Baseline Core

Product Introduction

1. Definition: Baseline Core is an open-source CLI tool and structured skills system designed for AI agent augmentation. It falls into the technical category of AI context grounding systems and productivity toolkits for generative AI.
2. Core Value Proposition: It exists to ground AI outputs in specific business context, eliminating generic responses. Its primary value is enabling AI tools (like Claude, ChatGPT, Copilot) to perform complex product tasks—market research, PRD writing, sprint planning, UX design—with consistency and brand alignment, using pre-loaded product methodologies and business knowledge.

Main Features

1. Pre-Built Skills Library (12 Skills): Encodes expert methodologies into reusable workflows. Skills like research-synthesis, ux-design, and strategic-advisory are directories containing prompts, reference chains, and output templates. The CLI (npx @baseline-studio/cli init) scaffolds these locally, enabling AI agents to execute multi-step tasks (e.g., competitor analysis → feature prioritization → sprint plan) using embedded logic.
2. Context Layer: Automatically injects business-specific data (context/core/identity.md, extended/users.md) into every AI interaction. This includes brand voice, user personas, product details, and competitor landscapes. Files are Markdown-based, version-controlled, and referenced dynamically by skills/frameworks to ensure outputs are on-brand and contextually accurate.
3. Frameworks & References (14 Frameworks, 34 Files): Provides battle-tested structures (frameworks/prioritization.md, frameworks/ux-heuristics.md) and reference materials guiding AI decision-making. These ensure outputs follow proven product management principles (e.g., RICE prioritization, Jobs-to-be-Done research) and maintain consistency across tasks and team members.
4. Tool-Agnostic Integration (AGENTS.md): The AGENTS.md file acts as a universal adapter. AI tools (Claude Code, Cursor, Copilot) read this file to auto-load relevant skills, context, and frameworks. For ChatGPT/Gemini, users upload AGENTS.md to provide the AI with the system’s structure and capabilities.

Problems Solved

1. Pain Point: Generic, ungrounded AI outputs lacking business-specificity or strategic depth. Baseline Core solves this by hardwiring company context and expert methodologies into AI workflows.
2. Target Audience: Startup founders, solo product managers, and technical teams without dedicated PM/UX roles. Specifically: SaaS founders validating markets, engineering leads writing specs, and growth teams designing user flows without specialized hires.
3. Use Cases:
   • Automated Market Research: AI agents use research-synthesis skill + competitors.md context to analyze competitors and generate SWOT reports.
   • Engineering-Ready Specs: product-communications skill + product.md context enables AI to draft PRDs with accurate technical and user context.
   • Brand-Aligned UX Design: ux-design skill + voice.md context guides AI to create user flows adhering to brand tone and usability heuristics.

Unique Advantages

1. Differentiation: Unlike fragmented prompt libraries or manual context injection, Baseline Core provides a unified, executable system with pre-integrated skills, context, and frameworks. Competitors lack its depth of pre-built product methodologies (12 skills, 14 frameworks) and CLI automation for setup.
2. Key Innovation: The structured file architecture (skills/, context/, frameworks/) combined with the AGENTS.md integration standard. This allows any compatible AI tool to dynamically access the entire system, enabling complex, multi-step agentic workflows grounded in live business data.

Frequently Asked Questions (FAQ)

1. How does Baseline Core integrate with ChatGPT?
   Users upload the AGENTS.md file to ChatGPT, providing it access to the system’s skills, context files, and frameworks. ChatGPT then references these during conversations to deliver context-grounded outputs.
2. Is Baseline Core suitable for non-technical users?
   While setup requires CLI usage (npx @baseline-studio/cli init), the Custom Setup service ($5,000) handles configuration and training. Daily usage involves interacting with AI tools (e.g., pasting prompts into ChatGPT), making it accessible to non-developers post-setup.
3. Can I add custom skills or modify frameworks?
   Yes. As an open-source system, all skills (/skills/), frameworks (/frameworks/), and context files are editable Markdown. Users can extend the system with proprietary methodologies or niche workflows.
4. What’s the difference between Core and Custom Setup?
   Core provides the generic system for self-setup. Custom Setup includes hands-on configuration: Trent writes your business context, builds custom skills, trains your team, and tunes the system to your specific workflows—all within one week.
5. Does Baseline Core work with local LLMs?
   Yes, if the local LLM tool (e.g., LM Studio, Ollama) can read project files like AGENTS.md or process uploaded context documents. Integration depends on the tool’s file access capabilities.