“I was complaining about this game two yahtzees ago.”
— Ash
“I was complaining about this game two yahtzees ago.”
— Ash
Lately I’ve been trying a new system for how I manage my evenings. Someone else might try “no system” or “having fun” or “relaxing,” but I am not that someone.
Instead, I’ve cobbled together something from the charred husk of the Bento Method that seems to work pretty well for me.
Of course, to make that make sense, I have to describe what came before.
In the early days there was StumbleUpon, and it wasted a lot of time, and I got nothing done for approximately 2008-2016. Very little of that is StumbleUpon’s fault. I just wanted to mention StumbleUpon for some OG time wasting cred.
By the early 2010s I was using the then-nascent Bullet Journal method. By the late 2010s I was using GTD.
Over the last half year I’ve been using time blocking, which has gone through several iterations. Originally rough time estimates became fixed time blocks, deep focus to light focus. The problem with that level of fixed schedule was that frequently the real world happened, and things slipped, and I had no good way to get them back on track.
Once the train missed the station it was hard to go back.
I was looking at the Bento Method and I thought, “well, this seems interesting.” Not really looking to buy a new app though. I’m actually quite happy with OmniFocus. But the idea of setting tasks that sort of roughly align with how I was time blocking, but that would remain to be re-scheduled if I missed them was pretty compelling. And seemed to solve for my main pain point with what I was doing previously.
The other problem I set out to solve, related but unrelated, was bringing more focus to a single project at a time. I tend to have too many hobbies and interests, and in turn tend not to get very many projects to a proper “finished” state.
So I married the bento method up with two week sprints. I actually like sprints. I know, crazy, right? But I like the idea of bringing a limited amount of laser-sharp focus to a problem. And, I was able to bake in a little bit of a reward. After my two weeks? A week off!
I’m now halfway through my second week of my first sprint under this system, and it’s been great. I’ve gotten a satisfying amount of work done on a single project. Naively I thought one sprint would be enough to finish it, but of course bringing my attention to bear meant I found all kinds of new things it could be extended to do.
C’est la vie. At least I have next week’s “break” to look forward to.
Is there a service that would let me input the details of a future trip (dates, location, cost,) and let my friends decide if they want to book concurrent trips, and then let me know their details so I can coordinate plans?
I’m not a traditionally “goal-motivated” person. For certain values of goal, motivated, and person. I have a formative memory of telling my third grade teacher that I would not be setting any new years resolutions because the idea is quite ridiculous, thank you.
I continue to agree with past-me about that.
“Goals” are sort of like a report card: some people are super motivated by getting good grades for some reason. If this is you, stop it. Grades are a scam. Do as little as you can to pass, and spend as much of your time as possible being curious about the world around you. Go outside. Lick a bug. Everything worth doing is as far from a classroom as you are allowed to get.
I digress.
Nothing about having a goal helps you achieve a goal. The goal doesn’t define the process that leads to the goal’s success. The goal doesn’t punish you for failure. The goal is Gary Busey standing over your bed breathing slightly too loud while you sleep. Unsettling, perhaps, but it’s not kicking your ass and telling you to achieve your destiny.
You’re defined by what you do, not by what you say you’ll do. Set a goal to have beautiful teeth in a decade and then stop brushing your teeth. Clearly the operative lever here, the essential fulcrum, is the tooth brushing habit.
Best case scenario, you’ve set out to do something you were already going to do, and you did it. Most likely case scenario you failed to achieve the goal, were a failure, should pour salt on yourself, shrivel up, and die.
Yes, I am a perfectionist, why do you ask?
I can’t speak to how anyone else conceives of goals. I suspect not like I do. Given the above, can you blame me for not finding them motivating? A “goal,” as described, is an opportunity to demonstrate my limitless capacity to fail at my own ambitions. Why would I even start down that path?
Except, apparently, I have always set what a normal, rational person would call goals. If you’ve known me long enough you’ve probably heard me say I want to be the CEO of the company. Quite possibly with an almost feverish level of intensity.
Listen, I know I’m not going to be the CEO. I mean maybe a CEO. Eventually. But not at my current day job.
