Category: AI

Learning to Work with Claude CoWork

~ Sasha ~ 1 Comment

Since our team hackathon, I’ve been working much more with Claude CoWork. It’s amazing, to be sure, and it also takes some getting used to.  Here are some reflections.

My biggest adjustment going from ChatGPT/Google—tools I use to answer questions—to Claude CoWork—a tool I use to do jobs—is how not-instant the turnaround is.

I, and we, have been trained to ask a question and get an instant answer. That is not what CoWork is like at all.

My CoWork experience is:

  • Describe a problem
  • Clarify the problem
  • Wait a while
  • Review the solution
  • Give feedback
  • Wait a while
  • Repeat a few times
  • Deploy
  • Test
  • Give feedback
  • Wait a while
  • Clarify
  • Deploy
  • Test
  • Give feedback
  • Wait a while
  • Etc

What I’ve found surprising is how much faster the non-bolded (my input) part is than the bolded (wait a while) part. That adds up to a lot of waiting.

While this is not inherently problematic, the experience is not “I’m going to work on this problem for the next hour.”

It’s much more like talking to a person who’s going to work on something, having that person go away and come back 5 minutes later. It’s fast enough that you can’t really do another thing, but slow enough that you can’t only do this thing.

For example:

On Friday I set out to build a web app to manage our EOS deployment.

(Aside: EOS stands for Entrepreneurial Operating System, and it’s a well-established management system used most often with small- to medium-sized companies—somewhat akin to OKRs. You can read all about it in Gino Wickman’s book, Traction.)

We’ve been running EOS for about a year at 60 Decibels, and for each team we have a detailed Google Sheet with that team’s quarterly priorities and workplans.

Now that we’re deploying EOS across functions, that adds up to 5-6 EOS workstreams, each with 3-5 quarterly plans, and each plan has 5-10 weekly tasks for various team members, plus other To Do’s. It quickly has become a lot of (too many) spreadsheets and tasks to manage.

Of course there are EOS software solutions we could buy, but, at this point, the last thing I want is another piece of SaaS software that doesn’t quite do what I want.

So I decided to build a webapp that would (1) Give a global view of EOS across the company; and (2) Help each person on the team easily see everything they need to do across all their workstreams each week.

I set aside a chunk of time on Friday to do this, and I did build a working app over the course of a few hours. Hooray! It’s pretty great.

But the build experience was different from what I expected: much more like baking sourdough (a small amount of doing, a lot of waiting) than writing a blog post (“I am working for the next XX minutes”).

I’m not used to structuring time / work this way. Instead of focused work, it feels more like “fiddle with this during the commercial break” (which is what I did watching the women’s NCAA Final Four, after I had the app up and running).

Even right now, I’m writing this blog post while tweaking a few things on the webapp in the background, because each of my inputs is <30 seconds and each output takes a few minutes.

It’s workable, but I’m finding it difficult to bounce back and forth between more focused tasks and Claude CoWork. So I’ve been working on the webapp while dealing with my Inbox, or catching up on Slack. That’s fine, but not a great way to spend 3-4 hours.

I’m sure some of this is my own inefficiency, because I’m not eyeballing any of the code before deploying it. And, to be clear, this is not to take away from how amazing it is that I have useful enterprise software that I’m deploying on a Monday with ~4 total hours of attention. But the experience is much more herky-jerky than I’d expected, and I’m a bit stumped with how to work these builds into my (and my team’s) regular workflows.

And, I must confess, it’s also surprising how amazingly easy seemingly big (UI) things are, and how difficult other small-seeming problems are (‘only show me tasks that are due this week).

(Somewhere out there, a PM and an engineer are quietly chuckling to themselves…)

More seriously, if you’re a leader asking your teams to lean in aggressively to these tools, you’ve got to use them yourself to develop some intuition about where they are great, where they are challenging, and what it takes to go from a “wow” prototype to something your teams can actually use.

