synthesis-llm-setup

What problem does it solve?

Many LLM platforms require different formats and delivery methods for instructions and knowledge, making multi-platform deployment time-consuming and error-prone. This guide consolidates a repeatable workflow for compiling, packaging, and delivering AI knowledge and custom instructions so projects work consistently across Claude, ChatGPT, Gemini, and similar systems.

Core Features & Use Cases

• Platform-specific instruction compilation: Assemble and produce tailored instruction files for Claude, ChatGPT, Gemini and other LLM targets.
• Knowledge concatenation and delivery: Build a single concatenated knowledge file and describe options for Git sync or manual uploads to each platform.
• Operational workflows and privacy model: Explain compilation commands, CI/CD handling of knowledge files, inheritance rules for including personal/team content, and verification steps for updates.
• Use Case: Prepare an enterprise AI assistant by compiling instructions for a client project, syncing the knowledge repository to Claude, and uploading the concatenated knowledge file to ChatGPT and Gemini.

Quick Start

Open the target LLM editor, copy the compiled project instructions into the platform's custom instructions field, and upload the concatenated knowledge file as the knowledge source.