OpenAI's NEW LLM Council - Here's how to use it

What is the LLM Council and How Can It Transform Decision-Making?

Introduction to the LLM Council

• The LLM Council, open-sourced by Andre Carpathy, allows multiple AI models (Chia Butt, Claude, Gemini, Grock) to answer questions and debate their responses.

• This tool can be set up in about 10 minutes using Cursor without any coding knowledge.

Benefits of Using Multiple AI Perspectives

• Many people rely on a single AI for answers; however, each model has biases and blind spots that can lead to incorrect information.

• Just like a board of directors seeks diverse opinions, the LLM Council provides varied perspectives from different AI models trained on distinct data sets.

Application in Business Decisions

• The council helps businesses make critical decisions by providing a range of viewpoints that challenge one another.

• By forcing AIs to critique and rank each other's responses, users gain insights that surpass what any single model could offer.

Comprehensive Analysis for Strategic Choices

• The council transforms significant business decisions into well-rounded plans by evaluating risks and returns comprehensively.

• It aids in identifying potential issues before committing resources or funds to new projects or strategies.

Cost-Efficiency and Problem-Solving

• The LLM Council serves as an affordable alternative for validating expensive ideas or consulting services.

• Its anonymous critique phase ensures unbiased feedback on contracts and proposals, highlighting unfavorable terms often overlooked by human reviewers.

How Does the LLM Council Work?

Stages of Operation

Stage One: Initial Opinions

• Users pose questions to four different AI models simultaneously; each generates independent responses without seeing others' inputs.

Stage Two: Review Phase

• All models review each other's responses anonymously. This prevents bias based on reputation while allowing them to rank answers based on accuracy.

Stage Three: Critique Stage

• Models actively criticize one another's arguments, revealing errors or logical inconsistencies that may not have been apparent initially.

Chairman Synthesis and AI Integration

Overview of Chairman Synthesis

• The final stage in the process is the chairman synthesis, where a trusted individual synthesizes insights from the debate, considering all rankings and critiques to produce a comprehensive answer.

• This synthesized response has been validated by four different AI systems before any action is taken.

Setting Up Cursor's IDE

• Traditionally, setting up such systems requires technical knowledge like running commands and installing Python, which can be daunting for business owners.

• The speaker introduces Cursor's IDE as an easier alternative that allows users to interact using natural language without needing coding skills.

Understanding IDE Functionality

• An Integrated Development Environment (IDE), like Cursor, enables users to describe their needs in plain English, allowing the system to build solutions automatically.

• While there are various IDE options available (e.g., Google's anti-gravity), Cursor is preferred for its user-friendliness and efficiency.

Getting Started with Cursor

• To begin using Cursor, users should visit cursor.com to create a free account and download the software. A link will be provided for easy access.

• After downloading, users will have options like opening projects or cloning repositories; they will clone a specific repository from GitHub.

Configuring the Environment

• Users need to set up their environment by copying setup instructions from GitHub into their project folder within LLM Council.

• An API key from Open Router is necessary for accessing various large language models (LLMs); this key can be created through openrouter.ai.

Finalizing Setup and Customization

• Once permissions are granted, the environment setup completes quickly—typically within two minutes—allowing immediate access to files and configurations.

• Users can customize which AI models are utilized in their console by updating configuration files based on their preferences.

Cost and Efficiency of Using AI Models in Business Decisions

Overview of Model Usage and Costs

• The speaker discusses setting GBT 5.1 as the chairman model for final synthesis, emphasizing its role in streamlining processes.

• Open Router charges based on tokens used; running queries through multiple models increases token usage significantly—approximately five times that of a single query.

• For strategic questions, costs can range from 5 to 20 cents per council meeting, depending on response length, making it a cost-effective option for businesses.

Return on Investment (ROI)

• Spending a few cents for four expert AI opinions is highlighted as one of the best ROI decisions, especially when significant business decisions are at stake.

• The speaker shares personal experience spending $30 to $40 on Open Router over several weeks, indicating affordability for real business applications.

Practical Application

• Viewers are encouraged to identify an important decision they face and utilize the LLM Council setup demonstrated in the video.

• Following the natural language approach shown will take about 10 to 20 minutes; participants should compare individual responses and critiques from the council.