(Bonus: if you want to geek out on the scale of change that is happening, whether there really is a SaaSPocalypse coming, and how much org charts might be changing, check out the latest Decoder (Verge podcast) with Todd McKinnon, CEO of Okta.)

Finally, a number of small, in-the-weeds tips if you’re new(er) to CoWork:

  • Create .md files for each topic you’re going to go deep on.
  • Recommendation is <200 lines each
  • I started with 5 background files for topics I wanted to go deep on
  • I am also creating updated .md files at the end of long sessions in the hopes that Claude will learn from those sessions (my preferences, mistakes it made, etc.)
  • For any properly large project, I’m using our company Max account. I have a Pro account also for myself, but I’m finding Pro times out more than Max, and I run out of tokens pretty quickly, even for seemingly small things.
  • For small and quick things, I’m still using Projects in ChatGPT, though I’d rather not
  • I’m only using the Desktop App
  • I was told by a friend that I should actually be using Claude Code for everything, not CoWork, but I haven’t yet.

Here’s a screenshot of my new app.

The Global Majority Data Project

~ Sasha ~ Leave a comment

I’ve been quietly working on an idea that I’m very excited about. It’s an initiative that will bring more of 60 Decibels data to life and will make this data—and the lived experience of the people it represents—more useful to more people.

The basic concept is that AI is being trained on data from a narrow slice of humanity. The voices of billions are missing.

This initiative, called The Global Majority Data Project, will build the infrastructure to make the lived experiences of the world’s most underserved communities both vivid and accessible, so that these experience can influence how decisions are made.

I’m in the early stages of fundraising for this work, and I’ve been talking about it with folks I know in the AI for good space.

After a few great conversations last week, the thought occurred to me: a nice website for this initiative would help move it forward.

But who has time to build a website? Certainly not me (time, or know-how).

And then I thought about the AI Hackathon we’re doing this Friday at 60 Decibels and realized it was time to eat my own cooking.

I had the idea for the website at the end of the day on Friday.

On Saturday, I sat down at noon with Claude CoWork.

At 3pm the site was live.

This is a massive step change in leverage for me (and it could be for you).

What I had on hand at noon was a whitepaper describing the project and existing branding from 60 Decibels.

Three hours of conversation with Claude (including a decent amount of waiting, because it was ‘thinking,’ so I cleaned up the kitchen) to make a high-quality website.

Think of what else it can do.

For those of you who have been using these tools, this is not a surprising outcome. For those who haven’t, I hope this serves as a concrete example of what is now possible.

Normally I’d end the post here, but I thought some specificity would help.

If you’d like to read on, here’s a detailed summary of what I told Claude and how the whole process unfolded.

I hope you’ll take this as inspiration to go build something meaningful.

And if you have ideas for folks who might want to make this idea come to life, please send them my way! (the contact form is on the website).

My Claude Prompts to build globalmajoritydata.com

  1. My initial prompt

OK I want your help building a website to support the Global Majority Data Project. Here’s the white paper that it is based on.

I already have a company – 60 decibels – so I don’t need this to be a new company,

it is an initiative of 60 decibels. I am raising money for this and want to see if I can make a decent website easily. Ultimately I expect that if it’s good, the pages will move to the 60decibels.com domain, but I just purchased globalmajoritydata.com on GoDaddy.

So what I want to do is:

  1. I’ll share the brief
  2. I’ll share a few websites that look like what I’m interested in – obviously the branding should mostly align with 60 decibels
  3. I want you to give me some options for how to approach this, ask questions, etc…I don’t want you doing too much work building until we are aligned on how it’s going to be structured and what it will look like
  4. I’ll want you to create the structure of the site and the draft copy for me to approve
  5. Once that’s sorted, we’ll work on look and feel
  6. Then you’ll do the homepage
  7. Finally, you’ll do the rest of the site

How does that sound?

Any questions?

