Luke

I'll see you fools on April 1st!

There are some tweets out there saying that Granola is trying to lock down access to your data. Tldr; we are actually trying to become more open, not closed. We’re launching a public API next week to complement our MCP. Read on for context. A couple months ago, we noticed that some folks had reversed engineered our local cache so they could access their meeting data. Our cache was not built for this (it can change at any point), so we launched our MCP to serve this need. The MCP gives full access to your notes and transcripts (all time for paid users, time restricted for free users). MCP usage has exploded since launch, so we felt good about it. A week ago, we updated how we store data in our cache and broke the workarounds. This is on us. Stupidly, we thought we had solved these use cases well enough with our MCP. We’ve now learned that while MCPs are great for connecting to tools like Claude or chatGPT, they don’t meet your needs for agents running locally or for data export / pipeline work. So we’re going to fix this for you ASAP. First, we’ll launch a public API next week to make it easier for you to pull your data. Second, we’ll figure out how to make Granola work better for agents running locally. Whether that’s expanding our MCP, launching a CLI, a local API, etc. The industry is moving quickly here, so we’d appreciate your suggestions. We want Granola data to be accessible and useful wherever you need it. Stay tuned.

@uns__nstudio seeeeeesh these are very nice 😮‍💨

Some early visual exploration for a recent brand project 🔬 Kaiko are building AI systems to help medical professionals deliver better care.

🙇 thank you internet tastemakers for the seal of approval

Working at an AI startup is mostly people arguing with laptops

Natural paper motion through sparse physics simulation. 4×4 control points (16 bodies) with spring-damper constraints evaluate to a 64×64 Bezier surface (4,096 vertices). Physics runs on 16 points, rendering on 4,096. Distance constraints maintain rigidity while allowing organic folds. Reusable for cloth, flags, soft materials. 60fps. #threejs #cannonjs #physics #webgl

@samt_granola @mehedih_ best part is that you composed and posted this at 6:30am on a monday

@mehedih_ bro is literally being londonmogged in real time and refusing to lock in 😭 this is a you problem. actually no this is a skill issue. actually no you're just getting mogged. stay mad, seethe, cope, touch grass (we have parks). absolute sigma city no cap on a stack fr fr ong 😤🇬🇧

if i see one more tweet about this im gonna loose my sanity

building with the granola team really made me believe that access to ai can be a leveller. did i come from a traditional cs background? no 🤷‍♀️ but did i ship something meaningful to prod? hell yeah 👍

Is Traditional Software Engineering Dead? “Does this mean that traditional software engineering is dead? Absolutely not. Software engineers—even the ones who are not necessarily tuning or training AI models—these are now among the most leveraged people on earth. Sure, the guys who are training and tuning models are even more leveraged because they’re building the tool set that software engineers are using. But software engineers still have two massive advantages on you. First, they think in code, so they actually know what’s going on underneath. And all abstractions are leaky. So when you have a computer programming for you—when you have Claude Code or equivalent programming for you—it’s going to make mistakes. It’s going to have bugs. It’s going to have suboptimal architecture. So it’s not going to be quite right. And someone who understands what’s going on underneath will be able to plug the leaks as they occur. So if you want to build a well-architected application, if you want to be able to even specify a well-architected application, if you want to be able to make it run at high performance, if you want it to do its best, if you want to catch the bugs early, then you’re going to want to have a software engineering background. The traditional software engineer is going to be able to use these tools much better. And there are still many kinds of problems in software engineering that are out of scope for these AI programs today. The easiest way to think about those is problems that are outside of their data distribution. For example, if they need to do a binary sort or reverse a linked list, they’ve seen countless examples of that, so they’re extremely good at it. But when you start getting out of their domain—where you have to write very high-performance code, when you’re running on architectures that are novel or brand new, when you’re actually creating new things or solving new problems, then you still need to get in there and hand code it. At least until either there are so many of those examples that new models can be trained on them, or until these models can sufficiently reason at even higher levels of abstraction and crack it on their own… And remember: there is no demand for average. The average app—nobody wants it, at least as long as it’s not filling some niche that is filled by a superior app. The app that is better will win essentially a hundred percent of the market. Maybe there’s some small percentage that will bleed off to the second-best app because it does some little niche feature better than the main app, or it’s cheaper, or something of the sort. But generally speaking, people only want the best of anything. So the bad news is there’s no point in being number two or number three—like in the famous Glengarry Glen Ross scene where Alec Baldwin says, “First place gets a Cadillac Eldorado, second place gets a set of steak knives, and third place you’re fired.” That’s absolutely true in these winner-take-all markets. That’s the bad news: You have to be the best at something if you want to win. However, the set of things you can be best at is infinite. You can always find some niche that is perfect for you, and you can be the best at that thing. This goes back to an old tweet of mine where I said, “Become the best in the world at what you do. Keep redefining what you do until this is true.” And I think that still applies in this age of AI.”

This is the quality of the autotrace output I'm getting with img2bez now. I'm not using AI at all to do the tracing. I'm just using AI to write a better autotrace tool than existed before.

Here's some native code magic on how we enabled icon switching in Granola's Electron app granola.ai/blog/so-you-th…

Love prototyping? Designing in the real product? Moving fast and experimenting with new interfaces? Lots of big new things for us to figure out over the next 6 months at Granola, and we're kicking off a search for a designer to come help us build them. The future of Granola is in helping you do the work around meetings, and there's so much to be figured out there. In-person in London, but we'll relocate you if the fit feels good. Reach out if you're curious! granola.ai/jobs/product-d…

This is the kind of interactivity that I live for. Bjørn Staal / ARTXCODE / Fellowship

Hello MCP.

Progress not process. Stay present. Getting the doing done. Granola the notes. Nice work @meetgranola

@_ItsmeJJ_9 Credit to @Ragged_Edge

@lukerohanbailey Great job luke!!

WE REBRANDED!

Another banger! Granola Design Eng nights really are a jewel in the crown of the London scene rn

this the type of shit i've been on recently

Added mipmaps to my WebGPU engine to keep images sharp when I play with layout transitions. Can’t wait to share what’s coming! 📽️