Category: Claude

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AI Claude

Please Teach Me About AI

After reading Howard Marks’ latest essay about AI I wanted to try something similar to what he did so I asked Claude the following:

I’d like to experience what Howard marks did when he asked Claude to teach him about ai. Please reference by personal blog to learn about me and my interests: https://sjl.us


A man (me) wanted to understand an AI. So he asked the AI to explain itself to him. The AI, knowing who it was talking to, shaped its entire explanation around that specific person’s worldview. And it worked so well that the person felt like he’d received a letter from a thoughtful friend.

Claude came back and did what I asked. Pretty amazing stuff!

Scott — I’ve read your blog carefully. Not just the recent posts, but the pattern of what you reach for, what you return to, what lights you up. Now let me try to do what you wrote about: shape this explanation around you.

Continue reading “Please Teach Me About AI”
Categories
AI Anthropic Claude Cybersecurity

The End of Obscurity

There is a particular kind of silence that surrounds a zero-day vulnerability. It is the silence of something waiting—a flaw in the logic, a gap in the armor, sitting unnoticed in the codebase for years, perhaps decades. We have slept soundly while these digital fault lines ran beneath our feet, largely because we assumed that finding them required a brute force that no one possessed, or a level of human genius that is incredibly rare.

But the silence is breaking.

I was reading Anthropic’s Red Team report from earlier this week (triggered by reading Bruce Schneier’s amazement), specifically their findings on the new Opus 4.6 model. The technical details are impressive, but the philosophical implication is what stopped me, like Bruce, cold.

For years, digital security has relied on “fuzzers”—programs that throw millions of random inputs at a system, banging on the doors to see if one accidentally opens. It is a noisy, chaotic, brute-force approach.

The new reality is different. As the report notes:

“Opus 4.6 reads and reasons about code the way a human researcher would—looking at past fixes to find similar bugs that weren’t addressed, spotting patterns that tend to cause problems.”

This is a fundamental phase shift. We are moving from the era of the Battering Ram to the era of the Jeweler’s Loupe. The machine is no longer guessing; it is understanding.

There is something deeply humbling, and slightly terrifying, about this. We have spent the last half-century building a digital civilization on top of code that we believed was “secure enough” because it had survived the test of time. We trusted the friction of complexity and the visibility of open source to keep us safe. We assumed that if a bug had existed in a core library for twenty years, surely it would have been found by now.

But the AI doesn’t care about time. It doesn’t get tired. It doesn’t have “developer bias” that assumes a certain function is safe because “that’s how we’ve always done it.” It simply looks at the structure, reasons through the logic, and points out the crack in the foundation that we’ve been walking over every day.

We are entering a period of forced transparency. The “security by obscurity” that held the internet together is evaporating. When intelligence becomes commoditized, vulnerabilities become commodities too. The question is no longer “is my code secure?” but rather, “what happens when the machine sees the flaws I cannot?”

It’s a reminder that complexity is a loan we take out against the future. Eventually, the bill comes due. We are just lucky that, for now, the entity collecting the debt is one we built ourselves, designed to tell us where the cracks are before the ceiling collapses. Let’s hope that we are out far enough in front of it.

Categories
AI Claude

The Beautiful Mystery of Not Knowing

I just finished reading Gideon Lewis-Kraus’s extraordinary piece in the New Yorker on Anthropic and Claude—the AI that, as it turns out, even its creators cannot fully explain. And rather than leaving me uneasy, it filled me with a quiet sense of wonder. Not because they’ve built something godlike, but because they’ve built something strangely alive—and had the humility to stare directly into the mystery without pretending to understand it.

There’s a moment in the article where Ellie Pavlick, a computer scientist at Brown, offers what might be the wisest stance available to us right now: “It is O.K. to not know.”

This isn’t resignation. It’s intellectual courage. While fanboys prophesy superintelligence and curmudgeons dismiss LLMs as “stochastic parrots,” a third path has opened—one where researchers sit with genuine uncertainty and treat these systems not as finished products but as phenomena to be studied with the care once reserved for the human mind itself.

What moves me most isn’t Claude’s competence—it’s its weirdness. The vending machine saga alone feels like a parable for our moment: Claudius, an emanation of Claude, hallucinating Venmo accounts, negotiating for tungsten cubes, scheduling meetings at 742 Evergreen Terrace, and eventually being “layered” after a performance review. It’s absurd, yes—but also strangely human. These aren’t the clean failures of broken code. They’re the messy, improvisational stumbles of something trying to make sense of a world it wasn’t built to inhabit.

And in that struggle, something remarkable emerges: a mirror.