  1. Claude asked two rounds of clarifying questions—tone, structure, site size, audience, etc.—which I answered. I also uploaded my existing Global Majority Data Project whitepaper.
  2. I had to fiddle with the Chrome for Claude extension, which wasn’t behaving. Claude suggested skipping it; I insisted we fix it. We did.
  3. With Step 1 done, Claude asked for reference sites (Step 2). I shared a few. It reflected back what it inferred from them and proposed two structures: single long scroll or multi-page.
  4. I reacted to the structure, added a missing page, and outlined what it should contain.
  5. Claude drafted full-site copy, page by page. I reviewed it, gave specific comments, and it incorporated them.
  6. It asked for images. I found ~30 from internal documents and from various 60dB published assets and uploaded them.
  7. It produced a first draft of the site. Some of it was jaw-droppingly ugly. I gave pointed feedback. We went ~4 rounds on design, then I did smaller copy tweaks.
  8. The site was nearly ready. Claude generated HTML pages for browser preview with no images. It said mine were too low-res, so I bundled them into a PPT and re-uploaded.
  9. A few more rounds of feedback about the images on the site: adding variety, eliminating repetition, tightening a few style choices.
  10. (Fun moment.) I said, “Looks great, let’s publish.” Claude replied, “You’ve flagged a style issue three times that I haven’t fixed. Want me to try another approach?” I said yes.
  11. I asked how to publish. It gave instructions, which I followed. I was mostly lost at this step, but it walked me through them (with me pasting a bunch of screen shots and saying, ‘what does this mean’?). I had a handful of DNS issues that took some time to resolve.

And that was that. The site is live. Pretty cool, huh?

 

Turning the Corner on AI

~ Sasha ~ 1 Comment

The context for AI has changed.

If you haven’t yet, I’d encourage you to read Something Big is Happening, by Matt Schumer.

It clearly explains the AI revolution taking place right in front of us. Here’s how the essay starts:

Think back to February 2020.

If you were paying close attention, you might have noticed a few people talking about a virus spreading overseas. But most of us weren’t paying close attention. The stock market was doing great, your kids were in school, you were going to restaurants and shaking hands and planning trips. If someone told you they were stockpiling toilet paper you would have thought they’d been spending too much time on a weird corner of the internet. Then, over the course of about three weeks, the entire world changed. Your office closed, your kids came home, and life rearranged itself into something you wouldn’t have believed if you’d described it to yourself a month earlier.

I think we’re in the “this seems overblown” phase of something much, much bigger than Covid.

Once you read that, I’d encourage you to look at this webinar announcing Claude CoPilot (40 mins full speed—but you can get through it in ~15 if you really want to).

It starts with this statement (paraphrasing): “most people are using AI to ask questions; the people who are going to stand out are the ones who get it to do things.”

I am in the category of “good at using AI to ask questions, but I don’t use AI to do things.” That’s not where I want to be so I’m going to make a new, more concerted effort to cross the next chasm—and we’re holding an AI Hackathon at 60 Decibels next week to jump start our next phase of usage of these tools. According Boris Cherny at Anthropic (from the webinar), he has CoPilot doing his project management for him, and he used it to unsubscribe from a ton of services he wasn’t using. (I appreciated the honesty of his top two use cases).

AI isn’t going anywhere. If you sit near anyone whose job used to be writing code, you know that they’ve mostly stopped writing code and are now having AI tools do that work for them. Their leverage is 2-10x (and increasing).

That’s where we all could be.

And, as they say, the best time to jump in was 5 years ago, but the next best time is today.

(friendly reminder: for all of these tools, you want the paid version. It makes all the difference).

The Problem with AI Writing

~ Sasha ~ Leave a comment

“Writing and reading is a way of underscoring that human connection is important. That you can know my mind and I can know your mind — which is a vastly consoling idea…So may times in my life, I felt a more articulate version of myself emerge after a period of writing. And when that happens, the world changes.”

– George Saunders, author of 13 books and a recipient of the National Book Foundation’s medal for Distinguished Contribution to American Letters

George Saunders, author of Lincon in the Bardo and many other works, is an acclaimed author and essayist who has also been called “the ultimate teacher of kindness and of craft.”

