gmays

The top AI use county in CA is Yolo county...

Agree. And the meta point, after reading through to the core committer channel on the WP slack is that it's clear he's now more involved in the project again and making decisions. I haven't been involved for years, but while I was it seems he had other priorities (understandable).

But the rapid changes from AI are an existential threat to the long-term viability of WP. Rather than bike shedding about something relatively trivial, they need to focus on the bigger issues, which it's apparent he's trying to do.

Interestingly, the culture that sustained WP over the last 2 decades may now be working against it. Culture is really hard to change, but he now seems to have his 'wartime CEO' hat on trying to do it, which is the right move.

I didn't want to hassle with migrating my WordPress blog, so now just deploy it to Github > Cloudflare Pages so it's served statically (fast + secure). It's free too, wrote a blog post on it a couple years back: https://gmays.com/how-to-host-wordpress-sites-free/

But these days any new site I build is on NextJS since coding agents make it a breeze.

Slick UI and well thought through, like the simplicity of the approach.

On the collab side, any limitations on simultaneous users? Like just a couple at a time or can handle a team?

Good point, it's a mix. The "it'll only get harder" is also because things are moving so fast and it takes time to learn (especially across teams) and change habits. No past paradigm has moved this quickly, which makes it hard to grok.

I also fully agree with "don’t overdo your investment into this generation of tools". IMO there are too many "cutting edge" tools trying to do all of this sexy stuff that'll be irrelevant in the next few months.

It's best to keep things simple with tooling. I push the edge on my general approach (99% of everything is AI coded) but conservative with my tools (pretty much only using Cursor now) to have at least some layer of stability. Otherwise stacking too many cutting edge things just feels too fragile, and will decay as AI improves, causing other issues. And this stuff is moving so fast and these companies are sufficiently motivated that the best things will make it into the tools, like plan/debug modes in Cursor.

I also feel that agentic coding is fast enough for now, so I don't even bother with multi-agent workflows. I still get a ton done and it's already at the edge of my ability to design coherently. Sure I could get 10X more code written in parallel with 10X more agents, but I can't design that fast, so it's just hurry up and wait with worse quality. And if that much code is needed I'm probably doing something wrong anyway.

Same. This is a surprisingly simple recipe for a happy life and helps prevent lifestyle inflation. It reminds me of PG's "Keep your identify small" (https://paulgraham.com/identity.html).

That's fair, but it wasn't the point of the article because it's messy. Many would argue that core LLMs are 'trending' toward commodity, and I'd agree.

But it's complicated because commodities don't carry brand weight, yet there's obviously a brand power law. I (like most other people) use ChatGPT. But for coding I use Claude and a bit of Gemini, etc. depending on the problem. If they were complete commodities, it wouldn't matter much what I used.

A part of the issue here is that while LLMs may be trending toward commodity, "AI" isn't. As more people use AI, they get locked into their habits, memory (customization), ecosystem, etc. And as AI improves if everything I do has less and less to do with the hardware and I care more about everything else, then the hardware (e.g. iPhone) becomes the commodity.

Similar with AWS if data/workflow/memory/lock-in becomes the moat I'll want everything where the rest of my infra is.

OP here, good points.

Your comment on Intel is correct, but it's also true that TSMC could invest billions into advanced fabs because Apple gave them a huge guaranteed demand base. Intel didn’t have the same economic flywheel since PCs/servers were flat or declinig.

That's a good clarification on Amazon, running on commodity hardware with competitive pricing != competing on price alone. It would have been better to clarify this difference when pointing out that they're trying the same commodity approach in AI.

True, but Apple is a consumer hardware company, which requires billions of users at their scale.

We may care about running LLMs locally, but 99% of consumers don't. They want the easiest/cheapest path, which will always be the cloud models. Spending ~$6k (what my M4 Max cost) every N years since models/HW keep improving to be able to run a somewhat decent model locally just isn't a consumer thing. Nonviable for a consumer hardware business at Apple's scale.

I'm somewhat bullish on Google as well, they have the opportunity if they can figure out the product (which they are bad at) and they have the edge in cloud with their models + TPUs.

But your comment about the phone could have been about horses, or the notepad or any other technology paradigm we were used to in the past. Maybe it'll take a decade for the 'perfect' AI form factor to emerge, but it's unlikely to remain unchanged.

