OpenAI’s New Agents - The End of an AI Agent Developer?



AI Summary

Summary of OpenAI’s New Agents: Operator and Deep Research

Overview of AI Agents

  • AI agents are LLMs (large language models) that interact with their environment autonomously and can now reason about tasks.
  • A comprehensive AI agent developer tutorial is upcoming.

Operator Agent

  • Mimics human actions in a browser (scroll, type, click, navigate).
  • Based on a new model called CUA (Computer Using Agent).
  • Trained to output mouse and keyboard actions, not just text.
  • Can reason about each action it takes.
  • Limitations include lower accuracy and high costs (only available on the $200 plan).

Deep Research Agent

  • Trained for comprehensive research.
  • Searches the web, compiles sources into insightful reports.
  • Powered by the new 03 model.
  • Goes beyond providing average results, compiles novel insights.

Best Use Cases

  • Operator Agent: Internal process automation, especially for enterprises using internal software tools.
  • Deep Research Agent: Research-related tasks like market, lead, legal, scientific research, and internal document analysis.

Q&A on AI Agents

  • AI agent developers are still needed to train agents on complex internal tools.
  • Some AI agent frameworks may become obsolete if they didn’t plan for improved AI models.
  • Multi-agent systems will benefit from the ability to spawn multiple agents for tasks.
  • The AI agent market will favor platforms that anticipated AI improvements.
  • The API for Operator Agent could be separate or integrated into existing APIs, while Deep Research Agent will likely be integrated through the assistance API.
  • To prepare for the API release, start building now, don’t build around current limitations, and focus on ROI.

Future Evolution

  • Operator Agent might control computers through the ChatGPT app for tasks beyond the browser.
  • OpenAI likely has more agents to launch.

Practical Examples (Hypothetical, as agents are not yet in the API)

  • Operator Agent: Automating the setup of a customer portal in Notion.
  • Deep Research Agent: Conducting comprehensive research on the Bitcoin market and making investment decisions based on the report.

Conclusion

  • The video concludes with a demonstration of how the agents could be used for automating complex processes and conducting in-depth research, highlighting the transformative potential of these new AI agents.