I’ve been casting about for an explanation of what’s worrying me when I read more and more AI-generated content. Saunders’ explanation—you can listen the whole conversation here—gets to the heart of the matter.

The question is: what is writing, really? And Saunders’ answer is anchored in the idea of two people knowing each others’ minds, and the beauty in that connection.

That’s the thing that’s tripping me up with all the AI-generated writing, a doubly confusing experience I’m also finding my own AI helper(s) to be radically useful: as brainstorming partners, as “I think this thing isn’t quite right, but I’m not sure how to make it better,” as a project planners… but very rarely as a writer, and never as a writer of this blog.

Like George Saunders, I’m writing for two reasons: to figure something out (a sharpening of my understanding that comes from sitting with and articulating an idea), and to personally connect with readers.

And something breaks when I’m not the person writing the words, and when I’m reading words not written by a person.

I’m sure you’re having this experience as often as I am: working your way through an article or an email or some other document, and you come across a sentence or a phrase that is so stylistically ChatGPT that you stop…and in that moment, feel a strong sense of disconnection.

For example, I was reading this interesting post about searching job listings and pay rates to understand what skills AI firms are paying for to feed their models (answer: “the bottleneck for AI is no longer information (facts); it is expert reasoning (process).) While the research and the conclusions in the article are interesting, the writing is so clearly authored by ChatGPT that I quickly disengaged.

The reason for that disengagement Saunders’ severing of human connection.

It’s as if there’s an implicit equation that I’m carrying around in my head, something about balancing:

The author’s effort in getting the words just right =  My effort as a reader to sit with and deeply understand what the author is saying.

Because when the author cares enough to toil over every word, that means that they are carrying around an idea that matters deeply to them.

If the author truly cared, if the author takes the work personally, then I do too.

(aside: if I’m reading something equivalent to a textbook. If I just am acquiring knowledge or skills, I’m fine with the computer writing most of that text).

Whereas, if my effort in deciphering a 1,000 word post is greater than what it took the author to create it…something feels fundamentally off. I feel like I’m being had, that that essay is part of the mountain of words generated by a computer model that doesn’t mean much, really, to the person who “wrote” it.

What’s curious is that the models will get better and this moment will pass. What happens when it’s impossible to tell the difference?

I don’t know how to answer that with confidence, but I’ll stand by my view that I’m reading because I want to see through a window into the mind of another person—whether it’s fiction or nonfiction, analysis or some fantastical world.

The intent and the human behind the words are the reason writing comes alive. It isn’t just words on a page, it is the effort, struggle and care of one person opening up their mind and heart. That’s why I’ve rewritten this post four times in 12 hours 🙂

We write what we believe, what we care about, what we’ve thought about, and then we share that with others. The connection is personal, the words are the medium.

The moment that connection is severed, I find it much harder to show up as a reader with my full attention.

Podcast Alert: Patrick Thean

~ Sasha ~ Leave a comment

Patrick is an author, CEO coach and mentor, and I was happy to get the chance to join his podcast recently. Our discussion covered topics that will be familiar to readers of this blog and, as always, I discovered that talking about a topic helps me understand the topic better.

If I had to summarize my reflections from the conversation, they are:

  1. How we do anything is how we do everything
  2. One way to learn how we do anything is by digging into new domains we are exploring

What follows is a conversation that starts with 60 Decibels,  my motivation for doing work in the social sector and my Generosity Experiment; but quickly turns to learning to play the guitar, my favorite AI use cases, and the attitude Patrick and I would suggest towards getting over your lingering AI resistance.

You can listen to the full podcast here (20 mins):

• Apple: https://bit.ly/3GB5W0P
• iHeart Radio: https://bit.ly/40eTeLU
• Spotify: https://bit.ly/4lqkhfM

What to Wear in the Rain

~ Sasha ~ Leave a comment

If it’s pouring rain out, and you’re heading for a walk, you have two good options.

A completely waterproof boot, one that will keep your foot totally dry.

OR

A flip flop, one that will allow your foot to get soaking wet, but you don’t care, because it’s your foot and it’s a flip flop.