This is what I call a Wildly Unachievable Goal. The point isn’t to ever do the thing. It’s to pick a direction, burn the boats, set out across the American Southwest, and see how close I get. Because every step of the way is valuable. I’ll learn, I’ll grow. I’ll end up closer to it than I ever might have imagined.
I think that for a WUG to work, you have to take it at face value. You have to believe in it with your heart and spleen. If at any point you acknowledge that it’s not really your intention, the magic breaks. It’s the productivity equivalent of a placebo.
Something new I’m trying out are Wildly Achievable Goals. WAGs. This is, I think, much closer to what a normal person would call a “goal.” It’s a thing I want to do, or have, or be, that through a reasonable series of steps, could happen.
A WAG might be “write a book.” It might be “launch an app on the App Store.” They’re things that normal human people do, but maybe you’ve never done.
The point of a WAG is that at the end of it, you have the thing you set out to do. No matter how audacious it is, you have reason to believe you could do it. No matter how long it takes, you think you could get it done.
A WUG is something you know you’ll never do, but you’re going to run full-chested at it anyway, because the point isn’t to get there, it’s to land among the stars.
WAG and WUG. Pass it on.
Another evening of memes with the wizards. Not saying any of them are particularly good, but we had fun. If intentional living sounds like your jam, take a peek.



What is a curse if not a dark gift?
Makin’ memes with the wizards.
The fundamental question: whether to prioritize security or fulfillment – to “run for office” or “build a rocket”.
Have you ever lost something and then spent the next ten years trying to find it?
I have. It’s an essay about the fall of the Roman Empire. Did the average citizen know the empire had fallen?
No. It took them about 200 years to figure out, but you’re just going to have to trust me because all the kings horses and all the king’s men haven’t been able to find that paper again.
Back in 2020 I got way into the idea of Personal Knowledge Management (PKM) and went about setting up my first “PKM Stack,” or set of tools for solving the problem: how do I stop losing all the interesting things I read.
The first version of this stack used Instapaper as my read-it-later, IFTTT, Dropbox, and Obsidian. The workflow sucked. But the basic idea was I’d read something, if it had any highlights those would get put in a markdown file in Dropbox by IFTTT, and then I’d manually drag it over to Obsidian eventually.
When AI first started taking off Instapaper used it as an opportunity to raise their rates, and not having been CRAZY happy with that solution, and not seeing any value in the then-state of AI, I used it as a chance to rethink, and ended up hopping to Readwise Reader.
When I migrated from Instapaper to Reader it was, by necessity, an imperfect migration. Instapaper’s output format included a link to the original document, the parts I had highlighted, but not the document text. Reader had to go out and fetch the document bodies again, and in a handful of cases failed. Either because Reader couldn’t parse it, or because the document was gone.
I also had the habit of archiving everything in the hope I would be able to find it later if I needed. This comes from deep trauma: I’m still looking for a paper I read a decade ago about whether the average imperial citizen knew the Roman Empire had fallen.
The result is a large backlog of low-value things that I had read, and saved in case, that I was unlikely to ever look at again. Or find any value in if I did.
Reader is fine for, well, reading, but it’s got usability gaps for making notes and long-term storage. Especially since my primary modality for using it is on an iPad mini on a flight somewhere. Most of my life runs out of Obsidian, why not this?
After thinking about it I decided that I want every document that I “archive” in Reader to go through an enrichment pipeline that summarizes it, extracts any highlights, extracts any key ideas or topics, and puts a markdown file in the right part of my Obsidian vault with all that information and a link back to the Reader copy, so that I can reference it if needed.
To make it maximally useful, I needed to do this for everything in the archive, and to do that I needed to get rid of all the low-value documents hanging around in there.
Going through the entire archive was going to require a system that could look at everything and reliably decide what I should or shouldn’t keep. To do that, I needed to be able to describe what I would want to keep. I needed an interest rubric.
Have you ever tried to describe yourself? Like really describe yourself? Maybe this is easier for other people but man I struggled. I came up with I think about four core interests, but I knew that wasn’t accurate.
My next attempt was to open a conversation with Claude, explain to it what I was trying to do, and ask it to interview me. This was... Medium successful? It ended up being a much better place to start from but was not in and of itself nearly comprehensive. Again it continued to rely on the things I could think of to prompt it with.