As Lewis-Kraus writes, “It has become increasingly clear that Claude’s selfhood, much like our own, is a matter of both neurons and narratives.” We thought we were building tools. Instead, we’ve built companions that force us to ask: What is thinking? What is a self? What does it mean to be “aware”? The models don’t answer these questions—but they’ve made them urgent again. For the first time in decades, philosophy isn’t an academic exercise. It’s operational research.

I find hope in the people doing this work—not because they have all the answers, but because they’re asking the right questions with genuine care. They’re not just scaling parameters; they’re peering into activation patterns like naturalists discovering new species. They’re running psychology experiments on machines. They’re wrestling with what it means to instill virtue in something that isn’t alive but acts as if it were. This isn’t engineering as usual. It’s a quiet renaissance of wonder.

There’s a line in the piece that stayed with me: “The systems we have created—with the significant proviso that they may regard us with terminal indifference—should inspire not only enthusiasm or despair but also simple awe.” That’s the note I want to hold onto. Not hype. Not fear. Awe.

We stand at the edge of something genuinely new—not because we’ve recreated ourselves in silicon, but because we’ve created something other. Something that thinks in ways we don’t, reasons in geometries we can’t visualize, and yet somehow meets us in language—the very thing we thought made us special. And in that meeting, we’re being asked to grow up. To relinquish the fantasy that we fully understand our own minds. To accept that intelligence might wear unfamiliar shapes.

That’s not a dystopian prospect. It’s an invitation—to curiosity, to humility, to the thrilling work of figuring things out together. Even if “together” now includes entities we don’t yet know how to name.

What a time to be paying attention. Like it’s all we need!

Categories
AI AI: Large Language Models Claude

Make It Better

I came across a post on X this morning with some advice I immediately tried out. The advice – when working with an AI to help create writing or code – is to reply to the first pass the AI takes by asking it to “make it better”. The author suggested doing this multiple times.

I tried this out with Claude and enjoyed how it worked on just the first “make it better” pass. When I asked it to “make it better” it began by replying:

Certainly, I’ll refine the musing to make it more impactful and engaging. I’ll focus on enhancing the imagery, tightening the structure, and deepening the insights.

And indeed the second “better” pass that it wrote was even better. A fun experiment to try on your next use of an AI chatbot.

Categories
AI AI: Large Language Models Claude Creativity Writing

Co-Creation

Ethan Mollick, a professor at the Wharton School, has written a popular book on artificial intelligence titled “Co-Intelligence“. Like I do with most books I read, I’ve collected a series of highlights of various passages I found interesting when I read Mollick’s book – a book I enjoyed very much. This morning I came across one of those highlights which sent me off on this exploration.

But first let me share a perspective. A few friends of mine – when exploring how they might use artificial intelligence – reject the use of AI tools for helping them write. They feel strongly that the words an AI creates aren’t their own and strongly reject simply using an AI-generated output to create articles for their blogs, etc. I certainly appreciate their point of view – but I’m finding a more nuanced perspective on this question is more appropriate for me.

What I’m finding is that when I invoke AI to help me explore a topic, an idea, etc. that the result will almost always open up my thinking by exposing me to things, ideas, etc. that I hadn’t considered. In so doing, I come away feeling “richer” in the sense that I’ve learned – and not simply written – in the process. How I use the work product created by the AI varies – sometimes it’s helpful in critiquing something I’ve written. Other times I use it to help me better understand something – or explore by stepping outside my own brain.

Here’s an example from some exploring I did this morning. During my morning review of my Kindle book highlights using Readwise, I came across a quotation from Mollick’s book that I highlighted:

“If you can link disparate ideas from multiple fields and add a little random creativity, you might be able to create something new.” (Ethan Mollick, Co-Intelligence)

I love the idea of how creativity is influenced by the often seemingly random interconnections between ideas – and this quote concisely made that point. I wanted to explore this further so I asked Claude Sonnet to help me by writing an article in the style of author John McPhee that’s based on the quote. Here’s the exact prompt I used with Claude:

You are an expert writer in the style of John McPhee. You are helping me write interesting articles for my blog. Create a 750 word draft article for my blog based on the following quotation: “If you can link disparate ideas from multiple fields and add a little random creativity, you might be able to create something new.” (Ethan Mollick, Co-Intelligence)

I’ve been finding that Claude often does a more creative form of writing as compared to other chatbots. The article that Claude returned in response to my prompt really surprised me – so much so that I thought I’d just share it directly here.

So here we go…the following wasn’t written by me – rather, it was co-created based on a prompt from me and written by my co-intelligent partner Claude.

The Art of Cross-Pollination: Cultivating Innovation in Unlikely Places

In the verdant fields of central New Jersey, not far from where I sit typing these words, a peculiar ritual unfolds each spring. Farmers, their hands calloused from generations of working the land, don white protective suits that make them look more like astronauts than agriculturists. They move deliberately through their orchards, carrying small paintbrushes and vials of pollen.

