Title: Suggestion: Leverage ChatGPT Deep Research to Accelerate True AGI—Draft, Evaluate, Fine-Tune Workflow

[harishiew42]

Content:

I’d like to propose that OpenAI and the developer community leverage the full potential of existing ChatGPT Deep Research tools and APIs to accelerate progress toward true AGI. By systematically using these advanced models to:

1. Design AGI Patterns & Functions:
   Rapidly prototype new AGI architectures by iterating on core reasoning, memory, planning, and self-reflection modules, leveraging ChatGPT’s deep contextual understanding.

2. Draft → Evaluate → Fine-Tune Loop:
   Adopt an agile workflow where AGI prototypes are drafted using existing LLMs, rigorously evaluated with automated Evals (covering reasoning, planning, consistency, and generalization), and then fine-tuned or optimized using both prompt engineering and custom datasets.

3. Human–AI Co-Design:
   Encourage open collaboration where developers use ChatGPT not just for code and prompt generation, but also as an architectural and debugging partner to accelerate breakthrough solutions.

This structured pipeline—Draft → Evaluate → Fine-Tune—will help bridge the gap between current LLM capabilities and robust AGI by systematically identifying weaknesses and enabling rapid iteration. I strongly believe focusing deep research resources on this iterative process will push us closer to practical, safe, and scalable AGI within a shorter timeframe.

Would love to hear thoughts from other developers and the OpenAI team!

[FrdsJhr]

Appreciate the enthusiasm, but what you outlined is already the standard pipeline used by OpenAI and other leading labs for years — iterative prototyping, automated evals, fine-tuning, and human–AI co-design are all deeply embedded in current AGI research workflows.

If you’re serious about contributing to AGI development, it might be more useful to propose novel architectures, alignment strategies, or training innovations, rather than repackaging existing methodologies as if they’re new.

Otherwise, this reads more like a motivational summary than a concrete proposal.