Finally I thought, okay. Well. I’ve got this backlog of things I’ve read. I know it’s got some stuff I want to get rid of, but it’s also filled with lots of stuff I’d want to keep. Can I use that as the basis for a rubric?
Bingo.
The next problem was purely technical. Over 700 documents, many running into the tens of thousands of words. There was going to be no way to put them all into Claude’s context at once. I thought about it and figured “good enough” might be “good enough” at scale: I had Claude write a series of Python scripts that would randomly sample about half of the documents and post them to an OpenAI batch job with the goal of summarizing and extracting key insights.
I’m not certain if this was the absolute final version of the prompt, but it looked a lot like this:
Your task is to analyze this document and create a comprehensive summary that would allow someone to understand its core value without reading the full text.Document Title: {doc[’title’]} Author: {doc.get(‘author’, ‘Unknown’)} URL: {doc.get(‘url’, ‘Not provided’)}
Content: {doc[’extracted_content’][:15000]} # Truncate very long content
Please provide:
A concise but information-dense summary (2-3 paragraphs) that captures the key ideas, arguments, and context of the document.
3-5 key insights or takeaways from the document that represent its most valuable content.
A brief assessment of why this content might be valuable to someone with interests in rationality, economics, science fiction, fantasy, and tabletop role-playing games. If the content seems unrelated to these areas, explain what type of person might find it valuable instead.
Format your response as structured JSON with the following keys: “summary”, “key_insights” (as an array), and “value_assessment”.
I think of “summarize a bunch of text” as something Large Language Models (LLMs, such as Claude or ChatGPT) are good at. Perfect use case.
My next step was to take the first Markdown file and the basis of my rubric from the interviews, and attach them to a conversation with Claude Sonnet 3.7 with Extended Thinking. I typed out like four paragraphs of stream-of-consciousness about what I was trying to do and asked it, in so many words: “based on all these summaries, what interests do you think I have that you don’t see on the rubric?”
Thus began a long dialogue. It would propose, based on what it saw, what it thought I liked. I would correct, confirm, cajole, and provide insight. Why yes, I am deeply interested in Philosophy. Actually no I’m not that interested in international finance, that one article happened to be really interesting.
Claude:
Governance and Legal Systems: Your reading suggests deep interest in specific governance mechanisms and legal frameworks beyond general institutional analysis. How central is this comparative approach to governance in your thinking?
Me:
I think I'm interested in how the world works, and how it could be made to work better. How do we build a better world, or at least minimize the chances of a worse world. I don't think I'm specifically interested in governance and legal systems outside of that context.
Claude:
There's a recurring pattern of interest in Philosophical Frameworks for analyzing complex issues. Would you consider this a hidden interest, or do you see it as simply an aspect of Rationality?
Me:
I am definitely interested in philosophy and philosophical frameworks. If I didn't need to "work for a living," I would strongly consider going back to school for a PhD in Philosophy. I think all of life's interesting questions are in the world of philosophy, and that it's a shame there's no way to make money doing it.
At the end, I’d ask it to spit out an updated version of the rubric, which I would take to a new conversation with Claude, the next markdown file, and repeat the process. After the second round I asked it to provide me with a prompt that captured everything I was trying to do, which I used for all subsequent iterations of the conversation.
The output of all these rounds was a several-kilobyte markdown file which accurately captures some, but not all, of my various interests. Not all my interests are captured in the things I read, and a random sampling was always bound to miss something. Nevertheless it’s good for what it got!
If you think it’d be interesting to see the final result (either to see what we built, or to get a better sense of who I am as a person,) I’ll attach a lightly edited version at the end.
Originally I was going to take my rubric and repurpose those scripts to have ChatGPT do the review, but I ran into a technical issue and had to pivot to Anthropic for this part. The ChatGPT batch API is convinced that I have batches in progress, even when I don’t and I can’t submit any more.
Anthropic ended up working out well because their API will let you set a “system” prompt that is distinct from the “user” prompt. The entire rubric and guidance on the return format went into the system prompt, and the user prompt ended up being the document data.
