One of the best technical resources I've come across recently is a handbook on engineering software for financial systems by @Krever01 👌🏾👏🏾👏🏾
https://t.co/5CBdfW5S2r
It covers the patterns, principles, and design decisions behind building trustworthy applications that handle money.
If you're breaking into fintech,
Already building financial systems, or Curious about how money software differs from traditional applications, interested in fintech, payments, banking, or digital wallets, it's definitely worth reading.
Highly recommended.
10,000 users!!! 😍🫶
I feel so emotional right now. I honestly can’t believe SportyClaw AI has crossed 10k registered users.
This feels unreal 😭
What started as a simple AI prediction assistant side project has spiralled into an All-in-One betting power tool for thousands of users across Africa 🤯
And honestly, I'm still just getting started.
I’ve shipped code EVERY DAY since launch, constantly improving the product, fixing bugs, and listening closely to users.
With this milestone, I’ve also decided it’s time to rebrand the look of SportyClaw AI 😁
Watch this space.
This is going to be one of the next big products out of Africa 🫡🤞🏻
Still DAY 1.
Back to work 👨🏼🍳
My dear front-end developers (and anyone who’s interested in the future of interfaces):
I have crawled through depths of hell to bring you, for the foreseeable years, one of the more important foundational pieces of UI engineering (if not in implementation then certainly at least in concept):
Fast, accurate and comprehensive userland text measurement algorithm in pure TypeScript, usable for laying out entire web pages without CSS, bypassing DOM measurements and reflow
The guy who helped build React, the most popular workaround for the browser's layout engine, just said the workaround isn't sufficient and built the replacement himself.
Cheng Lou's resume is the context that makes this announcement hit different. He worked on React at Facebook. Created ReasonML and ReScript. Built Messenger's frontend. Now runs Midjourney's entire UI stack on Bun. Every single role was a fight against the same enemy: the browser's rendering pipeline.
Here's why this matters beyond the engineering flex. The web was built to render documents. Static HTML, flowing text, pages you scroll through. CSS layout was designed for that world. Then we started building applications inside the document renderer: spreadsheets, design tools, messaging apps, AI chat interfaces. Every one of those applications has to ask the browser permission to know how big text is. That question triggers reflow. Reflow locks the main thread. At 60fps you get 16 milliseconds per frame. Spend those milliseconds on layout recalculation and the user sees jank.
The industry's answer for the last decade has been to work around the problem. Virtual DOM (React) batches the writes. CSS containment limits the blast radius. content-visibility skips offscreen layout. FastDOM separates reads from writes. Every solution accepts that the browser owns text measurement and tries to call it less often.
Cheng Lou's answer: stop calling it at all. Measure text in pure TypeScript. Skip the DOM. Skip CSS. Skip reflow entirely. Zero layout passes. The performance improvement, per his demo, is categorical. 0.05ms versus 30ms. Zero reflows versus five hundred.
The person who understands the browser rendering pipeline better than almost anyone alive just built the tool that makes part of it unnecessary. That tells you where application-grade UI is heading.
The first time I built my kamusi app around 2018, I got a cease and desist from some publisher firm.
Apparently their app had all the data I needed for my app. It was all in a db file in assets.
Okay years later they fixed their app and data is served from a server and app only works online if am not wrong.
My kamusi app on the other hand uses supabase for its backend and works well offline.
My app is available as SwahiLib on both Android and iOS https://t.co/SYMoDGdw4b
By the way I rewrote my app from Flutter to native: Kotlin and Swift
Here are my Source codes just for those who like to see my mischief, most of it is in clean arch:
FrontEnd (TypeScript + NextJs):
https://t.co/eBtZk7z7jt
Android (Kotlin + JetPack Compose):
https://t.co/hpyVNsx2Fn
iOS (Swift + SwiftUI) :
https://t.co/Ei7wMvVpbC
I think if I had more cash I could do more but all the same
If you are a Kenyan fintech dev tired of relying only on Daraja for STK Push, read this.👇👇
I integrated KCB Buni STK for a KCB merchant.
Before: Single rail. Long approval.
After: Direct bank STK. Faster go live.
Explore it: https://t.co/rJuGSXnpMq
With employment ngumu. Capital leverage, labour leverage , media a& digital leverage , the infinity bucket ( private equity, dividend stocks, real estate & intellectual property) , strategic tax optimisation. Siri ndio iyo. Waezi fundisha hii kwa shule because watakpsa employees/ workers. Shule ni kukufunza uwe worker.
I’m building a VOD pay-per-view platform for short/tiktok style films, with M-Pesa unlocking content instantly — built specifically for the Kenyan market 🇰🇪
Local stories need local monetization infrastructure.
Demo attached 👇
Repost for reach 🔁
rabbitmq is primarily used for queuing durable, long-running jobs.
for example, if you receive 1m reqs to send webhooks to 1m clients, sending those reqs is a blocking operation. you don’t want to overwhelm your servers with that many concurrent tcp connections, so you push the tasks into a queue and let a small number of consumers (say, 3) process them sequentially.
kafka, is lightweight and low-latency, and is typically used for internal service-to-service communication. it’s very good for high-throughput event streaming and real-time communication.
for example, an order service communicating with a payment service and receiving responses via events.
there is some overlap though, people do run queues on kafka and use it for long-running jobs, but that’s not its primary strength.
with rabbitmq, you rarely see two-way real-time communication. that’s because rabbitmq isn’t designed to be lightweight enough for low-latency, bidirectional messaging at scale.
what i'd suggest as general guidance.
pick kafka when:
speed and low latency are important
you’re doing internal service-to-service communication
high throughput matters more than delivery guarantees
use rabbitmq when:
you need to perform the same action for thousands or millions of users.
consistency matters.
speed is not required
reliability is required (at-least-once or exactly-once delivery)
jobs might run for hours or days.