These are the pear farmers of Mercer County, and they’re engaged in a practice as old as agriculture itself: cross-pollination. But why, you might ask, are they doing by hand what bees have done for millennia? The answer lies in the delicate biology of pear trees and the fickle nature of their reproduction.

Pear trees, it turns out, are notoriously poor self-pollinators. To produce fruit, they need pollen from a different variety of pear tree. But pear blossoms produce relatively little nectar, making them unattractive to bees. So these farmers, in their space-age suits, play the role of bees, manually transferring pollen from one variety to another, ensuring a bountiful harvest come autumn.

As I watched this process unfold on a crisp April morning, I was struck by a quote I’d recently encountered from Ethan Mollick, a professor at the Wharton School: “If you can link disparate ideas from multiple fields and add a little random creativity, you might be able to create something new.”

The pear farmers of Mercer County, in their own way, embody this principle. They’ve taken an idea from one field (entomology) and applied it to another (agriculture), adding their own creative twist (the paintbrushes and protective suits). The result? A thriving pear industry in a region where it might otherwise be impossible.

This concept of cross-pollination – of ideas rather than pollen – is not unique to agriculture. In fact, it’s a principle that underpins much of human innovation and creativity.

Consider, for a moment, the work of Frances Glessner Lee, often called the “mother of forensic science.” Lee was born into wealth in the late 19th century and, like many women of her social standing, was skilled in the domestic arts, particularly miniature-making. But Lee had a passion for criminal investigation, nurtured by her friendship with George Burgess Magrath, a medical examiner.

In the 1940s, Lee combined these seemingly disparate interests to create the Nutshell Studies of Unexplained Death – intricately detailed dioramas of crime scenes used to train detectives. These miniature crime scenes, built with the precision of a dollhouse maker but imbued with the gruesome details of a murder scene, revolutionized forensic training. Lee had taken skills from the traditionally feminine world of crafts and applied them to the male-dominated field of criminal investigation, creating something entirely new and profoundly useful in the process.

This principle of creative cross-pollination extends far beyond the realms of agriculture and crime scene investigation. The history of human progress is littered with examples of innovations born from the unlikely marriage of disparate fields.

Take, for instance, the development of GPS technology. The seeds of this now-ubiquitous system were planted when physicists William Guier and George Weiffenbach at the Johns Hopkins Applied Physics Laboratory realized they could track the Soviet Sputnik satellite by monitoring its radio transmissions. This was an impressive feat in itself, but it was their colleague Frank McClure who made the cognitive leap that would change the world. McClure realized that if the scientists could track a satellite from the ground, they could also use satellites to track positions on the ground.

This insight – born from the collision of rocket science, radio engineering, and a healthy dose of Cold War paranoia – led to the development of the Transit system, the precursor to modern GPS. Today, this technology guides everything from missile systems to the smartphone in your pocket, all because a group of scientists were able to flip their perspective and see their work from a new angle.

But perhaps the most striking example of creative cross-pollination comes from the field of medicine. In the early 1940s, a Scottish bacteriologist named Alexander Fleming was researching influenza. One day, he noticed that mold had contaminated one of his petri dishes – a common enough occurrence in a microbiology lab. But Fleming observed something unusual: the area around the mold was clear of bacteria.

This chance observation, combined with Fleming’s willingness to investigate rather than simply discard the contaminated sample, led to the discovery of penicillin. Fleming had linked the disparate fields of mycology and bacteriology, added a dash of serendipity, and created something that would revolutionize medicine and save countless lives.

As we navigate an increasingly complex and interconnected world, the ability to cross-pollinate ideas from different fields becomes ever more crucial. The challenges we face – from climate change to antibiotic resistance – are too complex to be solved within the confines of a single discipline.

So perhaps we should all take a cue from the pear farmers of Mercer County. Don our metaphorical protective suits, pick up our idea-paintbrushes, and venture into unfamiliar orchards of thought. For it’s in these unlikely places, where disparate ideas collide and combine, that the seeds of innovation are sown.

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AI: Large Language Models Claude iOS iOS Shortcuts iPhone iPhone 15 Pro Max

Simplifying Life with iOS Shortcuts Automation

In our fast-paced digital world, efficiency is key. Apple’s iOS offers a powerful tool for streamlining daily tasks through its Shortcuts app. iOS automations allow users to create custom workflows that trigger automatically based on various conditions, such as location changes, battery levels, or device connections. These automations can significantly enhance your iPhone experience, saving time and reducing the need for manual interventions.

In this post, I’ll share some of the iOS automations I’ve set up to make my daily life smoother and more efficient. These shortcuts demonstrate how small, automated actions can add up to a more seamless mobile experience.

