A Streamlined Acquisition Strategy

THIS IS A REQUEST FOR INFORMATION (RFI) ONLY. This RFI is issued solely for information and planning purposes in accordance with FAR 15.201(e). It does not constitute a Request for Proposal (RFP) or a promise to issue one in the future.

A. Description

The agency is seeking information from industry on the availability of innovative software development services that leverage small, highly experienced, Artificial Intelligence (AI)-augmented teams. The Government is exploring alternatives to traditional, large-team Agile development models to achieve significant improvements in delivery speed, software quality, and cost-effectiveness.

B. Background

The agency is responsible for modernizing and maintaining a large portfolio of mission-critical software applications. Current development efforts often rely on conventional Agile Scrum teams of 7-9 personnel. While functional, this model can be subject to challenges including high coordination overhead, long lead times, and significant labor costs. In alignment with federal initiatives to adopt secure and trustworthy AI, the agency is conducting market research to identify next-generation service models that can deliver superior outcomes more efficiently.

C. Scope of Interest

The Government is specifically interested in a service model characterized by compact, hyper-efficient pods of elite practitioners whose capabilities are amplified by AI. Key concepts include:

• Three-Person Pod Structure: Self-sufficient teams composed of a BA/Scrum Master, a Full-Stack Tech Lead, and a Front-End Lead.
• Elite Senior Practitioners: Personnel with 8-15+ years of experience who serve as "AI Orchestrators."
• Mandatory FedRAMP-Compliant AI Toolchain: Use of an integrated set of AI tools (e.g., GitHub Copilot, Codeium, Mabl) for code generation, testing, and security.
• Outcome-Focused Metrics: Performance measurement based on "flow" metrics like Cycle Time, Lead Time, and Defect Escape Rate.

D. Requested Information

Interested parties are requested to submit a response, not to exceed 10 pages, addressing:

1. Company Information (Name, CAGE, UEI, Small Business Status).
2. Experience with small development teams (5 or fewer members).
3. Approach to integrating AI development tools into the SDLC.
4. Policies for ensuring Federal AI security and compliance (FedRAMP, CUI).
5. Representative resumes for the three key pod roles.
6. Comments on the viability of outcome-focused performance metrics.

1. Introduction

This guide provides a framework for developing a realistic IGCE for the unique AI-Augmented Agile Pod service model. A standard IGCE approach based on typical developer labor rates is insufficient. This model's value is derived from the combination of elite-level human talent and AI force multipliers, which yields significant total project cost savings despite higher individual labor costs.

2. Recommended Estimation Methodology

A dual-methodology approach is recommended: Top-Down "Comparison Estimating" (Primary Method) and Bottom-Up Detailed Buildup (Validation Method).

• Top-Down: Baseline a traditional 7-9 person team's cost, then apply a 50-60% efficiency reduction factor to estimate the total price for the pod-based service. This establishes the overall value and savings justification.
• Bottom-Up: Perform a detailed cost buildup based on market rates for elite, senior-level practitioners (10-15+ years experience), not standard developer rates. Include direct costs for the FedRAMP-compliant AI tool suite (ODCs) and standard indirect rates for Overhead and G&A.

IGCE Template: Sample Annual Cost Buildup for One AI-Augmented Pod

Cost Element	Unit	Quantity	Unit Cost (Notional)	Total Annual Cost
Direct Labor (Based on elite, senior-level talent)
Full-Stack Tech Lead	Annual Salary	1	$220,000	$220,000
BA / Scrum Master	Annual Salary	1	$180,000	$180,000
Front-End Lead / UX	Annual Salary	1	$190,000	$190,000
Subtotal Direct Labor				$590,000
AI Tooling (ODC)
Codeium / Windsurf	Seat/Month	3	$50	$1,800
Smartsheet Gov	Seat/Month	1	$100	$1,200
Jira w/ Atlassian Intel.	Seat/Month	3	$30	$1,080
Subtotal ODCs				$4,080
Indirect Costs
Overhead @ 35% of Labor	Rate			$206,500
G&A @ 15% of Total	Rate			$119,937
Subtotal Indirects				$326,437
Total Estimated Cost				$920,517
Fee/Profit @ 10%	Rate			$92,052
Total Estimated Price				$1,012,569

Section B: Supplies or Services and Prices/Costs

The contractor shall provide the services specified in Section C, Performance Work Statement. This is a Firm-Fixed-Price (FFP) contract. The price for each Contract Line Item Number (CLIN) shall be inclusive of all direct labor, indirect costs, materials, AI tooling licenses, and fee/profit required for performance.

