AI Explored Podcast – Episode Summary
Episode: How Real-Time Data Unlocks 100X AI Performance
Host: Michael Stelzner (A)
Guest: Ryan Staley (B), AI Strategist and Founder of Whaleboss
Date: March 24, 2026

Overview

This episode of AI Explored dives deep into the transformative power of connecting real-time data to AI systems. Michael Stelzner and guest Ryan Staley unpack how marketers, entrepreneurs, and businesses can leverage real-time data integrations to radically improve efficiency, uncover new opportunities, and automate high-value workflows. Ryan shares hands-on examples, mindset shifts, tech details, and practical starting points, all aimed at making AI-driven real-time intelligence both accessible and actionable—regardless of technical background.

Key Discussion Points & Insights

Ryan Staley’s Origin Story in AI

• Ryan’s 23-year background in enterprise sales, building teams and consulting for companies like Amazon and Bed Bath & Beyond.
• Discovery of generative AI (DALL·E, then early ChatGPT) and immediate recognition of its revolutionary impact.
  • "Within three questions...I basically got 95% of the way there. Something that took me like 10 years to learn." (B, 03:05)
• Shifted his entire business to focus on AI implementation and strategy.

Breaking Down the Potential of Real-Time Data in AI

• Common Misconception:

  • Many believe AI integrations are only for technical or coding experts.
  • Modern tools (like OpenAI Codex, Claude Code) enable non-coders to leverage real-time data in AI, especially in marketing and sales. (B, 05:04)

• The Unlock of Real-Time Data:

  • Speed of Thought: AI acts instantly on up-to-date information.
  • Pattern Recognition: Identifies trends and opportunities humans might miss.
  • Substantial Time Savings: Automates hours of manual, repetitive work.
  • "It lets you operate at the speed of thought." (B, 07:25)
  • "It reveals patterns and opportunities that humans can't see most of the time unless they spend hours and hours…doing it." (B, 07:25)

Example: AI-Powered Social Content Creation (08:01)

• Ryan’s system: Connects HubSpot, Notion, Google Drive, and a note-taker.
• With a single prompt, AI analyzes transcripts, interactions, and content from the past week to generate sanitized, contextual, value-rich LinkedIn posts in minutes.

Example: Sales Ops Automation (10:09)

• Ryan built a sales operating system with AI agents that:
  • Generate and prioritize next-best actions for deals (no manual CRM grunt work).
  • Automatically update pipeline stages, stack-rank deals, and generate reports.
  • "It's almost as if you have a superpower." (A, 10:08)

Setting Up for Real-Time Data Integration

Mindset and Security Shifts (12:09)

• Use paid/professional AI accounts for data privacy and commercial protection—never free tiers.
• Double-check settings to prevent your data from training public AI models.
• Mindset: Recognize AI as "a worker that's available to me 24 hours a day and can work a hundred times faster than a human." (B, 12:48)
  • Challenge: Move from "classic" to "abundance" mindset; rethink your daily workflow as if you suddenly have a superhuman assistant.

How to Shift Your Thinking (13:40)

• Prompt the AI to help you reframe your own workflow:
  • "How can I work better with you [the AI agent]?"
  • Ask for side-by-side comparisons of ‘classic’ vs. ‘AI agent’ approaches.
• Self-discovery: Use AI to analyze your work patterns and point out blind spots or intuitive habits you didn't realize you had. (A, 14:32)

Operating Systems & Practical Examples

Ryan's AI Operating Systems Breakdown (15:53)

• CEO Operating System: Monitors alignment, beliefs, goals, daily/weekly tracking (incorporates frameworks like Tony Robbins and Marshall Goldsmith).
• Sales Operating System: Continuously improves deal flow and sales pipeline, identifies next actions.
• Product Operating System: Iterates and optimizes client deliverables.

The ‘Angel and Devil’ on Your Shoulder (17:53)

• AI surfaces both strengths and gaps by analyzing your unfiltered brain dumps, transcripts, and client data:
  • "It's almost like an angel and a devil on your shoulder that has access to more information than anybody else in your life… it synthesizes that, looks at patterns, and then helps you try and optimize it." (B, 19:39)

The Technology: Connectors, Models & Agents

Connecting Data Sources (20:00)

• Use ‘connectors’ or ‘apps’ inside AI platforms (Claude, ChatGPT, Gemini, Copilot) to link data sources like Google Drive, Notion, CRM systems—often via simple menus in settings.

  • Paid licenses sometimes enable deeper and automated connections.

• Are Connectors Truly Real-Time? (22:58)

  • Yes, data is typically pulled instantly, but you must toggle connectors on and specify which data source/folder to use.
  • Claude can often query across multiple sources simultaneously; others require explicit focus.

• Prompting Tips:

  • Tag/toggle connectors in chats or threads (e.g., “Look in HubSpot”), or select files with a ‘+’ or ‘/’ command in your AI tool.

Importance of Model Choice (25:00)

• Always use the most advanced available model for complex analysis (e.g., Claude Opus 4.6, ChatGPT 5.2).
  • Use slower, deeper-thinking models for large, important tasks; default models are fine for general use.

