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Claude Sonnet 4 5 Advances AI Agents Toward OS Like Capabilities

October 3, 2025•Anabelle Nicoud•Original Link•2 minutes
AI Agents
Operating Systems
Claude Sonnet

Anthropic's Claude Sonnet 4.5 coding model demonstrates how AI agents could evolve into dynamic operating systems, raising questions about future app development and security.

Anthropic's latest coding model, Claude Sonnet 4.5, released earlier this week, signals a potential shift in how AI agents could function as dynamic operating systems, according to Ismael Faro, VP of Quantum and AI at IBM Research. Faro, who has integrated Claude Sonnet models into his workflows, believes these agents could revolutionize software development by creating and adapting tools on the fly.

Key Developments:

  • Dynamic Systems: Faro describes a "fundamental shift" from static applications to self-modifying systems that blur the line between code and prompts. He demonstrated how an agent built a custom team management tool from a single prompt, showcasing the model's ability to create apps dynamically.
  • Performance Gains: Claude Sonnet 4.5 ranks among the top performers on SWE-bench, solving 82% of real-world software engineering tasks—up from 72% in its predecessor, Claude Sonnet 4.
  • Future of App Stores: Faro poses critical questions: "Are we going to need app stores in the future?" as AI agents may generate tools tailored to individual user needs.

Challenges and Innovations:

  • User Interface: The rise of AI-built apps raises questions about design and interaction. Companies like Nothing are already experimenting with platforms like Playground and Essential Apps for AI-generated apps.
  • Security Concerns: Faro emphasizes the need for protocols like Agent Communication Protocol and A2A to ensure reliable and secure agent interactions. IBM Research's BeeAI framework, including its RequirementAgent, aims to address these reliability gaps.

Industry Implications:

  • Hardware Collaboration: OpenAI's partnership with Jony Ive's LoveFrom hints at future AI-centric hardware designs.
  • Enterprise Readiness: Sandi Besen of IBM Research notes that reliability remains a blocker for widespread agent adoption in production environments.

Faro concludes that security must be prioritized: "We are going to need agents with more privilege than applications to prevent broken security."

For more insights on AI agents, visit IBM Think.

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About the Author

David Chen

David Chen

AI Startup Analyst

Senior analyst focusing on AI startup ecosystem with 11 years of venture capital and startup analysis experience. Former member of Sequoia Capital AI investment team, now independent analyst writing AI startup and investment analysis articles for Forbes, Harvard Business Review and other publications.

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