Like so many others, I’ve spent the past year exploring and experimenting with emerging AI tools.
Throughout that time, there has been one question I’ve been trying to answer: Will AI replace the need for Second Brains entirely?
A lot of people seem to think so, and I admittedly have a self-interested motivation: to decide whether I should continue advising people to build a Second Brain at all, or just tell them to rely on AI and save all that effort.
After many dozens of hours of experimentation, my conclusion is that AI is not going to replace the need for a Second Brain anytime soon.
Here’s why: no matter how powerful AI becomes, the data we put into it has to come from somewhere, and the AI’s outputs have to go somewhere. A Second Brain (or whatever you want to call it) is still needed both as the repository of all those inputs and as a staging area for storing those outputs until they’re ready to be used.
What’s Changed – Organize and Distill
There is no doubt that AI is going to radically change what we think of today as the creative process.
Looking at my CODE framework representing the creative process, however, it is mostly the middle stages of Organizing and Distilling that AI is transforming.
Organizing (step #2) is the stage of the creative process that inherently adds the least value – it is only needed to prepare the ground for the subsequent stages. Thus it’s no surprise that it’s the first one to be automated by AI.
No longer does it make sense to meticulously format your data in a perfectly organized database – instead you can just dump a morass of text into a prompt window, and AI is smart enough to understand what you intended.
As an example, Notion has added AI to its software, allowing you to interact with and “talk to” your notes without having to spend a lot of time adding structure.
Distillation (step #3) is also a perfect fit for the rapid, emotionless decision-making of AI. Large Language Models excel at rapidly summarizing huge amounts of text at whatever level of detail you desire.
For example, in my video on using ChatGPT to summarize books, I showed how AI was able to save me dozens of hours of formerly manual work to end up with a concise, actionable book summary.
What Hasn’t Changed – Capture and Express
The first stage of the creative process – capturing information in the first place – has still hardly been touched on the other hand.
New apps like Rewind allow you to record everything that happens on your computer, but in my experience that just creates a lot of recordings to wade through.
Although some capture tasks like digitizing handwritten text have been automated, we still have to write down our thoughts and ideas in the first place!
The quality of an AI chatbot’s response is always dependent on the quality of the inputs you provide it. AI cannot (yet) go out into the world and collect its own data, so we have to do that ourselves by capturing notes, highlighting passages in books, taking pictures, and saving our favorite ideas.
The fourth and final stage of creativity, expression, also still requires a human to decide what to do with the outputs of ChatGPT and other AI tools. Someone has to put the finishing touches on the final product via their own voice, style, taste, or perspective.
My wife Lauren’s video about creating a children’s storybook using AI perfectly illustrates this point: although every major component of the final product was created by ChatGPT, it was Lauren’s direction, synthesis, and creative nudges that allowed all the parts to come together in a cohesive, meaningful whole.
AI Concentrates Human Creativity at the Initial and Final Stages
AI doesn’t make human creativity unnecessary – it concentrates our creativity at the beginning and end of the creative process.
For a concrete example, in my video on Google’s new AI platform NotebookLM, I demonstrate how I can import the entire history of my reading highlights, and then freely make associations and connections out of that vast collection of text totaling 594,379 words from 719 sources.
While that capability seems almost superhuman, notice what it still required of me: to do the reading in the first place and save the excerpts I found valuable (capturing), and then to take NotebookLM’s responses and turn them into my own creation (expressing). In other words, the first and last steps of creativity haven’t been touched.
I can effectively skip from the first step to the last step, barely touching the steps in between. But that means I still need to take the first and last steps, to give the AI a starting point and an endpoint.
The relevant question has become: what do we do now that the “cost” of intermediate steps like organizing and distilling has plummeted?
Tasks that formerly required expensive human effort can now be completed with cheap computer effort, in fractions of the time. What kinds of goals, outcomes, and creative projects have suddenly become far more feasible than they were just a couple years ago?
For an example of what it might look like to work with AI as a real-time creative partner in this way, check out my in-depth interview (Part 1 and Part 2) with Srini Rao on the AI-powered noteaking app Mem (which by the way is the only notetaking app that OpenAI has invested in).
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