jdilla.xyz

What if OpenAI actually does have a moat?

2025-02-06

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.

What Google gets right

2022-07-29

It’s somewhat popular now to throw shade at Google1, particularly as a place to work: it’s big and bureaucratic, it’s not a good place to start your career and so on. I understand this impulse, but I disagree with it. Particularly for its size, I think Google is really effective company and rather than bagging on it, people should think about what has allowed it to stay as effective as it has despite being as big as it is.

I think people typically misunderstand Google in two key ways that then causes them to misjudge it:

Google isn’t a start up. It is one of the largest companies in the world, with more than 150,00 employees and about as many contractors. Its peer companies, in terms of number of people, are General Motors, Darden Restaurants, and Aeon, to name a few. Just to try and put this into context, my entire current company (Stripe) is smaller than my product area at Google (YouTube).

Because many people still remember Google as a younger, smaller company, they judge Google’s agility against much younger and smaller companies instead of against its peer set. Certainly it’s less agile than it once was, but on a size adjusted basis it’s one of the most agile companies in the world.

Google is much more decentralized than a typical company. I joke that the best way to think about Google is a university attached to a money printing machine. Like a university, Google has many different departments that really aren’t trying to coordinate with each other. This is by design. You may not agree that this is the right strategy, but I think you have to understand it to effectively evaluate the company.

So what does Google get right? Here are four things that come immediately to mind for me.

  • Product focus: an incredible amount of attention is paid at all levels of the company to the specifics of the product — what it actually does for the user. As a typical YouTube product manager, I regularly had to review product details with head of product, head of engineering, and other very senior leaders. These leaders, several levels up from me, were more well versed in the specifics of my product area than my manager or my head of product was at much smaller companies. This product focus isn’t top down, but cultural, which makes it much more powerful. People at Google encourage other people at Google to use their products and have opinions about how they should work.

  • Distributed decision making: For me, this is where the misunderstandings about Google begin to really show up. Google is incredibly effective at decision making for a company of its size. An incredible amount of relatively high stakes decisions can be made at Google very quickly. As an example, if my team made a product change that positively impacted our key metrics, I could have that launched globally to billions of people in two 15 minute meetings.

    Additionally, Amazon gets a lot of mileage out of the Bezos API mandate, but it’s pretty common at Google as well to have some internal help text and an API be all that is needed for different orgs to collaborate. Additionally, as long as team incentives are aligned, it’s pretty easy for individual teams in different orgs to collaborate without any formal sign off from their Product Area Leads.

    Where things do get complicated at Google is major collaborations across product areas where there is a lot of ambiguity. So for instance, if I wanted to get a couple of teams from Google Maps and a couple of teams from YouTube to collaborate on a set of features with high but uncertain potential, I knew that this was going to be a difficult and challenging path. And yet, as difficult and challenging as this would be, on a per person basis, it was much easier to get collaborations like this to happen than at <1,000 employee companies that I’ve worked at.

  • Talent friendliness and talent development. The slides and free lunches are really easy to make fun of, but Google legitimately tries to be a good place to work. The default policies are sensible and friendly to employees. When they make a change, they try to make sure to not punish their people along the way. It isn’t perfect, but especially for its size it’s really good.

    Beyond its policies, Google is a great place to develop your career if you’re thoughtful about it. As long as you’re keeping up with your day-to-day work, you can get exposure to almost any career path as a twenty percenter (once again, think of a university rather than a traditional company). Here the breadth of Google’s product offerings is a real asset; you can get exposure to almost any discipline or industry without changing companies.

Caveats: I worked at Google for about two and a half years, entirely at YouTube and mostly in the Zürich office. Google is a big place that varies a lot by team, so it’s entirely possible that my experience is an outlier. There are also many legitimate criticisms of the company that I’m not the best person to articulate.

Notes: 1: Alphabet