🏴‍☠️ Stop Deleting Your Best Ideas

Why Your Threads Vanish Afterward

Author

Captain YAR
December 02, 2025 • Estimated Reading Time: 7 minutes

You are almost certainly deleting ninety percent of the value from your AI sessions.

We tend to treat our chat windows like disposable coffee cups. You have a problem, you wrestle with the AI for twenty minutes, you get the answer, and then you close the tab.

I recently came across a fascinating perspective from this innovator that completely flips this habit on its head. The author argues that the context window is actually a “vector database of your own thinking,” and closing it without a second look is a huge waste of data.

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Context Mining

The core concept here is that an LLM does more than just predict the next word. As you interact with it, the model calculates complex relationships between your earliest ideas and your latest constraints.

The expert points out that the AI sees connections between “Idea A” and “Constraint B” that it never explicitly states in the final output. If you just copy the final result and leave, you lose that underlying logic. The “Context Mining” workflow solves this by adding a crucial step at the end of a session: an audit.

The Logic Map

The original poster explains that the AI is constantly building a probability map of your conversation. It knows why you rejected certain ideas and how different parts of your project fit together. This “meta-data” often contains better insights than the actual text the AI generated. By mining this map, you can uncover the reasoning behind the answers, which helps you understand your own project better.

The Analyst Shift

Most of us use AI as a generator. We want it to write code, draft emails, or brainstorm titles. The creator suggests that before you close a tab, you must command the AI to switch roles. You need to tell it to stop creating and start analyzing. This simple shift turns the AI into a consultant that reviews the work you just did together, offering a high-level view of the session.

Finding Abandoned Threads

One of the smartest parts of this workflow is looking for “abandoned threads.” In a long conversation, you often pivot away from good ideas because of a specific constraint. The expert recommends asking the AI to identify these lost paths. You might find that an idea you discarded twenty minutes ago is actually the perfect solution for a different part of your problem.

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Prompt of the Day

Here is the exact command the author uses to run this audit. Paste this into your chat before you close the window:

“Analyze the meta-data of this conversation. Find the abandoned threads. Find the unstated connections between my inputs.”

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