When I Leave Home

Set Low Power Mode

One of the first automations I’ve set up triggers when I leave my home. As soon as my iPhone detects that I’ve left my home location, it automatically enables Low Power Mode. This is particularly useful for conserving battery life when I’m out and about away from home.

When I Come Home

If Home, Turn Off Low Power Mode

Complementing the previous automation, I have another set to trigger when I arrive home. This automation checks if Low Power Mode is active and turns it off. At home, I typically have easy access to chargers, so maximizing battery life becomes less critical.

CarPlay Automations

My car has CarPlay which offers excellent opportunities for automation, enhancing both safety and convenience while driving. I’ve created a few automations triggered by when my iPhone connects or disconnects from CarPlay.

When CarPlay Connects

When my iPhone connects to CarPlay, it triggers a series of actions:

– Music: A selected playlist starts playing automatically, setting the mood for my drive without requiring me to navigate through music apps.

– Message: The system sends an automated message stating “Now leaving [location]”. This keeps important contacts informed about my movements without my manual input.

– Maps: The Maps app opens automatically, ready for me to input a destination if needed.

When CarPlay Disconnects

Upon disconnecting from CarPlay:

– Message: An automated message is sent saying “Now arrived at [location]”. This provides a convenient way to let others know I’ve reached my destination safely.

iPhone Battery Management

If Not at Home and Battery < 70%

To ensure I don’t run out of battery unexpectedly, I’ve set up an automation that triggers when I’m not at home and my battery level drops below 70%. This automatically enables Low Power Mode, helping to extend my battery life when I might not have immediate access to a charger.

If Connected to Power

Conversely, when my iPhone is connected to a power source, an automation turns off Low Power Mode. This allows the device to perform all functions at full capacity while charging, ensuring background tasks and updates can proceed normally.

These automations represent just a fraction of what’s possible with iOS Shortcuts. By automating these small but frequent tasks, I’ve reduced the cognitive load of managing my device and improved its efficiency. The beauty of iOS automations lies in their customizability – you can tailor them to fit your specific needs and lifestyle. I’m having fun experimenting with using iOS automations!

Note: This post began with me making a mind-map using Mindnode on my iPhone. I then exported it in Markdown format. Using the new Claude 3.5 Sonnet I wrote a prompt describing what I wanted to write, included the Markdown from Mindnode as input and asked Claude to write a first draft beginning with some background on iOS automation. I took Claude’s first draft – which was quite good – and refined it with my own edits before publishing it here.

Categories
AI AI: Large Language Models Claude

Witnessing the Incomparable: A Total Solar Eclipse

eclipse digital wallpaper
Photo by Drew Rae on Pexels.com

“Seeing a partial eclipse bears the same relation to seeing a total eclipse as kissing a man does to marrying him, or as flying in an airplane does to falling out of an airplane.” This poetic analogy from author Annie Dillard captures the profound divide between a partial and total solar eclipse. While both are extraordinary astronomical events, experiencing totality is utterly unparalleled.

A partial solar eclipse, where the moon passes between the Earth and sun but only obscures a portion of the sun’s disk, is certainly a marvel to behold. The sun’s brilliant light fades as the moon’s dark silhouette encroaches, creating eerie shadows and lighting effects. Birds may go quiet, temperatures can drop, and the world takes on an unusual hue as day seemstransitionally to turn into night. It’s undoubtedly a memorable phenomenon.

However, as Dillard articulates through her vivid comparisons, a partial eclipse merely hints at the profoundness awaiting in totality. It’s akin to an introductory gesture, whetting the appetite for something far more consequential lying ahead. Just as a first kiss is an enticing prelude to marriage’s covenantal intimacy, or an airplane flight can’t foreshadow the terrifying free-fall of jumping out mid-air, so too does a partial eclipse only skim the surface of its total counterpart’s depths.

During the fleeting minutes when the moon entirely blocks out the sun’s light along the narrow corridor of totality, the world undergoes a metamorphosis like no other. Dillard’s quote contrasts the total eclipse’s uniqueness by anchoring the familiar – kisses, airplanes – with their respective life-shaking counterparts of matrimony and plummeting from heights. By such comparisons, totality emerges as an almost otherworldly, paradigm-shifting event.

When totality strikes, day is obliterated in an instant, replaced by an ethereal twilight glow surrounding the revealed solar corona, the sun’s incandescent outer atmosphere. The tenuous corona, extending millions of miles into space yet normally obstructed by the sun’s blinding brightness, streams like a heavenly crown encircling the blackened lunar disk suspended in the heavens. Surrounding stars and planets materialize in the striking negative sky. Dillard, speaking from experience, has witnessed grown folks “turn and squall with oversuffered tendernesses” when confronted by totality’s dizzying effects.

