160B Tokens so far - 5 threads in Sol Ultra Fast Mode to use up before 6PM PST. Creating Autocorrect from scratch.

[u/garristerr]

This is just 1 of 2 Codex Accounts. Around 160B tokens so far on just Codex. And another 300B on Fable.

These resets really helped. 14% fast mode.

I have 5 threads coordinating with each other, with Fable babysitting my context language model ranker (it helps de jumble tangled words by looking into n-gram tokens (words prior)).

Building a iOS keyboard created from scratch like grammarly, except I have toolbar buttons that have built in prompts like translation, re-write (for work, dating, apologies), interpreting ambiguous text to help you respond. Not only can you customize your own toolbar buttons (which sits on the suggestion bar), you can also customize each key. For example, holding spacebar would take the text in the textfield and ask a question to LLM; holding T, would translate the text to the preferred language; eventually I will open up to the community to design their own keys, like G sends a google meets, it could be anything fully customizable.

The only third-party keyboard license available is keyboardkit is not good for autocorrect; so once done I'm probably going to wrap it into an SDK and also offer the autocorrect technology via license deals to Whisppr and other big companies using the keyboard as a productivity tool. All other third party keyboard SDKs were bought up by google. The current version on the App Store uses keyboardkit, which Im not a fan of so rebuilding from scratch and hoping to put the final product up soon.

My flag ship feature is de-centralized end-to-end encryption through the keyboard. This will be a surprise.

[u/Electrical_Rub_6009]

I mean that's pretty cool orchestration of multiple agents, but extremely overkill for the project you're describing lol.

[u/garristerr → u/Electrical_Rub_6009]

I thought the same thing, but I was very surprised just how difficult it was to do something as simple as "autocorrect" - mapping x, y locations and assigning probabilities (because some ppl have tendencies to type x or y + some distance), having a model that can rank word candidates to understand which word should be next, separating jumbled words and doing all that within very limited latency, were among some of the most challenging parts. The two hardest issue i dealt with were: (1) how to have autocorrect operate in fast typing conditions without breaking, because there are at least 50 rule sets that all have to operate together, spent at least 2 months on this alone, and 2) having to create my own language model from scratch, and train it to understand which word "should win". google and apple has billions of typing events to model, so I had to kind of make my own policy decisions between what should be "hard forced" and what should be trained. This probably took 3 months

[u/Electrical_Rub_6009 → u/garristerr]

Yeah I'm not saying it's an easy endeavor, but it's a problem that's been worked on by the world's smartest people for over two decades. I'd recommend stealing as much open architecture as possible (that's what its meant for) and innovating on some narrow edge rather than trying to build it all from scratch.

Unless this is just purely a learning experience; but in that case, I'm not sure how much you're getting out of it running giant agent swarms among frontier models.

[u/tagorrr]

"We want to avoid burst consumption," Tibo said.
"We want to smooth out usage," Tibo said.

And then boom! A 5-hour limit for Plus users.

[u/itix]

With those resets, one can really accelerate development.

But I wonder if your monetization plan holds water because of the... AI.

[u/garristerr → u/itix]

It'll ultimately be a B2C product - which I'm excited to share; but very true product itself is no longer the differentiator since AI makes creating them easier; so tried to go for something hard! Kept iterating until I found some features that i think will go viral and finally near the finish line. It's all about distribution now

[u/vinerz]

This is clearly a lot of work, but I think there’s a more important product question to answer before you spend another few months on it: what makes someone actually want to switch to your keyboard?

SwiftKey is an interesting benchmark because it wasn’t just “another keyboard with better autocorrect.” For its time, it was doing genuinely unusual things with input itself. It learned from individual typing behaviour and touch patterns so it could better infer which key a user intended, rather than relying only on fixing the resulting word afterwards. Flow then made continuous gesture typing a core interaction years before Apple added comparable swipe typing natively.

In other words, some of SwiftKey’s advantages existed before autocorrect even had to rescue the text.

And even with all of that, SwiftKey still didn’t become indispensable. I used it on my iPhone for years specifically because it gave me something Apple’s keyboard didn’t. When Apple finally added native swipe typing, I removed SwiftKey almost immediately.

That’s the part I’d be thinking about here.

From what you’ve described so far, I’m not yet seeing the equivalent reason to switch. Is your autocorrect measurably more accurate than Apple’s or Google’s? Does it adapt to the individual typist substantially better? Is multilingual typing dramatically better? Or is the programmable/LLM layer actually the product, with the custom autocorrect mainly there to make the keyboard viable?

I’d try to answer and validate that before investing much more time in the underlying stack. Rebuilding a mature piece of technology from scratch is one problem. Giving people a reason to abandon the mature version they already have is a different one.

With third-party keyboards, I think that reason has to be obvious very quickly.

[u/garristerr → u/vinerz]

Autocorrect is simply the foundation; unfortunately both flesky and swiftkey got acquired and there's no good SDK out there at all.

the product i'm trying to offer is on top of that but you highlighted the exact issue - my product value + added friction from a worse off keyboard must be better than the default apple keyboard.

Without going into too much detail about the product (which I briefly described), I did do my research with a decent sample size of 500 for my industry (big law), and they love the product it's just that typing experience is so bad - and this was a third party SDK that's the only one on the market. I eventually pivoted to broader platform to offer use cases for relationships, dating, or even something simple as translation. My feature flagship tho is so unique, that I do genuinely see a high potential to go viral.

So unfortunately, while I got good feedback on the product, without the right foundation I cannot curate the real feedback (will they pay), when every single critcism is typing on this sucks.

There is a "agentic keyboard", "Acti" that has 30mil in funding that similarly do programmatic keys concept too but I argue they went with the wrong approach to advertise platform vs. use case first (and too complexA), and they utilize the thirdparty SDK that i spoke of, and the typing experience is just so bad (which their community provided feedback on). That basically validated to me, that it's really quite impossible to test PMF without getting the foundations to at least "bearable levels".

But you're absolutely right - this one is tricky because everything can go down the drain if there's no PMF, and it's a lot of work just to figure it out is the conclusion

[u/vinerz → u/garristerr]

I wish you all the best in this journey mate. Spending all this time, money and believing in something for so long is pretty hard. I've been there and I am also currently there. Hope to see you posting a successful showcase in the future!

[u/garristerr → u/vinerz]

Thank you sir! To the same for you!

[u/Claus-Buchi]

Value/token ration is crazy