Agentic Systems, AR, OpenAI, and the Future of Enterprise Integration
Tom and Cameron explore Apple's AR announcements, OpenAI's enterprise connectors, and how agentic systems are reshaping the future of work.
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Agentic Systems, AR, OpenAI, and the Future of Enterprise Integration
Episode Summary
In this extended episode, Tom Spencer and Cameron Rohn break down a range of developments across augmented reality, creative tooling, and enterprise agent infrastructure. They begin with reactions to Apple’s AR announcements and the future of spatial content creation, before transitioning to OpenAI’s push toward enterprise integration via MCP servers, streamable HTTP, and connector-based workflows. The conversation spans voice agents, DeepWiki integration marketplaces, ChatGPT’s new memory capabilities, and the architecture of agent subgraphs and tracing. With real-world demos of the Open Agent Platform and Tableau workspaces, they explore how agentic systems will shape task execution, vertical SaaS, and the evolving nature of work in an AI-first world.
Topics Covered
- Apple’s AR announcements and the role of eye tracking in creative tools
- OpenAI’s connector architecture and MCP server framework
- Voice agents, memory features, and streamable HTTP
- Enterprise AI workflows: data access, auth, and optimization
- Agent tracing, LangSmith evals, and sub-agent orchestration
- Integration marketplaces and DeepWiki-style interfaces
- Agentic applications and vertical SaaS automation
- Market taxonomies, NAICS clustering, and Anthropic’s Economic Index
Key Takeaways
Takeaway 1
Apple’s AR platform sets a precedent for how creative tooling may evolve in spatial interfaces powered by eye tracking.
Takeaway 2
OpenAI’s shift to connector-based workflows signals a deeper push into enterprise infrastructure, raising both opportunities and vendor lock concerns.
Takeaway 3
Memory and voice assistants are converging to create persistent, personalized AI experiences that blend context and tool usage.
Takeaway 4
Agent observability and orchestration are now critical—LangSmith, sub-agent graphs, and tracing enable robust debugging and performance tuning.
Takeaway 5
Economic clustering and NAICS-based taxonomies can help identify where agentic automation will have the greatest enterprise impact.
Featured Guests
No guests in this episode.