Meaning, when your external environment changes radically, there are only two smart ways to react: you either decide you use the tools you have to fight it head on and win, or you choose to fully embrace the new reality.

Unfortunately, all too often we opt instead for a soggy shoe, soggy sock strategy, one that leaves us squishy and uncomfortable because we planned poorly and didn’t fully acknowledge that our world has shifted.

(and, no, this post isn’t only about AI).

Use AI to Turn Meetings into Action

~ Sasha ~ 1 Comment

My friend Irwin reminded me today of two things:

  1. How good it feels to figure something out
  2. How dangerous that good feeling can be

Meaning, if you’re a thoughtful, analytical, caring person, there’s a significant psychological payoff in diagnosing something correctly.

Imagine this:

  • There’s something not quite right going on in your company / organization (someone is unhappy, some process isn’t working, some results are off)
  • You and a colleague or two get together to figure out what’s what
  • You have a great conversation and unearth important things
  • Voila! You come up with real clarity on what’s wrong and what needs to happen

That’s all great, but be careful about how good that “Voila!” feels.

What happens next, for many of us, is that we jump to the next thing: another meeting, another task.

And the risk isn’t simply that we’ll lose some of the texture or nuance of the clarity we had in the meeting, though that often happens.

The risk is the fact that the meeting feels like success. We got to the answer!

At the extreme, a great conversation that leads to no action is literally worthless.

Even if you don’t fall into this trap, is it possible that the psychological reward of experiencing that insight and clarity lead you to do 70%, or 60%, or 50% of what you need to do? Could it be less?

If so, I have a proposal for you.

  1. Start by scheduling differently. For any problem-solving meeting, keep the hour after the meeting free / scheduled for just you.
  2. In addition (optional), record the meeting with an AI tool. (You decide your comfort level with this; I’ve found it very helpful.) In addition, take whatever notes you’d normally take during the meeting.
  3. At the start of your scheduled hour after the meeting, go to your paid AI tool of choice. While everything is still 100% fresh in your mind, speak (not type) freely to the tool. What’s the problem you were trying to solve? What were the specific issues you worked through? What solutions did you come up with? Talk as you would talk to a colleague who would want to understand all the ins and outs. Lots of detail. All the little juicy bits. Everything.
  4. Finally, take that text and ask the AI to summarize what you’ve told it. Ask it to give you a well-defined structure: headline problem statement; detailed issues that were discussed; proposed solutions.

(Here’s a starter prompt: What I just described is the output of a 90 minute problem-solving meeting. Take that detail and write a structured summary of the headline problem, sub-issues, and all proposed solutions. Be as detailed as possible. Before you start, make sure to ask me for any additional context you need and/or any clarifying questions. I want you to be confident you understand everything I’m saying and my proposed solution.)

These steps—from your input to the first AI output—shouldn’t take more than 10 minutes: you talk for ~5 minutes, write a prompt, respond to questions from the AI tool, get the first summary. Now the fun begins.

Read the output the tool has given you and start working with and through the AI.

You might say/write things like “this point you made wasn’t quite right: [quote the point]. Here’s why:” and explain it in more detail. Do this both for things the AI didn’t explain well and for areas where reading the summary helps you see gaps you didn’t see before. Keep at it until you have a document you’re satisfied with. This step can easily take 30 minutes or more.

Once you’re mostly satisfied with the content, structure, tone, and detail, you’re ready to put the finishing touches on the document.

I find myself consistently asking the AI to be a more specific with its points / language / descriptions, and I inevitably go into the document and edit some parts myself. I also always ask for specific next steps, a timeline/workplan for all parties involved, and a 1-2 page executive summary.

Voila! again, but now your best thinking is turned into a detailed action plan. With this approach, you’re:

  1. Capturing, and acting on, that beautiful moment of insight you have at the end of a great meeting
  2. Seeing what a professional summary of those insights looks like, so you can make it better
  3. Forcing yourself to engage in further brainstorming to refine your idea
  4. Creating clear next steps and a timeline
  5. Documenting it all in ways that makes it easier for everyone to act

If before you were acting on 50% of your best thinking from the meeting, this approach gives you 150% or more.

