Show Notes
If you already know your job well, AI raises a new question: which parts of your work could you do better, faster, or at a larger scale with an assistant that reads, writes, analyzes, searches, and sometimes acts? This episode maps what's available from OpenAI, Anthropic, and Google beyond basic chat, and how an experienced worker can put it to use.
The episode frames the toolset in layers: the model itself, the chat interface, Projects or knowledge files for ongoing context, reusable Skills, Connectors for approved tools and data, and agents that combine all of it into a multi-step loop. In ChatGPT, Projects keep related chats, files, and instructions together for work that spans more than one conversation, while connected apps and, for eligible users, scheduled tasks and workspace agents extend what it can search and do. Claude's progression runs through Claude.ai projects and connectors to Claude Code, which can inspect a repository, edit files, and run commands, supported by Anthropic's Model Context Protocol, MCP, for tool connectivity and Skills for reusable workflow knowledge. Google is adding Markdown-native skills to Gemini and Workspace, built on the open SKILL.md standard, with Gems transitioning toward that format over time.
The episode explains retrieval-augmented generation, or RAG, as a way to ground answers in a company's own documents by retrieving relevant passages before generating a response, while cautioning that poor retrieval or outdated documents can still produce a wrong answer that needs checking. It walks through a practical example for an operations manager, then covers company deployments: OpenAI's published stories on Asana, Sophos, Oracle, and Lowe's, and Anthropic's account of Barclays scaling Claude across operations and client service, all framed explicitly as company-reported examples rather than independent verification.
The episode closes with concrete guidance on agent permissions and prompt injection risk, and a method for comparing vendors using three of your own everyday tasks instead of benchmark charts. The throughline: start with one specific problem, add capability only as the task demands it, and let years of professional judgment guide and verify what the AI produces.
Sources & References OpenAI Help Center: ChatGPT release notes — https://help.openai.com/en/articles/6825453-chatgpt-release-notes OpenAI Help Center: Connected apps in ChatGPT — https://help.openai.com/en/articles/11487775-connected-apps-in-chatgpt OpenAI Help Center: ChatGPT Workspace Agents for Enterprise and Business — https://help.openai.com/en/articles/20001143/ OpenAI: Customer stories — https://openai.com/business/customer-stories/ Anthropic: Model Context Protocol (MCP) documentation — https://docs.anthropic.com/en/docs/mcp Anthropic: Fundamentals: The complete guide to building Skills for Claude — https://claude.com/resources/guides/the-complete-guide-to-building-skills-for-claude/fundamentals Anthropic: Barclays scales Claude to upgrade operations and improve client experience — https://www.anthropic.com/news Google Workspace Updates: Introducing skills in the Gemini app and Workspace, plus what's next for Gems — https://workspaceupdates.googleblog.com/2026/09/skills-gemini-app-workspace.html Google Workspace: Less switching, more flow: 5 new agentic capabilities across Google Workspace apps — https://workspace.google.com/blog/product-announcements/less-switching-more-flow-5-new-agentic-capabilities-across-google-workspace-apps Anthropic: Introducing Claude for Small Business — https://www.anthropic.com/news/claude-for-small-business Anthropic: Investigating unintended model actions in our evaluations and internal use — https://www.anthropic.com/news/investigating-unintended-model-actions
Voice narration is AI-generated.
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