Tag: personal knowledge management

Categories
AI Blogs/Weblogs

How to Refresh Dated Blog Articles

Woman typing on laptop at wooden table in cafe with coffee and pastry
A woman working on her laptop at a sunny cafe table with coffee and pastry

This afternoon I used the following prompt to help me assess posts I’d written a few years ago for updating:

I have a personal blog at https://sjl.us
Please review my blog posts that are between two and five years old and give me a prioritized list of which ones you think I should update.

I was curious how well it would do at this task. Turns out I was pleasantly surprised. Here’s the result:

Here’s my prioritized list of your blog posts (published roughly April 2021–April 2024, i.e., 2–5 years old as of April 2026) that I recommend updating, ranked from highest to lowest priority.

I reviewed the site structure, monthly archives, and indexed posts via searches. Your blog has dozens of posts in this window (mostly personal essays, photography, history, productivity/PKM, and heavy AI experimentation from the 2022–early 2023 wave). I prioritized based on:

  • How much the topic has aged (AI/prompting/tech tools change fastest; photography, personal reflections, and history are more timeless).
  • Potential value of an update (adding 2026-era insights, new examples, current tool versions, or follow-up reflections makes the post fresher and more useful to readers).
  • Thematic clustering (your AI/PKM series from 2022–2023 forms a natural arc that would benefit from a cohesive refresh).

I focused on the highest-impact ones rather than every post. Many others (e.g., pure street photography, freeway essays, family stories like the Tracy obituary, or 2021 COVID-era reflections) are still strong as-is and don’t need updates unless you want to add new photos or minor notes.

Top Priority (Strongly recommend updating soon — these are the most dated but highest-potential)

  1. Multi-step prompting for Claude (August 11, 2023)
    https://sjl.us/2023/08/11/multi-step-prompting-for-claude/
    Why update? Early Claude-specific prompting techniques; the entire field (Claude 3/4 families, GPT-4o-class models, Grok, etc.) has advanced dramatically. Easy win: expand with 2026 best practices, new multi-step examples, and comparisons.
  2. My Current PKM Stack as of September 2023 (September 20, 2023)
    https://sjl.us/2023/09/20/my-current-pkm-stack/
    Why update? Details your Obsidian/Instapaper/Feedly/Drafts workflow at the time. Tools and plugins have evolved a lot; readers love current “state of my stack” posts. A 2026 version would be highly engaging.
  3. Using AI to Help Write (November 15, 2022)
    https://sjl.us/2022/11/15/using-ai-to-help-write/
    Why update? Pure GPT-3-era experimentation. Perfect opportunity to contrast 2022 capabilities with today’s multimodal models and show how your own AI-assisted writing process has matured.
  4. LLMs = Dream Machines (December 11, 2023)
    https://sjl.us/2023/12/11/llms-dream-machines/
    Why update? References to early hallucination discussions and Andrej Karpathy’s tweet feel historic now. Update with current “dream machine” examples and how you use LLMs in 2026.
  5. Crafting Effective Prompts for Your AI Assistant (Claude, ChatGPT, Bard, etc.) (September 9, 2023)
    https://sjl.us/2023/09/09/crafting-effective-prompts-for-your-ai-assistant-claude-chatgpt-bard-etc/
    Why update? Another core prompting/PKM-adjacent piece from the explosion period. Pair it with the multi-step post for a nice “2023 vs 2026 Prompting Guide” refresh.

High Priority (Worth updating — clear value-add)

  1. An AI Thanksgiving (November 22, 2022)
    https://sjl.us/2022/11/22/an-ai-thanksgiving/
    Why update? Fun GPT-3 + DALL·E experiment. Readers would love a 2026 “then and now” version with newer models/image generators.
  2. Hacking Creativity with AI (August 22, 2023)
    https://sjl.us/2023/08/22/hacking-creativity-with-ai/
    Why update? Early chatbot creativity techniques; the creative workflow space has exploded since then.
  3. On the Minimum Viable Environment (MVE) and Apple’s Vision Pro (July 1, 2023)
    https://sjl.us/2023/07/01/on-the-minimum-viable-environment-mve-and-apples-vision-pro/
    Why update? Pre-launch speculation. Vision Pro shipped in 2024 — you can now add real-world usage, ecosystem updates, and whether MVE thinking held up.
  4. Drafts – a tool for idea capture (April 16, 2022)
    https://sjl.us/2022/04/16/drafts-a-tool-for-idea-capture/
    Why update? The app was celebrating its 10th anniversary then; it’s now 14+ years old with major feature/UI changes. Your long-term usage makes this a great “then vs now” post.

Medium Priority (Nice-to-have updates if you have time)

  1. Reading Books in 2022 (May 11, 2022)
    https://sjl.us/2022/05/11/how-im-reading-books/
    Why consider? Kindle/app habits and highlighting workflows have evolved; easy to refresh with current tools and your 2026 reading volume.

