Create AI summaries to save time

- You know what's a big source of time waste? Having to go through documents with low signal to noise ratio. What does that mean? Think about the last time you had to go through a 30 page report to find just three key insights, or that 50 email thread where the critical decision was buried somewhere in the middle. That's low signal-to-noise ratio. Too much filler, not enough substance. And it's not just inefficient, it's exhausting. But here's, once again, where AI can become transformative. Let me show you a concrete example. Here's a 12 page market research report I received last week. In the past, I would skim it, highlight key sections, probably miss important details, and spend 20 to 30 minutes in the process. Instead, today I will just upload it to a model like Claude or Notebook LM and prompt, summarize this market research report, focusing specifically on one, major market trends. Two, our competitive position. Three, recommended actions. For each recommendation include the supporting evidence from the report. Within seconds, I get a structured summary with exactly what I need to know, but there's a crucial step most people miss, verification. Always ask the AI to cite where in the document it found the key information. For instance, for the claim about decreasing customer retention, please quote the specific section and page number that supports this. Now, this is the only time we're going to get a little technical, not even really. The two things you want to know about is one, your AI model's context window, and two, its accuracy. Context window is how much text the AI can process at once. Think of it as how big of a document it can see. Some models can process hundreds of thousands of words at once. Others can only do maybe about 4,000. The other factor is accuracy. It's simply the extent to which it's good at finding a needle in a haystack. Now, by the time you watch this video, AI models will have changed significantly. Making it very hard to tell you which model is good for what. But you can look it up. What won't change is your approach. Here's my process that you can apply to any document type. Identify what you actually need from the document. Upload to an AI with a sufficient context window. Ask for a targeted summary with specific categories. Request evidence for key claims, and finally use the summary to decide if deeper reading is warranted. Now here's your challenge. Take the longest document in your to-read pile, run it through an AI summarizer using the process I just shared, and see how much time you save. I bet it's at least 70%. Remember, your brain is for thinking, not for storage. Let the AI handle the storage part.