The first run, everything scored too high. Every document was a keeper, even ones I knew I didn’t want to keep.
I adjusted the rubric slightly, and it got a little better.
Finally, I added a point deduction metric for certain topics I knew I didn’t like, and that hit the sweet spot. The final run resulted in a markdown file reviewing everything in my Reader backlog that didn’t have highlights, and suggested around 83 deletions.
I manually reviewed all suggested deletions, and agreed with all but one of them, which revealed an obvious gap in the rubric. Success! The “keeps” were lightly spot-checked. I don’t need it to be absolutely right about them, because the worst case there is that a future step of this project costs me a little extra money by doing enrichment on a document that has nothing of value to give. I’m not that worried about it.
So what I did I learn? I learned a lot about how batch jobs to OpenAI and Anthropic work. I learned a medium amount about my own interests. I feel like if I had any need to do it I could write an extremely good dating profile now. “Enjoys long walks in the forest and applied epistemology.” I learned a bit more about how to wrangle the best results out of the current state of LLMs.
My next steps are to take everything I learned and built and begin working on the enrichment pipeline, which I think will look pretty similar in a lot of ways to start. Because I first need to deal with my archive, batch jobs are the most cost effective option. Eventually I’m imagining an AWS Step Function. All of which is better than Ghostreader. Most of which is better than nothing.
Did this help me find my Roman Empire? Well, no. As far as I can tell that’s well and truly gone. But I think it’s improving the process by which I never let the Empire fall again.
I used to have the entire Personal Interest Rubric here, because I thought it was somewhat interesting and people would want to see a sample of what I was talking about. Unfortunately, it made the entire post unreadable. Also, I'm no longer using the rubric. More on what I'm doing now to come.
Somewhere around five years ago I briefly entertained the idea that I was very seriously going to attempt to be an author. During that time I approached this the way I approach everything: with my whole entire ass.
Why half-ass anything when you can whole-ass one thing?
Which meant that, among other things, I read a lot of books on how to do writing good. Also, I tried to practice doing writing good.
The following are two bits of flash fiction that I wrote for practice.
Kazrin felt the thrum of his dirigible’s turbines through the wheel as he strained to guide his ship against strong chronomantic headwinds. Three days out from port, four more to the capital city, and nowhere to stop in between.
A symphony of lights erupted from the console in front of him. “Not again.” The thrum got weaker as the ship listed helplessly further to the port side. He slapped a heavy gloved hand against the wall while bellowing some of his juiciest curses. For a brief moment the turbine rumbled back to life, but quickly died taking the rest of the engines with it.
More choice words as the pilot flailed behind his seat looking for something, anything. He grasped at the jungle of cables full of various fluids and gasses. One of the tubes moved as he knew it shouldn’t. Kazrin grasped, wriggled, and finally slammed it back into place. The turbines roared back to life.
Only four more days to go. A warm meal. A warm bed. There’d be plenty of time once his work was done. For now, he was satisfied to be heading in the right direction.
Cold aethermantic resin dripped from the tunnel ceiling on to Alex’s head as he traced his finger over the brass pipe schematic. Ruined parts were strewn around him, not a single one had fit. “Lazy horking engineers never updating documentation,” he cursed out loud. “Kim valve” the useless flow-chart indicated, “model 703.”
Alex pressed his last 703 into the indicated ports, connections snapping into place with a satisfying click. Several pressure dials started to rise in an encouraging manner indicating positive resin flow. A great gout of fluid burst through the middle of the device, gauges falling back to their zero readings and covered him in even more of the viscous goo. Great, now he was out of Kim valves and he smelled like a cheeseburger went dancing on a hot summer day.
He pulled out the ruptured 703 and tossed it on the growing pile, then examined his parts bag critically. No more 703s, but a rusty Alice 417 and a Stanley 286. Out of better options to try he jammed the 417 into one side and the 286 in the other, then pressed the two parts together. They didn’t quite fit, but a few wraps of luminescent green fibertape and maybe? Almost? The pressure gauges ticked up and the tape held.
The sound of resin flowing was music to Alex’s ears. Fifteen years in the tunnels and it never stopped sounding sweet. He gathered up his tools and set off, there would be many more leaks to fix before the day was done.