Other notable 2023 AI-adjacent posts (e.g., NotebookLM deep-dive from Dec 2023, Explorations of PKM from Oct 2023) would slot in here if you want to do a broader “AI/PKM 2023 Retrospective” series.

Lower Priority / Probably Leave As-Is

  • Photography series (e.g., “Capturing the Art in Everyday Scenes,” Paris posts, “Redwood Circle,” etc.) → Timeless and visual; they hold up well.
  • History/personal essays (e.g., “Ode to a Queen,” “The World’s Most Beautiful Freeway,” “Remembering Blue Chip Stamps,” “Old Man Walking,” 2021 book recs, “Stuck in Neutral”) → Evergreen or emotionally resonant; updating could dilute their original voice unless you have new material.
  • Holiday/personal posts (e.g., Thanksgiving 2023, Merry Christmas 2021) → Fine as snapshots in time.

Quick recommendation on approach: Start with the top 5 (they form a nice cluster around AI prompting/PKM). Updating them together would create a strong “2023 AI Reflections – Revisited in 2026” section or category on the blog. Many of these posts already reference each other, so cross-linking updated versions would be powerful.

If you’d like me to pull full content from any specific post, draft sample update language, suggest new sections, or help with images/AI-assisted rewrites, just let me know! Your blog has a great reflective voice — these updates would keep it feeling current without losing that personal touch.

Categories
AI AI: Large Language Models Investing

The Ledger of Curiosity

We often romanticize the “back of the napkin” idea. It is the symbol of spontaneous genius—the startup mapped out in a coffee shop, the ticker symbol hurriedly scribbled during a dinner party. But we rarely talk about what happens to the napkin afterwards.

Usually, it gets thrown away. Or lost. Or stuffed into a drawer, becoming just another artifact of a fleeting thought that had momentum but no direction.

In the first two parts of this experiment, I used Gemini 3 Pro to solve the friction of entry (transcribing my messy handwriting) and the friction of analysis (stress-testing the ideas against 10-K realities). But there was one final gap: Permanence.

An analysis that lives and dies in a chat window is barely better than one that lives and dies in a notebook. It is still ephemeral. To truly build a “Second Brain” for investing, the data needs to leave the conversation and enter a system.

“The goal of technology should be to stop us from losing the work we’ve already done.”

I tweaked my workflow one last time. I asked the AI to not just judge the stocks, but to format its judgment into a raw CSV block.

With a simple copy-paste, my handwritten scribble wasn’t just digitized; it was database-ready. It went from a piece of paper to a row in Google Sheets with columns for “Market Cap,” “P/E Ratio,” and “Primary Risk.”

Suddenly, I wasn’t just looking at a list; I was building a ledger. I can now track these ideas over months. I can see if the “Red Flag” the AI identified actually played out. I can measure my own batting average.

The goal of technology shouldn’t just be to make us faster at doing work. It should be to stop us from losing the work we’ve already done. By turning ink into data, we stop treating our ideas as disposable. We give them the respect of memory.

Categories
AI AI: Large Language Models Investing

From Ink to Insight

There is a distinct friction that exists between the analog world and the digital one. For years, analog notebooks have been the graveyard of good intentions—lists of books to read, article ideas to write, and companies to investigate, all trapped in the amber of my barely legible handwriting.

I recently found myself looking at one of these lists: a scrawl of company names I had jotted down while reading an article discussing possible companies for investment in 2026. Usually, this is where the work begins—taking my handwritten notes, typing them out one by one, searching for tickers, opening tabs, etc. It is low-value administrative work that often kills any spark of curiosity before it can turn into useful analysis.

“The barrier to entry for deep research drops to the time it takes to snap a photo.”

On a whim, I snapped a photo and uploaded it to Gemini 3 Pro. “Transcribe this,” I asked. “Give me the tickers.”

I expected errors. My handwriting is, to put it mildly, not easy to read (even for me!).

Instead, the AI didn’t just perform Optical Character Recognition (OCR); it performed contextual recognition. It understood that the scribble resembling “Apl” in a list of businesses was likely Apple, and returned $AAPL. It deciphered the intent behind the ink.

But the real shift happened when I asked Gemini to pivot immediately into research. Within seconds, I went from a static piece of paper to a dynamic analysis of P/E ratios, recent news, and market sentiment. The friction was gone.

This experience wasn’t just about productivity; it was about the fluidity of thought. We are moving toward a reality where the interface between the physical world and digital intelligence is becoming permeable. When the barrier to entry for deep research drops to the time it takes to snap a photo, our curiosity is no longer limited by our patience for data entry. We are free to simply think.

