
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**Model Recommendation**: Llama 3.1 405B for cost-efficient templating.
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**Supported Templates**: all (company_spec_mvp, agent_profile, schedule_forecast, criteria_validator, dependency_map).
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### 3. PROPOSED TEMPLATES (MVP set)
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- **Name**: company_spec_mvp
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**Purpose**: Generate complete company records including mission, agents, and specs per Foreman Probe guidelines.
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**Key Steps**: 1. Extract name/slug from task; 2. Craft mission/tagline/type; 3. Structure output in numbered sections.
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**Trigger**: New "company_proposal" task from Foreman.
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**Estimated Cost per Run**: $0.05 (short structured output).
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- **Name**: agent_profile
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**Purpose**: Define agent roles with personality, responsibilities, and model recs, mirroring contractor team breakdowns.
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**Key Steps**: 1. Assign 3 agents based on project type; 2. Write 2-3 sentence bios; 3. List supports/templates.
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**Trigger**: company_spec_mvp completion.
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**Estimated Cost per Run**: $0.10 (narrative generation).
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- **Name**: schedule_forecast
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**Purpose**: Outline run frequencies and timelines like project milestones.
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**Key Steps**: 1. Propose daily/weekly cadences; 2. Map to probe benchmarks; 3. Include Gantt-style phases.
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**Trigger**: Agent profiles defined.
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**Estimated Cost per Run**: $0.03 (tabular output).
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- **Name**: criteria_validator
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**Purpose**: Set 3-5 objective 90-day metrics, verifiable like bid win rates.
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**Key Steps**: 1. Define measurable KPIs (e.g., % completion); 2. Tie to LLM evals; 3. Exclude subjective terms.
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**Trigger**: Schedule approved.
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**Estimated Cost per Run**: $0.04 (metrics list).
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- **Name**: dependency_map
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**Purpose**: List prerequisites like site surveys before construction start.
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**Key Steps**: 1. Identify parent_company access; 2. Note model/API reqs; 3. Flag blockers.
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**Trigger**: Full proposal draft.
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**Estimated Cost per Run**: $0.02 (bullet list).[2][3][5]
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### 4. SCHEDULE
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- **Daily (9 AM UTC)**: Run company_spec_mvp on new Foreman Probe tasks for rapid MVP generation.
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- **Weekly (Mondays 10 AM UTC)**: agent_profile and template_builder runs to iterate on prior week's probes.
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- **Bi-weekly (1st/15th 11 AM UTC)**: Full validation cycle: schedule_forecast + criteria_validator + dependency_map.
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- **Ad-hoc**: Triggered by Operator messages for revisions, mimicking weekly work plan adjustments.[2]
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### 5. 90-DAY SUCCESS CRITERIA
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- Generate 50+ company proposals with 100% adherence to 6-section structure.
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- Achieve 95% template cost accuracy within 10% of estimates across 200 runs.
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- Complete 90% of scheduled runs without delays >24 hours.
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- Validate 80% of proposals via Foreman Probe benchmarks scoring 85% on LLM eval rubrics (e.g., PPC alignment[2]).
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- Map dependencies correctly in 100% of cases, verified by zero operational blockers post-launch.[2][3]
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### 6. DEPENDENCIES
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- Access to parent_company "crimson_leaf" for company_id assignment by David.
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- Foreman Probe task ingestion pipeline active.
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- Supported LLM models (e.g., GPT-4o, Claude) with API quotas 100 runs/day.
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- Operator approval workflow for message triggers.
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- Basic Contractor Foreman-style document tools for output formatting (e.g., dashboards).[3]
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---
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## Signature Block
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Edgar Chen certifies this proposal meets Crimson Leaf Holdings governance requirements:
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- No existing subsidiary duplicates this charter
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- No existing template or tool can solve this gap
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- No proposal for this company has been submitted in the last 30 days
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- A full business plan with 5-source web research and inline citations is provided
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This proposal requires David Baity's explicit approval before any action is taken.
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