The 90 Percent Expert

~ Sasha ~ 2 Comments

Think about your experience reading the newspaper: on most topics, the quality of the journalism, the insights and the perspective hit the bar for you. That’s why you read, after all.

Except in the rare cases when there’s an article about your area of expertise. Then the Emperor has no clothes. You can see where all the shortcuts and generalizations are, all the misses that the journalist made, the questionable choices on expert sources.

But does that stop you from reading the newspaper? Of course it doesn’t.

In a discussion group that I’m part of, one member suggested that this is how we should think about AI: it’s not perfect, but it is so good so often, that we shouldn’t let that 10% of time where we can see the flaws keep us from using the tool (read: keep us from reading the newspaper).

If you’re still stuck on this side of the fence, it might help to personify your AI a bit—meaning, move from “I’m going to use ChatGPT/Claude/Perplexity etc.” for this task to “I have access to a 90% expert across any topic I can think of.”

I’ve already shared my ongoing use of ChatGPT as a physical therapist, which is still my favorite use case.

This weekend, I used ChatGPT as an Apple Genius Bar Employee—because making an appointment at, and going to, the Apple Genius Bar is a hassle.

I had an old, powerful Mac that my son had used, and I wanted to wipe it clean. It was not playing along.

First, my son had partitioned the hard drive, so that created a series of problems. Then the Operating System refused to update—it took 6 different attempts at that problem to get it solved. Then, with a new OS installed, iCloud login wasn’t working (because the laptop is for my daughter, and age restrictions with Family Sharing didn’t allow her to log out). Etc, etc, etc. until I solved the problem a few hours later. All of this with ChatGPT calmly troubleshooting with me, providing a series of options, being endlessly patient when I asked new questions or corrected it. I’m positive I would have failed at this task a year ago with just Google search.

The laptop is beside the point (especially because, once I’d solved the problem, we discovered that the battery life was terrible….argh). The point is to think about what it means to have access to this kind of expertise: the best gardener, the best physical therapist, the best coding instructor, the best brainstorming partner.

Better yet, that expertise doesn’t have to be generic (though the generic is pretty amazing). Seth Godin has created a series of personas on Claude, each of which has been taught to respond like some of the greatest thinkers and doers of all time.

So if you have a question for Charles Darwin, Fredrick Douglas, Stephen Pressfield, Seth Godin, Zig Ziglar, Annie Duke, Carol Dweck, Clayton Christensen, David Allen, Mahatma Gandhi, Kevin Kelly, Marcus Aurelius, Simone Biles, Tim Ferris, Sun Tzu, Pema Chodron, or 36 other world-shakers, the answers are at your fingertips.

Try spending a week carrying around the idea, “I have access to a 90% expert on any topic in the world.”

Choose to act on that idea by consulting that expert on a real problem you’re facing.

I promise you you’ll get great (but not perfect) answers fast, in ways that might just blow your mind.

My AI Physical Therapist

~ Sasha ~ 2 Comments

My Instagram feed is basically:

  • The 10 people I follow (including my son’s ceramics account)
  • Dogs / puppies / rescues
  • Tennis / squash tips and highlights
  • Injury prevention / cures for middle-aged athletes

On the last point, my last few years have been marked by a series of minor but chronic injuries. I seem to be in the stage of life of small ligament and tendon strains, injuries that respond well to physical therapy if you can make the time.

The worst has been tennis elbow (lateral epicondylitis). It’s lasted for more than a year, and I’m just now getting better. But I’m finding PT too time-consuming (90-120 minutes so I can do 20 minutes of exercises??) and too much of an insurance hassle.

In a continuation of this trend, a month ago, I got a sharp pain in my hip after a run. After a few dead-end YouTube attempts, I realized I didn’t know what was wrong with me.