Categories
Claude PKM Personal Knowledge Management

Amusement Park of My Mind

white and yellow roller coaster
Photo by Min An on Pexels.com

I recently wrote (“Astonishment“) about the metaphor of an amusement park for my PKM. This morning I was listening to a podcast on my morning walk in which the host was encouraging us to use AI to help extend our thinking in various ways.

When I got back from my morning walk, I asked Anthropic’s Claude to help me brainstorm some more on this amusement park idea. I really like some of these suggestions – which definitely to extend my thinking about the various nooks and crannies of my PKM system!

  • A funhouse with distorting mirrors that show exaggerated or distorted versions of my ideas and beliefs. Allows me to see things from new angles.
  • A merry-go-round where I can revisit my favorite ideas and insights over and over. A place of comfort and familiarity.
  • A haunted mansion filled with doubts, fears, and limiting beliefs that I need to face and overcome. Facing the ghosts helps me grow.
  • Food stalls and snack bars representing nourishing ideas and mental models. Brain food to feed my thinking.
  • An arcade or midway where I can play games with ideas, combining them in new ways to see what emerges. Allows combinatorial creativity.
  • A lazy river where I can relax and let my mind wander, making new connections. Effortless flow of insights.
  • A hall of mirrors where ideas build on each other, combining and recombining. Represents the compounding nature of knowledge.
  • A carousel with different animals representing different perspectives – a way to look at ideas from different viewpoints. Expanding my frames.
  • A safari ride to discover new lands of knowledge I haven’t explored yet. Pushing beyond my comfort zones.
  • A hedge maze representing the challenge of finding my way through complex ideas and systems. Navigating nuance and ambiguity.
  • A theater showing films of my memories and vivid imaginings. My dreams, fantasies, and reflections come alive.
  • A Ferris wheel giving a bird’s-eye view when I need perspective on things. Rising above for clarity.
  • Bumper cars allowing ideas to collide and bump into each other randomly. Sparking new insights through serendipity.
  • A petting zoo with metaphors and analogies I can interact with. Making the abstract more concrete.
  • A sky tram/gondola lift connecting different domains of knowledge. Seeing interconnectedness.
  • A fun slide for taking quick leaps between ideas. Intuition and rapid insights.
  • A carousel of cognitive biases I need to watch out for. Remaining aware of my blindspots.
  • A picnic area for intellectual nourishment and pausing to reflect. Healthy thinking habits.
  • A mirrored labyrinth of ever-deepening knowledge. Infinite recursion of ideas building on themselves.
Categories
Obsidian PKM Personal Knowledge Management

My Current PKM Stack

My PKM Stack as of September 2023

I’m enrolled in cohort 2 of Mike Schmitz’s Obsidian University. Mike is an excellent educator and he’s developed considerable expertise in Obsidian. His first two sessions are deep dives into setting up a personal knowledge management (PKM) system. The first session was about philosophy, the second about specific tools he uses/recommends.

I’ve been using Obsidian pretty heavily since I first started playing with it in May 2022. I’ve got lots of notes collected and have a workflow that’s been working for me in terms of capturing information I want to think about later. Here’s my basic workflow:

  1. I’m doing all of my browsing in Safari on Mac, iPhone or iPad. I have used Instapaper as my read-later service for years and articles I find while browsing that I might want to save I’ll capture in Instapaper. I like Instapaper’s “clean up” approach – taking all of the extra stuff out of web pages and distilling them down to the essence of the text on the page.
  2. A second source of capture is Feedly which I’m using as my RSS reader and in which I also capture articles to Instapaper.
  3. Sometime later I’ll open Instapaper and read through what I’ve captured. If I find an article I want to add to my Obsidian vault, I will email it to Drafts using its recently added mail drop feature. Once it’s in Drafts, I used an action to save the article to my Obsidian Inbox folder which is stored in iCloud.
  4. Later, I’ll open Obsidian and review my Inbox folder and open each item in turn, add metadata properties to the top (using an Obsidian template that I’ve created), and – once I’m finished editing it – I’ll move the note to my Zettlekasten folder in Obsidian which is where I store all of my notes.

That’s it.

I also use Drafts from time to time to just capture text that I either write or dictate – and process that later in the same fashion.

What I’m still trying to figure out how to do better is taking advantage of the notes I’ve captured – revisiting them, summarizing them, using them as the basis for a new note or a blog post, etc. In other words, creating some useful output from all of the input I’ve been adding. This is very much a work in progress!

By the way, sometime that’s important to learn before or while you’re learning Obsidian is the Markdown text format. It’s a simple, easy to learn way to “markup” text and it’s important to become fluent in using it with Obsidian.

Note: in addition to Mike Schmitz’s Obsidian University, I’ve also purchased David Sparks’ Obsidian Field Guide which is also a useful educational resource for learning the ropes of Obsidian.