Reminder.dev - Quran app and API that includes RAG search to provide a more authenticated source of summarisation. The first thing I dabbled in with AI.
Micro.mu - Rebuilt my entire product idea from 10 years ago as a super app for daily digital habits. Something I use everyday for myself.
Aslam.org - An islamic knowledge base that uses sources of data as a way to ground AI chat and make notes. Very useful tool that I'm using on a daily basis.
Go-micro.dev - Totally revamped the open source project, docs, etc with Claude.
Micro.mu looks interesting, your description of daily digital habits made me think it was a productivity app, when it really is more of a dashboard for different channels of content on the internet (social, video, chat, etc.) what was your original vision? I am curios. Also I really like the design, its so clean, Ive never seen anything quite like it and yet it seems like such a good aesthetic that should have been obvious. kuddos.
Originally I felt there should be an alternative to Google and Facebook. It felt like our lives were being ruled by tech giants even ten years ago..and then all the advertising and algorithms really messed with us. I personally wanted an alternative way to use the web. So it's based around what I'd use on a daily basis. And then the idea of being able to extend it with a native app builder. The big stuff I continue to build with Go but ad-hoc things I can knock out with some JS in the app itself.
I think there's a lot that doesn't get built initially especially around error management and more feature completeness around how the response will be shaped. I think it's an interesting demonstration in how to leverage an existing system of services for AI but definitely more to do. Thanks for asking.
Edit: One other thing I kept out was code generation — the agent can call services but doesn't create them. I've just built it: `micro run --prompt "a task management system"` generates real services, builds them, starts them, and the agent can use them immediately. The agent can build new services on the fly.
We are now entering the closed loop game. Google doesn't need anyone else to accelerate their models. This is their bread and butter.
I'm both shocked but also not surprised that they continue to develop such efficiencies. Honestly it's like silicon and CPU architecture advancement. We kept shrinking it and shrinking it and it kept getting more and more powerful and here we are with AI and it's only going to be 100x more efficient with time. Maybe there's some point of decay but essentially the next 30 years will be more advanced than the last 30 and were going to be living in some sort of futurist blade runner scenario where gene editing is repairing ageing cells, organs and curing all sorts of cancers that haven't even appeared yet. Beyond our lifetimes people will live to 125 quite steadily and with great mobility and then obviously people will look to how do we get to living 1000 years, which of anyone is religious knows Noah and others lived to that age in a totally different era.
Anyway I'm going off on some tangent but look back 30 years. Now look forward 30 years. It's going to be insane. May God protect us.
> We kept shrinking it and shrinking it and it kept getting more and more powerful and here we are with AI and it's only going to be 100x more efficient with time.
It's definitely an exciting time, but in terms of advancements in the state of the art, there is a lot of low-hanging fruit left to pick. There IS a bottom, however, as you can only encode so much "knowledge" in a small number of parameters.
This feels to me a lot like what the early days of what radio or aviation must have been like. Or, heck, microcomputers even.
It's definitely a core component of a bigger system. We are effectively trying to recreate intelligence and human life through models and robotics. So the key insights for me, the LLM is the cerebral cortex but we have a lot more to recreate. Once you map in sensory input continuously and give it physical robotics, things start to change. But even before that leaving these things in simulated realities is what will happen, and right now we have things that operate based on our commands, but a complete step function will be the things that act on their own and that will be a very dangerous time but also where we see some very surreal things happening. They might not necessarily be made in the same way either, they might operate on entirely different types of architecture.
1996 didn't look that different than today, in the US anyway. Biggest difference, besides the electric cars, is everybody has a phone but nobody uses it to talk to people.
I agree the last 30 years in the U.S. hasn't changed all that much due to tech.
It's probably true that phones and social networks have altered the way people think, but not necessarily in a way that's qualitatively different from cable TV changing the way people in the 90s thought compared to people in the 60s...
Yes I've taken the "must optimise longevity" route, taking priority over other things such as my career and hobbies. I want to see the future - all this AI stuff fascinates me.
Today, data systems and algorithms can be deployed at unprecedented scale and speed. Unintended consequences will affect people with that same scale and speed
Only after the current generation(s) of doctor(s) dies. And only if you make this in pill-form. Otherwise people will be people and won't even go to the gym.
It might be also the reverse, they develop a powerful+personalized drug that brings heaven on earth to your neurons (first time heroin experience + sexual gratification + childhood fulfillment + extremely addicting etc etc etc).
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Now that I think of it I'm gonna go with the latter.
> Beyond our lifetimes people will live to 125 quite steadily and with great mobility
Possibly, but it'll take a lot of bioengineering. It looks like our metabolic processes really tap out at 120, so we'll need some way to maintain better biological condition body-wide at earlier ages so we're "younger" for longer. Definitely possible though, just hard.
Seems like they’re trying to put open ai, anthropic, grok out of business by releasing their open source models, as google actually has massive profitable arms of their business outside ai, and be there to scoop up any remaining demand for huge models run in the cloud as a monopoly of sorts.
> which of anyone is religious knows Noah and others lived to that age in a totally different era
My favourite conspiracy theory lately is that the above isn't a silly fairy tale, that we actually used to live much much longer -- until the common cold came on the scene, and the sequelae dramatically shortened our lifespans. Today we dismiss it as "just a cold" unbeknownst of what it robbed us from.