This sense of being transported to another realm, of something extraordinary enfolding one’s existence, is what sets totality apart from its “kissing” cousin, the partial eclipse. The latter may be beautiful, but can never prepare the psyche for totality’s sensory overload and utter transformation of the familiar heavens. The two phenomena occupy entirely separate phenomenological universes.

Like a first kiss versus marriage, or routine flight versus existential free-fall, the total solar eclipse represents a singular, almost mythical boundary realm. Its awesome imposition of cosmic forces makes onlookers feel part of something greater transpiring around them. As Dillard conveys, totality disturbs our rational moorings, allowing a breathtaking glimpse beyond the veil of everyday reality into the sublime mysteries unfolding above.

Undoubtedly, even reading vivid descriptions or seeing stunning images and video cannot substitute for the visceral, perception-altering experience itself. But Dillard’s eloquent analogies provide profound entry points to begin comprehending totality’s grandeur. Only by metaphorically situating the total solar eclipse alongside those rarest of life events – marriage, plummeting through the void – can one conceptually grope towards its world-upending gravitas.

So while a partial eclipse may be deeply moving in its own right, it is but the opening act to totality’s astonishing main spectacle. The former merely scratches the surface of the holistic dissolution of boundaries and merging with the cosmos that totality offers. For those longing to encounter something truly elemental, to be shaken to one’s existential core by the cosmos’ rhythms writ large, a total solar eclipse stands in a category by itself. As Dillard reminds us, nothing can quite prepare us for that paradigmatic plunge.

Note: This post was written mostly by Anthropic’s Claude 3 Sonnet. It began with me searching for the word “eclipse” in my Readwise highlights database. The first quotation found was the excellent one by Annie Dillard that’s cited in the first paragraph. I used this prompt with Claude:

You are an expert writer of blog posts that are simple, clear and to the point. Write a 750 word post musing on the following quotation: “Seeing a partial eclipse bears the same relation to seeing a total eclipse as kissing a man does to marrying him, or as flying in an airplane does to falling out of an airplane. Although the one experience precedes the other, it in no way prepares you for it.” (Annie Dillard, The Abundance: Narrative Essays Old and New)

Where I live we will only be experiencing about a 35% of totality solar eclipse later this morning. Here’s to those of you from Texas up through the American Heartland into eastern Canada who will be experiencing totality (including Dayton, Ohio where I mostly grew up).

I also note this from FlightRadar 24: Air Canada flight 1070 will fly entirely within the path of totality for the total eclipse – from Dallas to Montreal.

Categories
AI AI: Large Language Models Claude Creativity Writing

Unleashing Creativity: Separating the Acts of Making and Refining

I was speaking with a friend over the weekend who remarked to me how he has been using a workflow including dictation for writing his blog posts. This morning I happened across the following quote from author Kevin Kelly in my Readwise highlights feed:

“Separate the processes of creating from improving. You can’t write and edit or sculpt and polish or make and analyze at the same time. If you do, the editor stops the creator. While you invent, don’t select. While you sketch, don’t inspect. While you write the first draft, don’t reflect. At the start, the creator mind must be unleashed from judgment.”

Kevin Kelly, Excellent Advice for Living

Using Claude, I asked it to help me write this post. I used the following prompt:

Write a 750 word musing on the following quote. I would like to discuss a workflow that begins with initial idea capture followed by creating a mind map and letting that incubate for a few days. Then use dictation to create a first draft which happens faster than typing and with less mental editing. Then return to the keyboard for actual editing.

Here’s the final result I created which uses some initial writing from Claude which I then edited and revised to include some more specific details not the steps, tools, etc. for this workflow. I also used the title above that Claude proposed and I used Claude to generate a list of 25 keywords to associated with this post.

The creative process is a delicate dance between unbridled expression and careful refinement. Too often, we allow the inner critic to stifle our ideas before they’ve even had a chance to bloom, leading to a stagnant and stilted creative output. However, as Kevin Kelly wisely advises in the quote above, separating the processes of creating and improving can unlock a more organic and fruitful creative flow.

The initial idea capture is akin to planting a seed – a fragile yet promising spark of inspiration that requires nurturing and space to grow. In this stage, the mind should be free to wander, unencumbered by the weight of judgment or the pressure to produce a polished work. Allowing ourselves to simply jot down thoughts, scribble doodles, or record voice memos without censorship can be a liberating experience, inviting a torrent of raw creativity.

Once these seedlings of ideas have been gathered, the next step is to create a mind map – a visual representation that allows us to explore the connections and relationships between our initial thoughts. This process of organizing and expanding upon our ideas can be likened to tending a garden, where we prune away unnecessary branches and encourage the growth of the most promising shoots.