Note: This pricing structure is a "capacity-based" approach. By pricing the integrated output of the "Pod-Month" rather than individual labor hours, the contract focuses on the total value and capability being delivered.

Table B-1: CLIN Structure

CLIN	Description	QTY	Unit	Unit Price	Total Price
0001	AI-Augmented Development Pod - Base Year	12	Months	________	________
1001	AI-Augmented Development Pod - Option Year 1	12	Months	________	________
2001	AI-Augmented Development Pod - Option Year 2	12	Months	________	________
3001	AI-Augmented Development Pod - Option Year 3	12	Months	________	________
4001	AI-Augmented Development Pod - Option Year 4	12	Months	________	________
Total Estimated Value (Base + All Options)					________

Section C: Performance Work Statement (PWS)

1.0 Objective

To acquire one or more self-sufficient, AI-augmented software development "pods" to provide full SDLC services, delivering high-quality, secure software with greater velocity and at a lower total cost of ownership.

2.0 Scope

The Contractor shall provide all personnel, expertise, management, and tools to operate stable, three-person AI-augmented development pods responsible for analysis, design, development, testing, security, deployment, and maintenance of software applications.

3.0 Specific Tasks

Task 1: AI-Augmented Pod Composition and Staffing. The contractor shall provide stable, dedicated pods with 100% allocated members, with roles as defined in the Staffing section above.

Task 2: AI-Augmented Agile Delivery Process. The contractor shall implement an Agile methodology adapted for a three-person, AI-driven pod, including modified ceremonies (e.g., stand-ups focused on AI collaboration) and new rituals (e.g., Prompt Engineering Reviews, AI Governance Check-ins).

Task 3: Security and Compliance. All development must occur in the Government-Furnished AWS GovCloud environment. The contractor shall provide and use a suite of AI tools that are, at a minimum, FedRAMP Ready or Authorized. The use of unapproved "Shadow AI" is strictly prohibited.

Task 4: Performance Management and Reporting. Performance will be measured against outcome-focused objectives. The contractor shall provide a Monthly Performance Report.

4.0 Performance Requirements Summary

Performance Objective	Performance Standard	Acceptable Quality Level (AQL)
Productivity	Deliver value efficiently from concept to deployment.	Cycle Time: 50% reduction from baseline. Deployment Frequency: 2+ per week.
Quality	Deliver high-quality, reliable, and maintainable software.	Defect Escape Rate: 25% reduction from baseline. Test Coverage: >90%.
Security	Deliver secure software compliant with Government standards.	Zero Critical/High vulnerabilities in production.
Cost-Effectiveness	Deliver exceptional value for the cost invested.	Cost per Feature: 60-70% reduction compared to traditional team baseline.

Section L: Instructions, Conditions, and Notices to Offerors

L.1 General Instructions

This acquisition is a total small business set-aside under FAR Part 19. Proposals shall be submitted electronically by the date and time specified on the SF 1449. Failure to conform to these instructions may result in rejection without evaluation.

L.2 Proposal Format and Content

Offerors shall prepare their proposal in four (4) separate volumes:

• Volume I: Technical Approach (20-page limit): Must detail the approach to execution, specifically addressing the nuances of the AI-Augmented Pod model. Must include:
  • Approach to Human-AI Collaboration (prompt engineering, review process).
  • Risk Mitigation Strategy for Key-Person Dependency and AI Over-reliance.
  • Performance Management Plan for measuring and reporting on KPIs.
• Volume II: Key Personnel (No page limit for resumes): Submit resumes for the three key roles, demonstrating they meet or exceed the minimum qualifications in PWS Table C-1.
• Volume III: Past Performance (5-page limit per reference): Provide up to three relevant past performance references from the last three years.
• Volume IV: Price: Complete the pricing schedule in Section B. No narrative is required.

Section M: Evaluation Factors for Award

M.1 Basis for Award

This is a competitive, best value tradeoff source selection (FAR 15.101-1). The non-price factors, when combined, are significantly more important than price. The Government may award to a higher-priced offeror if their proposal is determined to be technically superior.

M.2 Evaluation Factors (Descending Order of Importance)

1. Factor 1: Technical Approach: The most important non-price factor. Evaluates the understanding of the AI-Augmented Pod model, human-AI collaboration strategy, and risk mitigation.
2. Factor 2: Key Personnel: Significantly more important than Past Performance. Evaluates the extent to which proposed personnel meet or exceed PWS requirements.
3. Factor 3: Past Performance: The least important non-price factor. Assesses confidence based on recent and relevant past performance.
4. Factor 4: Price: Evaluated for reasonableness but not scored.