Tag: productivity

Categories
AI AI: Large Language Models

The Texture of Autonomy

There is a distinct texture to working with a truly capable person. It is a feeling of relief, specific and profound.

When you hand a project to a junior employee who “gets it,” the mental load doesn’t just decrease; it vanishes. You don’t have to map the territory for them. You don’t have to pre-visualize every stumble or correct every navigational error. You simply point to the destination, and they find their way.

I was thinking about this feeling—this specific brand of professional trust—when I read a recent observation from two partners at Sequoia regarding the current state of Artificial Intelligence:

“Generally intelligent people can work autonomously for hours at a time, making and fixing their mistakes and figuring out what to do next without being told. Generally intelligent agents can do the same thing. This is new.”

The phrase that sticks with me is “without being told.”

For the last forty years, our relationship with computers has been strictly transactional. The computer waits. We command. It executes. Even the most sophisticated algorithms have essentially been waiting for us to hit “Enter.” They are tools, no different in spirit than a very fast abacus or a hyper-efficient typewriter.

But we are crossing a threshold where the software stops waiting.

The definition of intelligence in a workspace isn’t just raw processing power; it is the ability to recover from failure without supervision. It is the capacity to run into a wall, realize you have hit a wall, back up, and look for a door—all while the manager is asleep or working on something else.

When Sequoia notes that “this is new,” they aren’t talking about a feature update. They are talking about a shift in the ontology of our tools. We are moving from an era of leverage (tools that make us faster) to an era of agency (tools that act on our behalf).

This changes the psychological contract between human and machine. If an agent can “figure out what to do next,” we are no longer operators; we are managers. And as anyone who has transitioned from individual contributor to management knows, that is a fundamentally different skill set. It requires clearer intent, better goal-setting, and the ability to trust a process you cannot entirely see.

We are about to find out what it feels like to have a digital colleague that doesn’t just listen, but actually thinks about the next step.

Categories
AI AI: Large Language Models

The Shipping Manifest

“Recursive self-improvement has graduated from a safety paper to a shipping manifest.”

For years, “recursive self-improvement”—the idea of AI building better versions of itself—was a concept relegated to academic safety papers and late-night philosophy forums. It was a theoretical horizon event, something to be modeled, debated, and perhaps feared.

But this morning, the tone shifted. As noted in a briefing this morning from @alexwg, recursive self-improvement has graduated from a safety paper to a shipping manifest.

The evidence is tangible. Anthropic confirmed that their new “Claude Code” wrote the entire Claude Cowork desktop app in a mere week and a half. This isn’t just code completion; it is code creation at a structural level. More importantly, this app grants the AI direct access to the file system. It is no longer trapped in a chat window, floating in the abstract void of the cloud. It has touched down. It can sort downloads, generate reports, and effectively reorganize “local reality.”

Simultaneously, the definition of “colleague” is dissolving. The CEO of McKinsey dropped a quiet bombshell, revealing that the firm now counts AI agents as “people” that the firm “employs.” The current census? 40,000 humans and 20,000 agents. The goal is parity within 18 months.

We are witnessing a fundamental agentic shift. When a consultancy firm—the bastion of human capital and billable hours—begins to view synthetic agents not as tools (CAPEX) but as employees (OPEX), the psychological contract of work changes. We are moving away from a world where we use software to a world where we manage it.

The org chart is no longer a biological tree; it is becoming a hybrid network. The recursive loop isn’t coming; it’s already clocked in.

Categories
AI AI: Prompting Writing

AI as a Mirror, Not a Maker

I’ve been thinking a lot lately about how we move past the novelty phase of AI—beyond just asking a chatbot to “write a poem about a turkey” or summarize a meeting—and into actual thinking with these tools.

As a lifelong learner, I’m always on the hunt for workflows that help me synthesize information better. Most of the “AI for writing” advice I see online is pretty generic. But I recently came across a breakdown of how four high-profile writers are making effective use of tools like NotebookLM and Claude in ways that are much more sophisticated than simple text generation.

What jumped out at me is that none of these writers use AI to write for them. They use it to structure, challenge, and code.

Here are the four models that caught my eye.