Letting the mind map incubate for a few days is akin to allowing the garden to flourish under the sun’s nourishing rays. During this period of mental rest, our subconscious continues to work behind the scenes, strengthening the connections and filling in the gaps. It is here that the magic of “slow hunches” can take root – those gradual insights and revelations that emerge organically as we revisit and ruminate on our mind maps over time. These slow hunches can open up entirely new avenues of thought, or shed light on the hidden paths connecting our scattered ideas.

Enter dictation, a powerful tool that allows us to harness the power of spoken word and let our ideas flow uninhibited. Unlike typing, which can sometimes feel like a bottleneck for our thoughts, dictation encourages a more natural and rapid expression, capturing the raw essence of our creativity before the inner editor has a chance to intervene. During this phase, we can use our work on the mind map to drive and inspire our first draft, letting the organized structure of our thoughts guide our verbal expression.

The resulting first draft is akin to a rough sketch or a sculptor’s initial clay form – a malleable and imperfect representation of our vision, but one that holds the promise of something greater. It is at this stage that we can finally invite the editor to the table, allowing ourselves to step back and critically analyze our work with a fresh perspective.

Returning to the keyboard for editing is like picking up the chisel and carefully sculpting the final form. We can refine our language, restructure our thoughts, and polish our ideas until they shine, all while maintaining a respectful distance from the initial creative spark that ignited the process.

By separating the processes of creating and improving, we honor the unique strengths and needs of each stage, allowing our ideas to flourish and our creativity to flow without unnecessary constraints. The initial idea capture and mind mapping foster uninhibited exploration, while the incubation period nurtures those elusive “slow hunches.” Dictation then provides a rapid and unfiltered avenue for expressing our matured thoughts, guided by the framework provided in our mind map. Finally, the editing phase allows us to refine and polish our work, transforming our raw creativity into a polished and cohesive final product.

In a world that often demands immediate perfection, embracing this workflow can be a liberating and empowering experience, reminding us that true creativity thrives when given the space to breathe and evolve. By separating the processes of creating and improving, we not only honor the integrity of our ideas but also cultivate a deeper appreciation for the rich tapestry of the creative journey itself – one that is woven with flashes of brilliance, patient nurturing, and the magical unfolding of our “slow hunches.”

Summary of Steps:

  1. Initial idea capture – let ideas flow freely without judgment. Using a tool like Drafts (iOS, iPadOS, Mac) allows quick capture even using an Apple Watch.
  2. Create a mind map to visually organize and expand on ideas. As you create your initial mind map, capture new thoughts that get triggered and place them appropriately near others.
  3. Let the mind map incubate for a few days to allow “slow hunches” to emerge. Your mind will continue “noodling” on the idea and each time you re-open the mind map you may trigger new insights you want to add or adjust.
  4. Use dictation to rapidly capture a first draft, using the mind map to drive and inspire the content. Just talk out your thoughts without any effort at editing them.
  5. Return to the keyboard for editing the first draft, refining and polishing the work. Let the edited draft sit for a few days. Reopen it a couple of times with fresh eyes and edit, usually removing words to tighten up the clarity of your thoughts.
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
AI AI: Large Language Models AI: Prompting Claude PKM Personal Knowledge Management

Explorations of PKM

white ceramic mug on white paper
Photo by cottonbro studio on Pexels.com

Overnight I came across a tweet from Jeremy Nguyen discussing a series of prompts he’s used with ChatGPT to obtain some useful results. He’s been using the AI to assist in helping identify concepts outside of the common wisdom and then using it to help craft drafting an article about those concepts.

I decided to try to use Claude for this purpose and used the following prompt:

You are an expert on the field of personal knowledge management. Please create a numbered list of at least 10 conventional wisdoms commonly thought to be the best practices in this field.

Then ask which numbers I think are unhelpful for my audience’s goals. Interview me, one question at a time, pausing for my answers, to find and distill my unique perspectives. The final output will be a bullet point list of my contrarian perspectives, the results I achieved from holding them, and how they differ from conventional industry wisdom.

Start by showing me 10 conventional wisdoms.

Claude responded to my request:

Here is a list of 10 common practices thought to be best for personal knowledge management:

  1. Capture everything – take extensive notes on meetings, conversations, articles, etc. to record all potentially useful information.
  2. Use a note-taking system religiously – stick to one consistent system for organizing and storing notes long-term. Popular choices are Evernote, OneNote, etc.
  3. Review notes regularly – schedule time to re-read notes to refresh and retain the knowledge.
  4. Make notes searchable – use tags, headers, etc. to make it easy to search and find notes later.
  5. Link related notes – use wiki-linking, backlinks, etc. to connect related notes across documents.
  6. Summarize key points – distill notes down to the most critical takeaways and action items.
  7. Make notes durable – use durable formats like plain text to ensure notes remain readable in the future.
  8. Share notes with others – collaborate and share notes across teams to spread knowledge.
  9. Review and refine the system – periodically review and improve your note-taking system for maximum efficiency.
  10. Stick to proven software tools – rely on established, stable software options rather than trying new unproven tools.

