Codex vs Fable: Which AI Agent Picked the Better Problem?
Fable vs. Codex 5.6: A Knockdown, Drop-Out Fight
Introduction to the Challenge
- The speaker introduces a comparison between Fable and Codex 5.6, emphasizing the importance of asking AI to identify problems rather than just prompts or tools.
- The task involved allowing both AIs access to local files and Slack communications to define a problem and propose an automation solution.
Observations on Problem Recognition
- There is often a disconnect between verbal understanding of business problems and actual behaviors, especially in team settings.
- Both AIs identified different pain points, highlighting their unique approaches to problem-solving.
Analysis of Codex
- The speaker praises Codex for its efficiency in completing tasks without issues when given clear instructions.
- Notably, there has been significant user growth for Chat GPT work and Codex recently, surpassing Claude code usage.
Task Execution by Codex
- Codex was tasked with discovering information from Slack and creating an automation script while narrating its reasoning behind choices made.
Critique of Fable's Performance
- Working with Fable proved challenging due to multiple permission dialogues but ultimately yielded interesting results.
- Fable recognized that finding the right story is crucial in storytelling amidst numerous AI-generated narratives.
Insights from Fable's Approach
- Fable proposed building a tool for pre-pipelining ideas, which could help refine selections before execution—an innovative concept with potential leverage.
Limitations Identified in Problem Definitions
- Despite its strategic insights, Fable returned a narrow definition of the problem compared to what was expected.
Comparison of Problem Selection
- While Codex provided a practical solution focused on improving handoff packages for scripting, it missed identifying more pressing challenges within the business context.
Conclusion on AI Capabilities
- The speaker appreciates both AIs' strengths; however, emphasizes that better problem identification is essential for effective solutions.
The Future of Automation Skills
Importance of Effective Tools
- The video aims to address how AI can solve open-ended problems without needing users to specify exact needs upfront.
Development of Automation Solutions
- An automation skill is being developed that incorporates safeguards while allowing flexibility in addressing various personal or business challenges.
Enhancing AI Understanding
- This skill will enable deeper analysis into causation levels within projects or personal life scenarios before suggesting automations tailored specifically for users’ needs.
Leveraging Diverse Perspectives
Utilizing Multiple AIs
- Running both Fable and Codex simultaneously allows users to benefit from diverse perspectives leading to better decision-making regarding implementations.
Enjoyment in Using AI
- Engaging with AI should be enjoyable; it alleviates the burden of identifying problems while enabling collaborative tool-building through simple prompts.
Final Thoughts on Skill Release
Encouragement for User Engagement
- Users are encouraged to share their experiences using these tools and provide feedback on which approach they preferred after testing both AIs.
Overall, this markdown file captures key discussions around comparing two advanced AI systems—Fable and Codex—focusing on their capabilities in problem recognition and automation solutions.