1. The Triangulated Research Base (Steven Johnson)

Steven Johnson (Where Good Ideas Come From) has a workflow that solves a problem I face constantly: the messy “research phase.”

Instead of treating the AI as an oracle, he treats it as a connection engine. He creates a dedicated notebook (using Google’s NotebookLM) and uploads three distinct types of sources: a primary source (like a raw PDF or study), a secondary source (like a context article), and a multimedia transcript.

Then, rather than asking for a summary, he asks the AI to find the friction between them: “What themes appear in the interview transcript that contradict the historical account in the PDF?”

It’s less about getting an answer and more about finding the blind spots in your own reading.

2. The Diagnostic Editor (Kenny Kane)

This one really resonated with me because it mirrors the experiment I tried recently with my “Bubble Bath” post.

Kenny Kane uses Claude not to generate prose, but to act as a ruthless developmental editor. He uploads a messy draft and runs a “Diagnostic” prompt. He doesn’t ask “fix this,” he asks: “Where does the argument drift? Where does the energy drop?”

He even has the AI analyze his best writing to identify his specific “DNA” (sentence length, vocabulary choice) and then asks it to apply that same tone to his rougher sections. It’s using the AI as a mirror rather than a ghostwriter.

3. The Memo-to-Demo Shift (Dan Shipper)

Dan Shipper at Every is doing something fascinating that changes the definition of writing altogether. He argues that in the AI age, we shouldn’t just describe a concept; we should build a small app to demonstrate it.

If he’s writing about “Spaced Repetition,” he doesn’t just explain the theory. He asks Claude’s Artifacts feature to “Write a React component that lets a user test spaced repetition live in the browser,” and then embeds that little app directly into the essay. The writing becomes 50% prose and 50% software.

4. The Co-Intelligence Loop (Ethan Mollick)

Ethan Mollick focuses on breaking the echo chamber. Before he publishes, he spins up simulated personas—a skeptical VC, a confused novice, an expert in a tangential field—and asks them to critique his draft from their specific viewpoints.

It’s effectively a focus group of one.

How to Get Started

If you’re like me, seeing all these workflows might feel a bit overwhelming. My advice? Don’t try to overhaul your entire writing process overnight. Just pick one experiment to try this week.

Here are two simple entry points:

Experiment A: The “Blind Spot” Check (For Research)

If you are reading up on a topic, don’t just take notes. Open Google NotebookLM, create a new notebook, and upload your sources (PDFs, URLs, or pasted text). Then, ask this specific question:

“Based strictly on these sources, what is the strongest argument against my current thinking? What connection between Source A and Source B am I missing?”

Experiment B: The “Ruthless Editor” (For Writing)

If you have a rough draft sitting on your hard drive, copy it into Claude or ChatGPT and use this prompt (adapted from Kenny Kane’s workflow) before you do any manual editing:

“Act as a senior editor. Do not rewrite this text. Instead, analyze my draft and tell me: 1) Where does the argument lose energy? 2) Does the opening hook successfully promise what the conclusion delivers? Be critical.”

I’ve found that using the tools this way—as a partner for thinking rather than just generating—is where the real magic happens.

Which one will you try first?

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
Inspiration Living Reflection

Exploring the Seams of Freedom

“All of us have little fissures in our lives that provide us greater than normal moments of freedom. You play the seams when you identify those moments and seize them.”

Neal King (American Ramble)

We often conceive of our lives as following fairly rigid scripts and routines. We wake up, go to work or school, come home, eat dinner, maybe squeeze in some hobbies or time with loved ones, then go to bed and repeat. The cycles feel inescapable, like train tracks laid out before us.

But if we look closer, there are tiny fissures and fault lines running through even the most regimented of daily grinds. Moments where the iron grip of obligation loosens ever so slightly. A traffic jam that makes you late, forcing you to take an alternate route. A cancelled meeting that clears an unexpected hour in your calendar. A power outage that shuts down the office and sends everyone home early. A flat tire that happens at the worst possible time and place – like happened to me yesterday!

These are the seams that Neil King refers to in the quotation. Little rips and tears in the fabric of our routines that create momentary pockets of freedom. Openings where the rules don’t quite apply and we can slip through the cracks of the scheduled order.