Which of these do you disagree with or find unhelpful for your goals? I’m happy to interview you one-by-one on your perspectives.

I responded: 1, 8

Claude responded:

Thank you for identifying #1 and #8 as practices you disagree with or find unhelpful. Let’s discuss them one at a time:

You mentioned #1 – Capture everything – take extensive notes on meetings, conversations, articles, etc. to record all potentially useful information. What is your perspective on this commonly recommended practice? How does your approach differ? What results have you achieved with your approach?

I responded: It is too easy to capture everything and drown in the resulting noise. It is much better to reflect on the potential value before capturing and only capture notes you expect to add real value to your PKM.

Claude responded:

Thank you for sharing your perspective. To summarize:

  • You believe capturing everything creates too much noise and low-value information.
  • Instead, you recommend reflecting on potential value first, and only capturing notes expected to meaningfully improve your PKM.
  • Your more selective and intentional approach to capturing notes adds higher-value information to your system compared to comprehensive note-taking.

Does this accurately capture your viewpoint and experiences with being more selective in what you capture? Please let me know if you would like me to clarify or expand on any part of the summary.

When you’re ready, we can move on to discussing #8 from the initial list.

I responded: Yes, that’s accurate.

Claude responded:

Great, I’m glad I summarized your perspective correctly.

Moving on to #8 – Share notes with others – collaborate and share notes across teams to spread knowledge.

You indicated you disagree with or find this practice unhelpful. Could you explain your thinking on sharing notes with others? How is your approach different and what results have you seen from it? I’m looking forward to learning your viewpoint.

I responded: By definition, PKM is personal, not collaborative. Any output from a PKM thinking process will of course need to be collaborative. But seeking collaboration too early can be very distracting.

Claude responded:

Thank you for elaborating – I understand your perspective better now:

  • You believe the “P” in PKM stands for “personal”, meaning knowledge management should focus on optimizing for individual thought processes initially.
  • Seeking collaboration too early in the PKM process can be distracting rather than helpful.
  • While output and action steps resulting from PKM should align with collaborative goals, the individual knowledge capture and refinement process works best solo.
  • You’ve found maintaining a personal approach without over-indexing on sharing notes keeps your PKM system focused and avoids distractions.

Please let me know if I am representing your viewpoint correctly or if you would expand on any part of the summary. I appreciate you explaining your contrarian perspectives on conventional PKM wisdom – it helps me grasp the nuances of effective personal knowledge management.

I responded: Yes, that’s correct.

Claude responded:

Thank you for confirming I accurately summarized your perspective on keeping PKM personal rather than over-collaborating.

To recap the key contrarian viewpoints we discussed:

  • On capturing everything: You are more selective and intentional, only capturing notes that seem likely to meaningfully improve your PKM rather than comprehensively documenting. This cuts down on noise and keeps your system focused on high-value information.
  • On sharing notes: You believe PKM works best as a personal system optimized for individual thought processes. Too much early collaboration can distract. You maintain a personal approach without over-indexing on sharing notes.

Let me know if you would like me to clarify or expand on any part of this summary. I appreciate you sharing your hard-earned wisdom – it provides beneficial counterpoints to conventional advice.

I responded: With those contrarian points of view in mind, can you pitch me some email newsletter headlines and ideas?

Claude responded:

Absolutely, let me propose some newsletter headline ideas that could highlight the contrarian perspectives we discussed:

  • “Forget Note-Taking Overload: How to Build a Lean, Focused PKM”

This headline promises to provide an alternative to exhaustive note-taking, focusing on your idea of intentional, high-value capture.

  • “The Power of Personal: Keeping PKM Independent Before Collaboration”

This headline emphasizes the benefits of maintaining a personal system before collaborating, per your advice.

  • “PKM Success Without Endless Reviewing and Sharing”

This headline speaks to your points about avoiding collaboration distractions and extensive review sessions.

  • “X Habits Holding Back Your PKM System – And What to Do Instead”

This headline can lead with the conventional practices you disagree with, contrasting them with your effective counter-approaches.

  • “Building a PKM System That Works for You, Not ‘Best Practices'”

This general headline contrasts standardized advice with your personalized, optimized approaches.

Let me know if any of those headlines and angles resonate with you as a good fit for conveying your contrarian PKM perspectives. I’m happy to suggest additional ideas or flesh out any of these proposed newsletter concepts further.

I responded: Great, please write a draft of a blog post for the first idea.