Large models still are quite far ahead, don't be fooled that even Gemma:31b (which is better than the 12b overall) is anywhere close to big models.
There is definitely room for optimization, but fundamentally, for complex tasks, you need visible small gradients for accuracy that allow the model to be trained on (and consequently be followed during inference). For example, if you specify in instructions not to write code but ask coding question, Gemma will still write code. Whereas Gemini/Claude will pick up on that and follow your instructions better.
It doesn't matter if Large models are undeniably better, if a local model is "good enough" to handle the task. With API costs ramping up, I think a lot of companies are going to want to look into what can be run locally instead, possibly only using larger models when the local models fall short.
Love how everyone boasted about replacing all the software with ChatGPT and then we end up with coding agents meaning the software engineer are STILL important. The sell is the development tool. It's classic cloud. Where did all the ops people go, many got subsumed by the cloud companies YET every company still has DevOps people to manage cloud infrastructure. The layer of abstraction went up but we still need the people to write the glue code and understand the business. OK great there's a new cash printer in the room. There's a new tool. Let's just start to ground the tooling in its new found gravity, profitability and IPO market dynamics... Reality has set in. The hype cycle is about to explode... Do you remember ride hailing and just how much cash was burned on credits pre Uber IPO. Then remember the IPO itself? These companies are not the new Google. They are a layer on top. Google was still the most efficient cash printing machine in history beyond the the US government and might still be. Will be interesting to see what the trillion dollar IPOs turn into. I'm going to say we see those prices get cut to a third in less than 5 years and scale back up over the next 15-20 years.
I've been calling that out for a couple years now. LLMs best and most viable use case is still just as a dev tool. Even for non-programming tasks, I still get better results from the LLM if I instruct it to write code to do the task...look at Claude Cowork for example, it's everything I used to do with python myself. It's not really a novel capability, it's just using python & bash for automations that any sysadmin has been doing for decades. Yeah, that's valuable for a non-techincal audience but is it $1T valuable? I don't think so.
When has an IDE or other dev tool ever commanded a $1T valuation?
These things get lost in discussions because people conflate "overvalued" with "not useful." LLMs are useful, particularly as dev tool, but Anthropic & OpenAI are definitely way overvalued.
Every so often there is a trend and a hype cycle. It eventually dissipates. There's value in what gets built but it also becomes the silver bullet or the hammer used for everything. In 2-3 years it's going to die off, it becomes the norm technology trend but it's also part of a larger suite of foundational tooling, meaning so much of it is going to fade into the background and we're going to get back to good old problem solving. Doesn't mean we shouldn't learn and understand but yes we're all going to get burned out on AI chatter.
Good for them. We built similar tooling at that time, but backed by our own APIs. It's something that has a lot of value, that standardisation needs to exist, but it also makes a lot of sense to fold the team into a company like Anthropic that is so developer centric. Good luck to the team there.
The same thing for 10 years and every couple years it gets reimagined while trying to get to the original goal of building a replacement for Google. It's called Micro.
Ah man the VC death trap. It's ok. I don't mean it like that but this is classic. It's unavoidable. They gotta make money. They took money, they gotta make money. It's not easy. Everyone has principles, developers more than anyone. They are developers, they are people like you and me. They didn't even start as ollama. They started as a kubernetes infra project in YC and pivoted. Listen don't be hard on these guys. It's hard enough. Trust me I did it. And not as well them.
This is the game. We shouldn't delude ourselves into thinking there are alternative ways to become profitable around open source, there aren't. You effectively end up in this trap and there's no escape and then you have to compromise on everything to build the company, return the money, make a profit. You took people's money, now you have to make good, there's no choice. And anyone who thinks differently is deluded. Open source only goes one way. To the enterprise. Everything else is burning money and wasting time. Look at Docker. Textbook example of the enormous struggle to capture the value of a project that had so much potential, defined an industry and ultimately failed. Even the reboot failed. Sorry. It did.
This stuff is messy. Give them some credit. They give you an epic open source project. Be grateful for that. And now if you want to move on, move on. They don't need a hard time. They're already having a hard time. These guys are probably sweating bullets trying to make it work while their investors breathe down their necks waiting for the payoff. Let them breathe.
> This stuff is messy. Give them some credit. They give you an epic open source project.
It seems to me the epic open source project was given to us by Georgi Gerganov. These people just tried to milk it for some money, and made everything a little worse in the process.
Especially when the solid core now ships with a web ui and API compatibility with OpenAI and Antropic. In my test of ai clients, Ollama was the only one I deleted.
I don't know why in 2026 I'm still surprised CLIs are taking off. But here's the difference today. It's for real world end user platforms like WhatsApp and Claude. That's the difference. Previously it was only Dev and infrastructure focused. Today we're saying you know what, I need programmatic access to this real world thing. It's fascinating because I rarely open my laptop now or try not to.
Reminder.dev - Quran app and API that includes RAG search to provide a more authenticated source of summarisation. The first thing I dabbled in with AI.
Micro.mu - Rebuilt my entire product idea from 10 years ago as a super app for daily digital habits. Something I use everyday for myself.
Aslam.org - An islamic knowledge base that uses sources of data as a way to ground AI chat and make notes. Very useful tool that I'm using on a daily basis.
Go-micro.dev - Totally revamped the open source project, docs, etc with Claude.
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