Rather than go to the doctor and then back to PT, I turned to ChatGPT. I was amazed with how helpful it was. If you, like me, are still under-using these tools, perhaps this can be an inspiration.

Here’s the original prompt I wrote:

I need you to be an expert physical therapist who can help me diagnose and treat injuries at home. Be thorough in your diagnosis and assume that I am a sophisticated lifetime athlete who can do complex exercises at home as needed. I’m 51 years old. I need to diagnose a pain I have in my right outer hip, just below my hip pointer.

I got the injury after a fast (for me) hilly run after having taken off a few months. This was my 10th run after having taken 3 months off. I had done the same run, 4.3 miles, twice earlier in the week, but my pace in those was 9:30/mile and in this run was 8:20/mile. I felt no pain during the run but after the run it hurt some to stride / step with my right leg, and to go up hills. The pain is greatest when I get up after sitting down for a bit. After a little while it decreases. The pain is sharp and localized to the area just below and above the hip pointer.

From this prompt and a few follow ups, ChatGPT gave me:

  • Its first diagnosis (either a tendinopathy in my gluteus medius / minimus or a TFL overuse injury)
  • A series of diagnostic tests I could do to narrow down the potential injury
  • A full 30 day PT plan that I now have in a Google Sheet that I’m following daily
  • This plan includes descriptions of all the exercises with references.

Since this went so well, I’ve kept talking to ChatGPT about how it’s going: how the exercises, felt; how one of them hurt more than expected and could it give me an alternative; how I feel first thing in the morning and over the course of my day. It’s the conversation I would have with my PT every day if he were available.

With this feedback, ChatGPT both modified the exercise regime to better suit how I’m feeling and has modified the diagnosis.

Here’s the latest that I got back this morning, based on my updated symptoms:

Differential Diagnosis Recap

Condition Why It Fits Why It Doesn’t
Gluteus med/min tendinopathy Pain with heel strike, long stride, compression from sleep, improves with warm-up —
TFL overuse Could be involved, but unlikely primary now; less direct heel-strike involvement Less pain with bridge, more lateral than anterior
Trochanteric bursitis Possible secondary irritant But no diffuse swelling or tenderness reported yet
Labral or joint issues No locking, groin pain, or deep ache Very unlikely
Femoral stress reaction No deep bone pain or night pain Very unlikely

And here’s a visual representation of what I’ve told my AI physical therapist and what that means for my diagnosis—this pretty much blew me away:

I know that for many people, AI is an idea—perhaps even a scary one—and not something that’s part of daily life. And I can understand why many of us might be happier either using none of these tools or waiting for someone to build a “Virtual Physical Therapist” app rather than playing around with ChatGPT or the many other tools available to us today.

I’d encourage you to think about this another way: for $20 / month, an expert in literally any topic you can accurately describe is available to you and to your team.

It’s a shame not to take advantage of that.

Is “Polished” Writing a Good Thing?

~ Sasha ~ Leave a comment

How we communicate evolves with time and with the medium.

I write my texts (mostly) like I write my emails, resulting in my kids repeatedly telling me that it sounds “aggressive” when I put a period at the end of a text message.

(They also want me to use exclamation points much much more! LOL)

While I’m comfortable with the idea of tone and style evolving over time and in different contexts, I’m uncomfortable with what happens when we no longer need to struggle with a blank page. I’m skeptical that it’s a good thing that Gmail is now offering to “polish” my posts and that LinkedIn suggests “rewrite with AI” every time I string a few words together.

Clear writing and clear thinking co-evolve: I don’t know anyone who writes well who doesn’t think well; and how we express our thoughts in written form is a great way to reveal whether our thinking is as clear as it needs to be. I also know that convenience will win out—why wouldn’t it?—and that the cost of all of this convenience will be mostly invisible.

It’s already established that AI is most useful when you have subject matter expertise, so you can tell the difference between good and bad, and use these tools as leverage for your strengths.

How do we avoid systematically undertraining ourselves as strong writers and strong thinkers, to use the tools without having them replace an activity that sharpens our mind?