Right, but remember Microsoft was 'working on' mobile also. The issue is that they're working on it the wrong way. Amazon is focused on price and treating it like a commodity. Apple trying to keep the iPhone at the center of everything. Thus neither are fully committing to the paradigm shift because they say it is, but not acting like it because their existing strategy/culture precludes them from doing so.

The special sauce:

"GPUs leverage hardware-compiler techniques where the compiler guides hardware during execution."

For context in response to the questions about "Why build on X?"

I've be working to relearn math and there happens to be a large group of others also doing the same with Math Academy and sharing daily updates on X.

I found this inspiring (especially as the lessons got harder) so I tweeting my updates too. But I also wanted a way to independently track my progress across math and other areas to see progress over time, even if I changed tools or stopped tweeting.

So that's the reason I built app on X: So my tweets get logged in a GitHub-like habit graph to show progress over time. It just pulled my bio/profile from X (login with X) and tracks my habit tweets. It's super simple, but meets my needs perfectly. My habit page: https://xtreeks.com/gabemays

I understand the questions around the long-term stability of the API, but I'm optimistic.

I've started using X a lot more in the last few months since I built an app that let's you track habits with a tweet called Xtreeks (yeah, I know..).

I enjoy the product, but wish they'd spend more time making the core elements of the product work. For example, aspects of the API just don't work as expected, like for some reason search and mention endpoints do not have support for long form posts (>280 characters) enough though X supports posts with thousands of characters. The result is the API appears to work for some posts and just silently fails for others.

In addition to the API issues, we've struggled with inexplicable labeling/suspension and shadow banning, even on the personal account I've had for over a decade (seemed to be triggered by using my VPN). I understand the desire to control spam, but it seems excessive. Or if you do it excessively, at least provide adequate tools/support to request review.

On my app's X account I paid for both API access ($200/mo) and the Verified Org status ($2,000) and had a hard time getting support that took days to reply, when it did reply at all. And when the person replied they had nothing to do with the account label process, so weren't able to help, which was quite frustrating. It was fine since this was a little side project, but if this was a business at scale and I was paying that much in addition to ad spend I'd be furious.

Anyway, I know nothing about the Head of Eng or what's at the root of these issues, but I'm a big fan of X and hope they're able to fix these things. It's such. valuable tool. I'm even fine if it's pay to play, but if someone is on the higher tiers of your paid plans the support should be available when they need it.

Yes, much better. ChatGPT/Claude/etc. are useful the times I want extra explanation to help connect the dots, but Math Academy incorporates spaced repetition, interleaving, etc. the way a dedicated tutor would, but in a better structured environment/UI.

Their marketing website leaves a lot to be desired (a perk since they are all math nerds focused on the product), but here are two references on their site that explain their approach:

- https://mathacademy.com/how-it-works

- https://mathacademy.com/pedagogy

They also did a really good interview last week that goes in depth about their process with Dr. Alex Smith (Director of Curriculum) and Justin Skycak (Director of Analytics) from Math Academy: https://chalkandtalkpodcast.podbean.com/e/math-academy-optim...

Good luck! You should check out Math Academy, it's more effective/efficient/cheaper but also a good supplement since it's accredited.

I recently turned 40 myself and I'm working through their Foundations courses (made to help adults catch up) before tackling the Machine Learning and other uni courses.

Have you tried Math Academy? I think the difference is that it's actually made by a team of mathematicians creating the content manually.

Yes, Math Academy is insanely good. It's a lot more intense, focused learning and less edutainment.

I'm an adult and not a kid, but wrote about my experience after 100 days of using it daily here: https://gmays.com/math

The Math Academy team (including the founders) are also active on X/Twitter: https://x.com/_MathAcademy_

And there's a Math Academy community on X here in case you want opinions from other users: https://x.com/i/communities/1833198423593431339

The hard thing is that it's both a bubble and not.

It's a bubble in the respect that the hype around integrating into existing companies/software is likely often falling flat.

It may not be a bubble in that all of the best/useful/valuable use cases of AI are in new software, which have yet to prove themselves in the enterprise. This makes sense because you can't just bolt it onto existing software/organizations and expect it to work because they're built around the way things used to be, similar how when factories first tried to integrate electricity.

For example, I'm sure Palantir is doing some good stuff, but I just have doubts about how useful AI can be in the context of existing companies. And their valuation seems insane, which screams bubble, especially since they're an older companies and less 'AI-native' than the newer ones, like the clunky ways Salesforce and Microsoft implement AI.

