Every story, one dial. Find the signal on Spectrum.
I asked my research library a question this week and had the answer in about three seconds. Links, dates, and the exact wording from sources I’d already read, listened to, or watched. Getting the same thing out of a deep research run in ChatGPT takes me around twenty minutes.
I was thinking about shared team memory: why a team needs one memory that people and AI both work from. I wanted to see whether the library could back it up better than Claude alone. On ideas, it tied. Claude and I would have reached most of the same ones anyway.
It outperformed us on evidence. It found what one of the big AI labs had written about context being the real bottleneck, with the link, the date, and the exact wording. It found a piece published five days earlier that gave me my best new point and the strongest case against me. Where Claude would say “someone has written about this,” the library handed me the page.
I’ve always been a bit of a pack rat. I used to keep a bin of old cables in case I needed them.
I had to break that habit. Most of them were obsolete, and you can get a cable delivered to your house the next day.
Information doesn’t take up space, but it still causes clutter. It’s a lot to process at once. So I built a library on my Mac Mini and let a machine sort the pile. I call it ParaCorpus. It doesn’t decide what’s worth saving. Jev, the judge from my last story, ranks everything that arrives. It never deletes a thing.
I don’t file anything anymore. A bot I named Garfield can see my history: what I watch, what I read, what I like. A click is enough to flag something. That one habit accounts for more than half of the library. The Mini also goes out on its own, checking a couple dozen channels and blogs on a schedule and following the references in what it reads. Claude, ChatGPT, and Grok can all search it and add to it. Whatever my tools find, the library keeps.
When I built it in September, I pointed it backward. Everything I’d watched or read since January came in, about 6,000 things, and in one week the library grew by more than 7,000 items. Today it holds almost 10,000, broken into about 90,000 passages and indexed by meaning. I can ask a plain question and get back the parts that matter.
This level of hoarding only works if the library is honest about what it doesn’t have. Early on, it fell short. Ask it something it couldn’t answer, and it handed back its least-bad guesses: a video about Carl Jung, a story about a chip company’s stock.
The fix seemed obvious: throw out anything that looked like a weak match. We tested it, and it tossed good answers along with the junk. There was no clean line between the two.
Instead, we kept everything. When nothing in the library fits the question, it says so: no good match. It still shows me what it found, marked as weak, and I decide.
I’m not claiming perfection. A bad match can still look like a good one, so I read what it hands me. The first question after a quiet stretch is slower, about thirteen seconds. And it only knows what’s caught my attention.
A personal library isn’t new. What changed is the cost of using one. Jev makes sorting it cheap enough to do on everything, and tools like Claude can pull from it in seconds, at a scale no person could match.
And it compounds. Every question I ask, every source a chat cites, every video I click on makes it bigger. The bigger it grows, the better the evidence behind my tools. Back in Drinking from the Garden Hose, I wrote about potable information. This is my reservoir.
Save the whole haystack. Find the needles later.
Uncomplicated systems. Uncommon results.
Find the next story.
Spectrum is the dial for the rest. Type a word, a name, or a feeling, and it finds the stories that match, plus the source material behind them.
Behind this story: what it builds on and the source material.