fteplusai

🥈Silver

FTE+AI is a 30-60-90 day program framework for replacing outsourcing vendors with AI-augmented teams. It guides R&D organizations through the entire vendor replacement process, from initiation to execution. The framework is designed to integrate with existing workflows and tools, providing a structured approach to transitioning from vendor-dependent operations to AI-driven teams.

81130Updated Today

Intermediate30min to implementautomation

Saves ~240 min per use

Quick InstallView Source

git clone https://github.com/mitkox/fteplusai.git

Works with:

Claude

Overview

About This Skill

How to Use

1. **Define the Scope:** Clearly outline the vendor services to be replaced (e.g., 'customer support outsourcing' or 'software development augmentation') and the specific tasks or processes involved. Use tools like Jira, Trello, or a simple spreadsheet to document current vendor dependencies. 2. **Audit & Map:** Conduct a detailed audit of the vendor’s current workflows, tools, and outputs. Identify pain points (e.g., slow turnaround, high costs) and success metrics (e.g., defect rates, response times). Tools like **Process Street** or **Miro** can help visualize workflows. 3. **Select AI Tools:** Research AI tools that can replicate or enhance the vendor’s tasks. Prioritize tools with: (a) integration capabilities (e.g., Slack, GitHub, Jira), (b) scalability for your team size, and (c) transparent pricing. Use **G2** or **Capterra** for comparisons, and request demos or free trials. 4. **Create a Phased Plan:** Break the transition into 30-60-90 day phases using the FTE+AI framework. For each phase, define: (a) specific goals, (b) AI tools to implement, (c) internal team roles, and (d) risk mitigation strategies. Share the plan with stakeholders for feedback. 5. **Execute & Iterate:** Start with a pilot project (e.g., automating a single task) to test the AI tools and gather feedback. Use the insights to refine the plan for broader deployment. Monitor KPIs like cost savings, efficiency gains, and quality improvements using dashboards (e.g., **Tableau**, **Power BI**). **Tips for Better Results:** - Involve the vendor early in the process to reduce resistance and leverage their expertise. - Start with low-risk, high-impact tasks to build confidence in AI tools. - Allocate a portion of the vendor’s budget to training and upskilling internal teams. - Document lessons learned at each phase to refine future transitions.

Setup & Installation

Quick Install

No install command available. Check the GitHub repository for manual installation instructions.

Alternative Install (Git Clone)

git clone https://github.com/mitkox/fteplusai

Requirements

Claude Code or compatible AI agent
Works with: Claude

Quick Start Guide

Install the Skill

Copy the install command above and run it in your terminal.

Open Your AI Agent

Launch Claude Code, Cursor, or your preferred AI coding agent.

Try It Out

Use the prompt template or examples below to test the skill.

Customize

Adapt the skill to your specific use case and workflow.

Usage Examples

Prompt Template

Use the FTE+AI 30-60-90 day framework to plan the replacement of [VENDOR_NAME] in [DEPARTMENT/TEAM] with an AI-augmented team. Start by auditing the vendor's current services in [SPECIFIC_TASKS/AREAS]. Then, design a phased transition plan that includes: (1) [PHASE_1_GOAL] by day 30, (2) [PHASE_2_GOAL] by day 60, and (3) [PHASE_3_GOAL] by day 90. Include specific AI tools or models to be implemented at each phase, and outline the risks and mitigation strategies for the transition. Reference the FTE+AI framework for structure and best practices.

Example Output

### FTE+AI 30-60-90 Day Plan: Replacing AcmeCorp’s QA Outsourcing with AI-Augmented Teams

**Current State Audit:**
AcmeCorp’s QA team relies on AcmeCorp’s outsourced QA vendor, which handles 85% of manual regression testing for the company’s mobile app and web platform. The vendor employs 12 full-time testers, costing $180,000 annually. Key pain points include: (1) 3-week turnaround for test cycles, (2) 15% defect leakage into production, and (3) limited scalability during peak releases. The vendor uses a proprietary test management tool that doesn’t integrate with AcmeCorp’s Jira or CI/CD pipeline.

**Phase 1 (Days 1-30): Foundation & AI Tool Selection**
*Goal:* Audit current QA processes and select AI tools to automate 30% of regression testing.
- **Audit:** Map all test cases in AcmeCorp’s Jira to identify redundant or low-value tests. Use a script to extract test data and categorize by priority (P0-P2).
- **AI Tool Selection:** Evaluate three AI-powered testing tools: (1) **Testim** for AI-driven test maintenance and self-healing, (2) **Applitools** for visual regression testing, and (3) **Functionize** for autonomous test generation. Prioritize Testim for its seamless Jira integration and 40% reduction in test maintenance time.
- **Risk Mitigation:** Address vendor pushback by framing the transition as a cost-saving initiative (projected $120K annual savings) and involving the vendor in the AI upskilling process to retain institutional knowledge.

**Phase 2 (Days 31-60): Pilot Implementation & Hybrid Model**
*Goal:* Deploy AI tools for a pilot project covering 20% of regression tests and train internal teams.
- **Pilot Project:** Select the mobile app’s login flow as the pilot, which has a high defect rate (12% in the last quarter). Use Testim to automate 15 test cases, reducing execution time from 6 hours to 45 minutes. Integrate Testim with AcmeCorp’s Jenkins pipeline for continuous testing.
- **Hybrid Model:** Retain 3 vendor testers to manually test edge cases and exploratory testing, while training 5 internal QA engineers on AI tool usage. Conduct weekly syncs to address gaps.
- **Metrics:** Track reduction in test cycle time (target: 75% faster) and defect leakage (target: 5% or lower).

**Phase 3 (Days 61-90): Full Transition & Optimization**
*Goal:* Scale AI testing to 80% of regression tests and decommission the vendor contract.
- **Full Deployment:** Expand Testim to cover 80% of regression tests across web and mobile platforms. Use Applitools for visual regression testing on UI components. Deploy Functionize to generate new test cases for recently added features.
- **Vendor Transition:** Terminate the vendor contract after a 30-day knowledge transfer period. Redirect the $120K annual savings to hire 2 AI QA specialists and 3 internal testers to focus on high-value exploratory testing.
- **Optimization:** Implement a feedback loop where AI tools continuously learn from production defects and vendor testers’ insights. Set up a dashboard in Tableau to monitor test coverage, execution time, and defect rates in real-time.

**Risks & Mitigation:**
- **Vendor Resistance:** Offer the vendor a consulting role to assist in AI tool adoption, ensuring a smoother transition.
- **AI Tool Limitations:** Start with low-risk, high-impact test cases to build confidence. Gradually expand to complex scenarios as the team gains experience.
- **Team Upskilling:** Partner with a QA training provider to upskill internal teams on AI testing tools. Allocate 10% of the vendor’s budget to training costs.

**Projected Outcomes:**
- **Cost Savings:** $120K annual reduction in QA expenses.
- **Efficiency Gains:** Test cycle time reduced from 3 weeks to 3 days.
- **Quality Improvements:** Defect leakage reduced from 15% to 3%.
- **Scalability:** Internal team can handle peak testing loads without vendor dependency.