But do I expect startups to continue to emerge that approach problems in AI-native ways that help companies reorganize? Yes, it's just a question about how long it takes these companies to work their way into the enterprise and earn enough credibility to drive organizational change and restructuring.

The 'bubble' question is really about whether this latent/potential productivity will be enough to inflate the bubble before it bursts.

My money is on yes, but rather than picking a winner at the app layer and trying to win the lottery I'm heavily invested in the boring stuff like chips (NVDA) and those building data centers with low P/Es (back when I bought them), thus a lot of room to grow even conservatively.

Comparing AI to crypto doesn't really work due to the utility of AI. If you believe that there haven't been meaningful use cases from the recent generative AI surge, then you might be out of touch.

On the investment side, it's hard to say that since ROIC is still generally up and to the right. As long as that continues, so will investment.

Then biggest gap I see is expected if you look at past trends like mobile and the internet: In the first wave of new tech there's a lot of trying to do the old things in the new way, which often fails or gives incremental improvements at best.

This is why the 'new' companies seem to be doing the best. I've been shocked at so many new AI startups generating millions in revenue so quickly (billions with OpenAI, but that's a special case). It's because they're not shackled to past products, business models, etc.

However, there are plenty of enterprise companies trying to integrate AI into existing workflows and failing miserably. Just like when they tried to retrofit factories with electricity. It's not just plug and play in most cases, you need new workflows, etc. That will take years and there will be plenty more failures.

The level of investment is staggering though, and might we see a crash at some point? Maybe, but likely not for a while since there's still so much white space. The hardest thing with new technologies like this is not to confuse the limits of our imagination with the limits of reality (and that goes both ways).

Awesome improvements. How does this compare to Braintrust? I've played with it a bit and we're gearing up to implement a solution in during the Christmas lull.

We use various LLMs as a core part of our app but I'm looking for ways to more quickly iterate on our prompts, test different LLM outputs against each other, etc. ideally while minimizing deploys. Would Langfuse serve that purpose?

I guess it's individual. My wife flew F-18's for the Marine Corps and is chronically late for everything! So much for on time, on target.

Real estate can be speculative as well. A better way to state that might be "things outside of productive assets and services" are increasingly speculative.

The bright side of this that has me excited is what seems to be a growing sense of optimism about the future, driven by AI entering the public conscious, Space X's "rocket catch" etc. There seems to be a growing belief that the future can and will be better, more so than a decade ago.

I've been using Math Academy daily for over a year now and have been similarly impressed with how much I'm learning with it.

Congrats on your pace, 9k XP in 9 weeks is impressive!

+1 for Math Academy. I’ve been using it daily for over a year now (started October 2023). I summarized my experiences after 100 days here in case it helps anyone: https://gmays.com/math

Good analysis. One correction though, EmailOctopus does offer auto-plan downgrades. Screenshot of the billing page on our account: https://share.cleanshot.com/VJdQPrjP

After trying a few also we ended up with EmailOctopus because of simplicity (we only send plain text emails) and cost. The trick was using their Connect [1] plans so it could send via our AWS account, which is cheaper (we pay $30/mo for the 10,0000 subscriber plan).

I also tried Loops and wanted to love it since they're perfect for SaaS companies, but back when I tried them we just got a ton of spam subscribers since they didn't have any built-in mitigation, so our list (and cost) grew.

But that was in their very early days, so I assume they've resolved it by now and I'd like to try them again at some point since they're much more modern and purpose-built for SaaS (and a YC company).

[1] https://help.emailoctopus.com/article/161-what-is-emailoctop...

"In times of great uncertainty, the relative value of "playing it safe" is reduced, since - for better or for worse - no option can now reduce risk to truly safe levels. And so, paradoxically, in times of risk and uncertainty, it can actually become more rational to think and act more boldly - or more precisely, to bring one's personal risk tolerance to match the amount of external risk present in the system."

https://archive.is/AushK

I've had a similar experience. I've now done math with Math Academy for 349 days in a row as of today. I'm not going as fast as I'd like due to other higher priorities like my kids and my startup, but Math Academy helps me make the most of the time I do have. I highly recommend it.

I also documented my experiences when I hit the 100 day streak mark here: gmays.com/math

It’s been great for me. As of today I crossed 324 days of using it straight. I wrote about my experience here: https://gmays.com/math

And yes, I’m a total fanboy. I’ve also known the founder for over a decade and he’s been working on it for most of that time. Math Academy came out of him helping his son learn math even before that.

I haven’t found anything close to teaching math than this. It’s legit.