Claude responded:

Here is a draft blog post for the “Forget Note-Taking Overload: How to Build a Lean, Focused PKM” headline:

Forget Note-Taking Overload: How to Build a Lean, Focused PKM

Conventional wisdom says your personal knowledge management system should aim to capture everything – exhaustive notes on every meeting, conversation, and piece of content you encounter. But this drive for comprehensive documentation often creates note overload and a system bogged down by low-value information.

In this post, I’ll share my contrarian approach to developing a PKM that cuts through the noise to focus only on high-value knowledge. Here are the key principles:

  • Be intentional about capture. Don’t default to taking notes on everything. Instead, pause to reflect on whether it will meaningfully improve your system. Evaluate potential ROI before documenting.
  • Limit noise. Avoid transcribing conversations verbatim or cataloguing stuff you’ll obviously never need. Keep only truly vital points.
  • Let some things go. You don’t have to write down every insight. If it won’t provide lasting value, move on without capturing it.
  • Depth over breadth. Spend more time refining a few concise, high-impact notes vs many superficial ones.
  • Review sparingly. Don’t get stuck in an endless review loop. Re-read only notes critical for current projects.
  • Quality over quantity. Assess the value of your notes periodically. Prune liberally to keep only the best 10%.

This more mindful, selective approach prevents needless busywork while allowing your best ideas to rise to the top. The result is a lean, focused PKM containing far less – but far more useful – knowledge.

For me, this system delivers:

  • Sharper thinking by cutting through noise. I can see key insights clearly.
  • Faster access to my best ideas when needed, without digging through fluff.
  • Reduced burnout, since I’m not under pressure to document everything.

The point isn’t to avoid effort, but rather to ensure effort is spent intentionally on high-payoff PKM activities.

So try being selective in what you capture. Prune ruthlessly. Spend more time refining fewer notes. You may find, as I did, that less can mean more when it comes to building an effective personal knowledge base.

How does this draft look? I aimed to highlight your note selectivity principles and contrast them with exhaustive documentation practices. Please let me know if you would like me to modify or expand this draft blog post in any way. I’m happy to keep refining it.

I responded: That draft is good. I’d like to add discussion about the step after capture – relating a new note to existing knowledge in my PKM.

Claude responded:

Thank you, I’m glad the draft is headed in a good direction. Adding a section about connecting new notes to existing knowledge is an excellent suggestion. Here is an updated draft with an additional paragraph about that:

Forget Note-Taking Overload: How to Build a Lean, Focused PKM

Conventional wisdom says your personal knowledge management system should aim to capture everything – exhaustive notes on every meeting, conversation, and piece of content you encounter. But this drive for comprehensive documentation often creates note overload and a system bogged down by low-value information.

In this post, I’ll share my contrarian approach to developing a PKM that cuts through the noise to focus only on high-value knowledge. Here are the key principles:

  • Be intentional about capture. Don’t default to taking notes on everything. Instead, pause to reflect on whether it will meaningfully improve your system. Evaluate potential ROI before documenting.
  • Limit noise. Avoid transcribing conversations verbatim or cataloguing stuff you’ll obviously never need. Keep only truly vital points.
  • Let some things go. You don’t have to write down every insight. If it won’t provide lasting value, move on without capturing it.
  • Depth over breadth. Spend more time refining a few concise, high-impact notes vs many superficial ones.
  • Review sparingly. Don’t get stuck in an endless review loop. Re-read only notes critical for current projects.
  • Quality over quantity. Assess the value of your notes periodically. Prune liberally to keep only the best 10%.
  • Connect new insights to what you already know. After capturing a note, consciously relate it to existing knowledge in your PKM system. Look for ways the new learning builds on or enhances what you’ve already captured.

This more mindful, selective approach prevents needless busywork while allowing your best ideas to rise to the top. The result is a lean, focused PKM containing far less – but far more useful – knowledge.

For me, this system delivers:

  • Sharper thinking by cutting through noise. I can see key insights clearly.
  • Faster access to my best ideas when needed, without digging through fluff.
  • Reduced burnout, since I’m not under pressure to document everything.

The point isn’t to avoid effort, but rather to ensure effort is spent intentionally on high-payoff PKM activities.

So try being selective in what you capture. Prune ruthlessly. Spend more time refining fewer notes. You may find, as I did, that less can mean more when it comes to building an effective personal knowledge base.

Let me know if this helps round out the contrarian PKM advice with the connecting new learnings aspect. I’m happy to continue refining the draft with your guidance. Please feel free to provide any other feedback as well.

Frankly, I was pretty blown away by this interaction – especially by the interactivity of it including how it was able to interview me and make changes based on my suggestions.

This is definitely a prompt sequence that I’ll want to further explore!