The key, as King notes, is to first identify these seams when they occur, and then seize them rather than letting them pass by unnoticed or unremarked upon. It’s about being present enough to your circumstances to recognize when one of these fissures opens up, and then brave enough to diverge from the mapped out path to explore it.

After all, some of life’s greatest adventures and discoveries have happened during these “off script” moments. Yesterday, my conversation with a tow truck driver opened my eyes to the steps he took to fend off a mountain lion attack on a 5 AM run in the dark! I hope I never have to apply his techniques but I did find our conversation about his encounter fascinating!

Of course, these serendipitous detours and unplanned paths are easy to romanticize after the fact, when we know they turned out well. In the moment when the seams first crack open, it can be daunting to jump through them into the unknown. Sometimes we have to but our ingrained instinct is to stick to our set schedule, to get back on course as quickly as possible.

There’s comfort and safety in routines. Seizing those fissures when they present themselves means trading certainty for adventure, the familiarity of a well-worn groove for the risk and exhilaration of going off road into the unknown. It requires being able to quiet that voice of fear inside us that clings to control and embrace one of spontaneity and serendipity in where the detour might lead.

The rewards of following those detours down their winding paths are often worth it. While not every seam we slip through will result in a life-altering event, they allow us to break up the monotony, to experience something different from our repetitive routine, even if just for a little while. Those moments add texture and vibrancy to our days. They’re the asides and ad-libs to the main scripts we follow. Often they provide those special moments we vividly remember and want to share with others.

So keep your eyes peeled for those little fissures and unexpected openings in your routine. Don’t just impatiently wait for life to reset to its default settings once these moments arise. Seize them while you can and see where they lead you. You might just stumble into a beloved new local cafe, or finally muster the courage to start writing, or meet someone who changes your life’s trajectory and opens even more new possibilities.

The seams are there, waiting to be played whenever we’re bold enough to follow their diverging paths. All we have to do is watch for the fissures and be willing to step through into the open spaces of freedom they reveal. Who knows what new experiences and challenges await us on the other side? What new learning might result?

Categories
Productivity

A Productivity Field Guide that’s all about Living

Recently, blogger, podcaster and teacher David Sparks (aka MacSparky) introduced the latest in his series of Field Guides – the Productivity Field Guide. This one comes in two flavors: a standard edition ($49) and plus edition ($99) – both include a combination of a PDF and extensive videos that walk you through his process.

The plus edition includes an additional twelve part webinar series doing a deeper dive on many of the topics in the course. I signed up for the Plus edition and have been working my way through the course content and attending the Plus edition webinars as they’re being held.

Although I’m retired and wasn’t looking for the latest and greatest set of tips and tricks to maximize my productivity – like I’d be wanting desperately in my younger years! – I’ve really been enjoying this field guide. The reason is that I find it’s less about productivity – although that’s still the focus – and much more about an approach to living that MacSparky has developed over years and years.

In fact, he’s described how he set out to write this field guide years ago but held off on completing and publishing it until he felt comfortable he had fully thought through and could articulate this approach to living.

The foundation for MacSparky’s approach is to orient life around a series of roles – the many different “hats” that one wears as we live day to day. In his case, his roles (which evolve from time to time) include: husband, father, brother/uncle, friend, MacSparky, ex-lawyer, learner, creative human, spiritual human, responsible human, and altruistic human.

These roles are really foundational to living for him and the rest of the field guide builds on them. As a next step after clarifying your roles, he recommends applying a bit of Greek philosophy – specifically the notion of “arete” or excellence and using that to help define living up to one’s potential. (“Arete” is pronounced “ah-reh-tay”.) So for each role, he spends time defining what the notion of arete means to each role. He then uses those refined definitions to help manage everything he has to do in life – including the inevitable prioritizing required to juggle too many tasks.

MacSparky’s approach to productivity is refreshing – and a whole different approach from almost all of the many other productivity approaches I’ve come across. If this kind of approach sounds attractive to you, I’d recommend you explore what he had to say in his introductory video. I really like the way he’s approaching this and recommend this field guide.

If you’d like to learn even more, be sure to check out several recent blog posts by Jim Eager on his blog OriginalMacGuy.com:

Jim does an excellent job in each of these articles walking through how he is applying the lessons and techniques that MacSparky teaches in the PFG.