Lifelong Learning Club

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Lifelong Learning Club
Why Dumping Everything Into ChatGPT Fails (And the Convergence Fix That Works)

Why Dumping Everything Into ChatGPT Fails (And the Convergence Fix That Works)

Cultivate a knowledge garden that yields clarity for grants, curricula, and beyond.

Eva Keiffenheim MSc's avatar
Eva Keiffenheim MSc
Aug 18, 2025
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Lifelong Learning Club
Lifelong Learning Club
Why Dumping Everything Into ChatGPT Fails (And the Convergence Fix That Works)
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Credits: Diana

It’s 2020, and I’m clicking through a digital sea of documents, searching for a single coherent thread to design a writing course.

My screen glows with hundreds of pages of research, syllabi from top-tier MFA programs, notes from my favorite books, and transcripts from dozens of interviews.

Yet, I'm paralyzed because I can't find a single coherent thought in my head. After hours of scrolling, I find only one thing: the crushing realization that I’ve built a labyrinth, and I am lost inside the very material meant to set me free.

What I went through is a central friction in knowledge work. We rarely fail for a lack of information; we fail for a lack of coherence.

A grant proposal's core narrative might feel disconnected from its supporting data. The central argument of a book manuscript is buried under a mountain of research notes. A PhD candidate stares at a folder of seminal papers, unable to spot the novel research question hidden at their intersection. A founder struggles to synthesize market analysis, internal reports, and user interviews into a clear strategic next step.

The insights are all there, but they remain a collection of disconnected tracks.

The temptation, especially since late 2022, is to drop everything into an AI chatbot and ask it to "find the key themes." But a tool designed for invention will stitch together a plausible summary that lacks an intellectual backbone. This is where most knowledge workers stumble: applying a tool for divergence to a task of convergence.

The most critical distinction you can make with AI is between these two modes.

  • Divergence is the wilderness. Tools like ChatGPT and Gemini explore the vast, untamed territory of the open internet (and the data they have been trained on). They are brilliant for brainstorming and creative exploration, but not the best choice when accuracy and fidelity to your sources are non-negotiable.

  • Convergence is the garden. The goal is to cultivate understanding within the closed system of your own curated sources. A convergence tool doesn't invent; it reveals connections inherent in the material you provide. If an answer can't be grown from the soil you've given it, it won't invent a plastic flower.

Using a wilderness tool for a garden task is a critical error. It leads to plausible-sounding hallucinations—helpful when you're brainstorming a sci-fi novel, terrifying when you're drafting a legal contract.

This playbook is for cultivating that garden. It’s a three-step process for turning project chaos into strategic clarity when accuracy is non-negotiable and your information is scattered. It’s a workflow built on a simple rule: use the right tool for the job.1


A 3-Step Playbook for Strategic Clarity

You are drowning in documents. Your job is to produce a single, defensible conclusion—a strategic plan, a new curriculum, a winning proposal. The common approach is to dump everything into an AI and ask for a summary. This is a recipe for nonsense.

You don't need a summary. You need a synthesis. This is the system for achieving it.

(The following steps link to Google Doc templates you can copy and use.)

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