Advanced Applications: Claude Code, Skills & Workflows

What is Claude Code? (26:10)

• Originally designed as a coding agent but excels at orchestrating complex, multi-step, cross-system workflows.
• Think of it as building a custom “app” or “agent” that autonomously runs background tasks, sometimes for hours, across different data sources.
  • Example: One agent researches trending topics, another matches to personal content, third creates new posts automatically. (B, 27:32)

Agents, Skills, and the Future of Work (29:14)

• Skills: Predefined instructions/workflows agents use to perform jobs seamlessly every time.
• Emerging standard across platforms (Anthropic/Claude originated, OpenAI adopting).
  • “Today's jobs are going to be tomorrow's tasks.” (B, 29:14)

Practical Skill Sharing (30:24)

• "It's just a little zip file… I shared that skill with someone else on my team who uploaded and activated that skill. It's kind of like the Matrix." (A, 30:24)
• Skills can be downloaded, shared, and plugged in—enabling rapid upskilling and scaling across teams.

Claude Code Interface (31:44)

• Looks like a text-based coding terminal—may feel intimidating, but integration with tools like Obsidian or Notion adds a friendlier, structured display for results.

Local vs. Cloud Connections (33:47)

• Desktop Claude code can connect directly to local/cloud files (e.g., OneDrive); web version requires a free GitHub account as a storage backend.

App Overviews: Cowork, Cursor, and More

Levels of AI Workflow Tools (36:48)

• Chatbots with Connectors: ChatGPT, Claude, Copilot—add connectors for instant file/CRM access.
• Desktop Orchestrators: Claude Cowork—simple interface, supports multi-file, plugin workflows.
• Coding Agents: Claude Code, Codex—handle advanced, long-running, multi-agent tasks.
• Aggregators: Cursor—lets you select between different coding models for specialized tasks.

Why Bother With Coding Agents? (38:34)

• Enable concurrent, autonomous workflows across multiple sources.
• Handle long-running, complex jobs that a single chat cannot.

Costs, Scaling & Automation

• Paid accounts necessary for commercial data privacy and high-usage scenarios.
• (Cloud code, Cursor: $20–$100/mo typical range; scale as needed.)
• Automation/scheduling: Still some manual steps—more progress needed for fully automated, scheduled output via triggers.
  • Possible to use external schedulers or OS tools for advanced automations. (B, 39:56)

Getting Started: Practical First Steps

• Entry-Level Experiment:

  • Connect your CRM or document storage (OneDrive, Google Drive).
  • Prompt example:
    • “Look across my data and tell me trends and patterns I should be paying attention to that I’m not.”
    • “Identify five unique opportunities I don’t see right now that are game-changing.” (B, 40:57)

• Next Level:

  • Try out Claude Cowork—connect to folders, experiment with built-in plugins.
  • Explore shared and downloadable skills for automating complex tasks.

  "Once you start using them… it's going to unlock a lot of benefits, especially if there is any kind of database… inside your business. This could be a really big unlock."
  — Michael Stelzner (42:38)

Notable Quotes & Memorable Moments

• On the transformative potential of AI:

  "You gotta kind of reevaluate how you work on a day to day basis… if you have that kind of power."
  — Ryan Staley (12:48)

• On real-time workflow shift:

  "It's almost as if you have a superpower."
  — Michael Stelzner (10:08)

• On the future of skills and jobs:

  "Today's jobs are going to be tomorrow's tasks."
  — Ryan Staley (29:14)

• On skill sharing:

  "It's kind of like the Matrix."
  — Michael Stelzner (30:24)

• On first steps:

  "Ask it… what are trends and patterns I should be paying attention to that I'm not… you'll get two or three just bangers that are awesome. I can't believe I didn't think of that."
  — Ryan Staley (41:13)

Timestamps for Key Segments

• [02:10] — Ryan's entry into AI & career background
• [05:04] — Common misconceptions about AI/data
• [07:25] — The “unlock” of real-time data: speed, patterns, time
• [08:01] — Social content creation example
• [10:09] — Sales operating system, automation
• [12:09] — Security, privacy, and mindset setup
• [13:40] — Mindset shift: Prompting AI for workflow improvements
• [15:53] — Operating system examples: sales, CEO, product
• [20:00–22:58] — How to connect data sources (connectors/apps) and is it really “real-time”?
• [25:00] — Model selection best practices
• [26:10–29:14] — Claude Code, agents, skills, workflow orchestration
• [31:44] — Navigating the Claude Code interface
• [36:48] — Summary: Tools & use-case progression
• [38:34] — Why advanced agents/coding tools matter
• [39:56] — Automation: What’s possible?
• [40:52] — Practical first step(s) for experimentation

How to Connect with Ryan Staley

• LinkedIn, YouTube, and X (Twitter)
• Suggests: “Just reach out, say you heard me on the show so I know who you are.”

Final Takeaways

• For Marketers & Entrepreneurs: Real-time AI integrations are now accessible and can yield radical improvements in efficiency and insight—no need for a developer background.
• Mindset is Key: Treat AI as a partner/agent, automate mundane work, focus time on high-value opportunities.
• Start Simple: Begin with connector integrations; explore advanced workflows as comfort grows.
• The Competitive Gap is Widening: Early adopters of real-time AI unlock advanced capabilities and ROI.

For actionable notes, workflows, and tutorials: Visit the episode’s show notes