ICOR with Tom | AI Productivity

This video explores why Claude and other AI models produce inconsistent results, examining how model selection (Haiku vs Sonnet vs Opus vs Claude 3.5 Fable), effort levels, prompt clarity, and system context dramatically affect output quality. The speaker demonstrates these differences through a Venn diagram creation task and advocates for using organized folder systems with documented SOPs and code-based solutions to ensure consistent AI performance.

Claude now has the ability to interact with multiple sessions, allowing a streamlined orchestration of tasks through an agent called Larry. This integration can simplify task management and enhance productivity by enabling a single main session to oversee various sub-sessions or tasks.

Tom explains why he disabled Claude's native memory feature and instead built a local folder-based system (myPKM) to maintain persistent context with AI agents. He shares an audit revealing systemic issues like contradictory documentation, forgotten rules, and parallel session conflicts, then outlines how to systematically fix these problems using the ICOR productivity methodology.

The speaker demonstrates how he uses AI (Claude) integrated with his local folder system to automate invoice collection for his accountant, downloading 36 invoices in 5 minutes with minimal manual intervention. He explains his AI team methodology, work streams, and how persistent local knowledge bases enable AI to handle recurring tasks independently without constant re-explanation.

A creator demonstrates a comprehensive local-folder-based system for managing AI-generated deliverables asynchronously, featuring an interactive browser interface that tracks decisions, changes, and conversations without relying on external databases or web applications. The system enables collaborative editing, visual annotations, and automatic context preservation across multiple parallel AI projects.

The speaker demonstrates how AI-powered weekly reports can automatically synthesize journal entries, notes, and captured content into personalized insights without manual review. Two different implementations are shown—one dashboard-style and one essay-style—proving the same underlying system can be customized to individual preferences and consumption habits.

The speaker has replaced traditional weekly reviews and manual note-linking with an AI-powered system built on a local folder structure called a 'scaffold.' This approach eliminates the time-consuming review ritual while enabling the AI to automatically connect notes and surface meaningful patterns that humans would miss.

The creator demonstrates real-world AI applications in their productivity business using Claude Fable and Opus, showing how Fable excels at comprehensive analysis of complex systems while comparing its performance to Opus on specific tasks. The key finding is that Fable's holistic understanding justifies its higher cost for business-critical audits and optimizations.

The hosts discuss the importance of double-checking AI outputs and validating information, emphasizing that this is not a new problem but rather a longstanding practice required with any information source. They explore how AI tools can be customized to individual workflows and contexts, arguing that understanding foundational methodology matters more than specific tools.

The speaker shares how an AI confidently generated a completely fabricated $67.4 billion statistic while researching AI hallucinations, then explains his systematic approach to combating AI misinformation: using dual independent search engines to cross-check answers and identify where hallucinations occur.

AI companies are racing to own users' context and memory through integrated tools like Claude in Slack and ChatGPT's auto-memory features, creating a lock-in trap. The speaker argues users should own their context (expensive, irreplaceable) in local plain text files while renting the AI model (cheap, replaceable), and demonstrates his personal knowledge assistant system built on markdown files that work with any AI model.

Tom, creator of the iCola methodology, releases My PKA version 3 with a free interface (My PKA Cockpit) that provides 12 pre-built AI agents for productivity, note-taking, health tracking, document management, and task planning—all running locally in a folder structure accessible via Claude and a web interface.

The creator explains why the removal of Claude Fable didn't disrupt his workflow, arguing that model-agnostic local folder setups with structured instructions make users resilient to AI changes. He uses an analogy of a dark room with a chair to explain how context and instructions guide AI behavior. The core message is that building robust local documentation and agent orchestration systems matters more than chasing the latest AI model.

The creator demonstrates a custom-built, locally-run personal knowledge management interface powered by Claude AI that replaces multiple productivity apps including note-taking tools, planners, and health trackers. The entire system lives in a single local markdown folder, requiring no subscriptions or cloud dependencies beyond a Claude plan. The interface will be made available for free to members of their myICOR community.

The video introduces the ICO framework, a Venn diagram-based map for visualizing your productivity tool stack across four quadrants: personal/business and information/action. The presenter demonstrates how to categorize tools as core applications, satellite apps, or utility apps, and how to identify redundancies and gaps in your system. The goal is to build tool-agnostic clarity about your productivity system rather than chasing new apps.

The creator demonstrates how an AI team generates interactive HTML review dashboards inside a local folder system, allowing him to review, approve, and copy social media campaign content without writing any code. The HTML file includes embedded videos, custom images, and copy-to-clipboard functionality for scheduled posts. This workflow is built entirely through natural language instructions to AI team members.

The presenter demonstrates a personal knowledge management system built entirely on a local folder structure using plain text files and Claude AI via terminal, replacing five human team members with AI agents. The system features a multi-agent team orchestrated by 'Larry' who delegates tasks to specialized agents like Pax (research), Charter (design), and Sage (writing). The approach emphasizes persistent memory, brand consistency, and tool-agnostic design over cloud-based AI chat interfaces.

The creator demonstrates a workflow for capturing handwritten notes and sketches using PDF Expert on iPad, syncing via iCloud, and having Claude AI read and act on the annotated PDF files. The system connects to a local 'myPKM' folder where an AI orchestrator named Larry processes inputs and outputs. The workflow eliminates the need for complex automations by relying on simple PDF files as the universal format.

Two AI productivity professionals discuss their local folder-based personal knowledge management system, explaining how it remains tool-agnostic across AI models like Claude, Codex, and Gemini. They address listener questions about agent orchestration, token efficiency, and the ICO framework's distinction between individual versus team-related knowledge. The conversation emphasizes that the underlying organizational principles remain constant regardless of which AI brain is pointed at the folder.

The creator showcases a fully custom-built learning and membership platform called MyICO, constructed entirely by an AI team using Claude and a local folder-based agent orchestration system. The platform features self-hosted video, semantic search, community management, coaching session libraries with timestamped chapters, and a tool-finder database. Three new courses are announced teaching users how to replicate this AI team structure for their own productivity or knowledge management needs.