A deep dive on how a clothing brand prices their clothes.
Ethan Mollick on Deep Research. I’ve been working with it quite a bit this week and generally speaking been impressed with it.
Musings
“All great work is preparing yourself for the accident to happen” — Sidney Lumet, via The Browser
An underrated truth about the modern world is that everyone reads their @mentions and sees who likes their posts
The Luka trade is a reminder that even at the highest levels, mistakes genuinely do happen. You would think that evaluating the market for one of the 5 best basketball players in the world would be an efficient market… but it appears that it wasn’t!
Reflecting on the ROI of marketing efforts I’ve done recently
Print isn’t that useful unless it’s with a writer with a voice (e.g., a substack)
Audio and video really make an impact. You want to be inside someone’s EarPods.
Speaking at trade shows is helpful in expanding your network
Asking good questions is more important than ever
On the modern internet, one should never be self congratulatory. It’s totally okay to accept compliments from your audience, but the moment you start saying or implying you’re great at something or have it figured out, you begin to sew the seeds of your downfall.
My bias is to think that the most useful AI is the one that has your personal context — your documents, your emails, and all that stuff.
But despite the fact that ~100% of my useful documents are with Apple or Google, I almost never find myself using Apple AI or Gemini, and instead copying and pasting into Claude or ChatGPT. I have meticulously organized project folders in Google Drive, yet I’m never asking Gemini about them.
Does this mean:
My intuition is wrong - model quality is actually more important; over time, our data will move to where the models are. Owning the user was less valuable than we thought it was.
My intuition is right, but it’s still too early; Apple and Google are big, but eventually they’ll catch up and I’ll start using them
Apple and Google are failing in the way that companies fail when paradigms shift and new competitors will rise up to take their place
There’s a stickiness in how models work. I’ve developed a feel for how to use Claude / ChatGPT, what they’re good at and when they’ll bite me, and there’s a lock in quality here. I did feel a sense of exhaustion at having to learn DeepSeek r-1 despite being excited to have a new player on the scene.
I’m the problem. I’m not as exploratory of a consumer as I think I am and actually there’s a low friction way to use Gemini for these tasks that I haven’t figured out yet. I don’t think it’s this one because it’s pretty common for me to choose Chat GPT 4o when I want an answer fast vs. Claude when I have a project already set up with my key documents in it vs. o1-pro / Deep Research (or one of the other models now) when I need a higher quality answer
Something else I’m not thinking of?
Here is what Claude thinks:
This is an interesting reflection on AI adoption patterns. I think the stickiness factor plays a significant role - there's a real cognitive investment in learning how to effectively "speak" with a particular AI model, understanding its strengths and quirks, which creates a natural barrier to switching even when alternatives might offer theoretical advantages in terms of data integration. This parallels how humans often stick with familiar tools and workflows even when "better" options exist, because the familiarity itself has concrete value.
I think GLP-1 drugs might be the most underrated technological change currently underway. We're talking about big shifts in what people eat, how they look and feel about themselves that run counter to the last ~50 years of consumer trends.
With this in mind, I found this Cricana report to be eye opening.
First, I love that the report using real transaction data - this isn't what about what consumers are saying, but what they're doing compared to what they were doing before.
Spending went up on:
🫗 Drinkware and water filtration (+28%)
⌚️ Fitness trackers and wearables (+183%)
🧴 Skin care (+12%)
💋 Lip care products (+14%)
And down on:
🥗 Refrigerated salad dressing (-19.5%)
🥩 Dried meat snacks (-17%)
🍷 Alcoholic beverages (-10-12%)
My simple model here is that people drift away from unhealthy foods and towards healthier ones. As they do this, they start getting out more and doing more things (see the spending on wearables, cosmetics). They're also spending more on the things that mitigate the downsides of the drug (mints for bad breath, tea to soothe stomachs).
The entire thing is worth a read.
(Hat tip to Dan Frommer whose New Consumer newsletter flagged this for me)
Noah Smith on China Talk. Interesting throughout but what I enjoyed most was him talking about the types of posts he writes:
1. Things he already understands that are topical (he can just sit down and write)
2. Things where he is going out and doing the research because he thinks something should be better understood
3. Things he is passively interested in and just collects links as he goes, so when it becomes topical, he can go back and find those things and quickly write them.
I think I can adopt some of this into my own work.
The short case for Nvidia, but also a fantastic explainer on how different approaches to AI work. I now understand what makes Groq special.
Musings
Goals:
I’ll never forget standing in your kitchen in Oakland, watching you juggle a toddler and two babies while making margaritas and asking you about your next venture - what problem you wanted to solve. You looked at me replied “I want to bring commercial super-sonic flight”
The most successful one was drafting an update to a document. We have a Partnerships document that we use as a part of our sales materials and we're onboarding a new partner. I needed to go to the Partner's website and draft some language for them to edit / approve.
I've been putting this off for a couple of weeks so I fed it to Operator. It took a little nudging, but eventually it was able to read through their site and write passable copy that I could refine and send to the partner for their review. So that's a success. Worth $200 a month? If I have 2-3 tasks like this each month, I think so.
I also tried seeing if I could get Operator to compile information for me (e.g., create a CSV file with the meeting dates and times of the Roswell City Council for the rest of January). It failed here in two ways:
First, the meetings were wrong. It grabbed one that was in the past and then chose not to grab some of the meetings upcoming this week. It's possible that some of this was prompter error and could be fixed with more trials.
There was no easy way to export the information. I wanted it to create a CSV file for me, but couldn't get it to. I do imagine that this will improve over time.
This past summer, I tried out several other products in this space (e.g., AutoTab) and this is a big step beyond what was possible then... but still not there yet.