Khalid, The Engine

@kiishigod Welcome back

Been building this AI harness for a while now, I think it holds its own against the greats. But it has choked my finances and I need help to actually push it out. I. think I'm on to something. You can try it out. ite.kiishi.space

The compiler is not sacred. The debugger is not sacred. Build your own.

Hands-on Rust exercises and projects guide github.com/sunface/rust-b…

We launched the "Build your own GPT" from scratch project on NeetCode - inspired by @karpathy 's Lets build GPT series Some reasons you should check it out: - it's beginner friendly / no ML background required - solve 36 real ML problems, learning math, NLP, pytorch, transformers & more - each of your solutions is a .py file - after you solve all problems, you will have built a working GPT clone you can run locally - automatically sync your solutions to github as you progress - a lot of other really cool features, like some problems are inspired by research papers, so for these we embedded the actual paper pdfs and highlighted the important sections, so you dont need to keep opening new tabs TLDR: Learn ML. Build a real project. Show off your work. All 100% free.

most people don’t know the difference between MCP and agentic skills. this 20mins course teaches you everything you need to know. it’s free on YT. bookmark. watch. at the end of the video course, you’d have learnt what the differences and similarities between agents skill and MCP. and the best part when to use which. this is just the first 12mins, check the cs for link to the full video.

+1 Happy birthday Faizah❤️

Entire 1-hour Quant Finance workshop by a Two-Sigma AI Engineer:

Finally, after a lot of procrastination, I’ve started this Distributed Systems playlist. The playlist consists of 20 videos, and I’ve just finished Lecture 1: Introduction. Here are some points from the first video: >Explained the basic requirements of an infrastructure >Discussed achieving abstraction in infrastructure >Covered the impact of scalability on performance >Introduced key aspects of fault tolerance (availability, recoverability, consistency) >Gave a high level overview of MapReduce and how it works The video wasn’t very detailed, but the playlist looks promising.

Two Anthropic engineers spent 24 minutes exposing every Claude Code feature you didn't know existed. Most people will scroll past this. Don't be most people.

@_hashcode @SemudaraAbayomi Heavy on that QA boss man 😂 I pity her when she doesn't tesr for loads of edge cases

The person is not serious, should only take 2 days build the entire business. 2 hours for the user UI, 6 hours for payments, 1 hour for the merchant UI, 3 hours for back office UI, all the backend services should take max 6 hours, no QA cos it should just work since it’s AI, what is security? Business models implementations should take 25 minutes. Merchant onboarding is easy just do summoning jutsu and they all appear. Follow me for more tips🙂‍↕️🙂‍↕️🙂‍↔️

Some 9ja tech bros wants to build Jumia in two weeks…

Open-source local AWS emulator with real databases github.com/ministackorg/m…

在 GitHub 上挖到一门很实用的开源课：Learn Harness Engineering，专门教你给 AI 编程助手搭一套更可靠的“工作台”。 它把 AI 协作拆成五个关键机制：指令、状态、验证、范围、会话，让每次任务都可追踪、可续接、可验证，不再靠运气出结果。 GitHub：github.com/walkinglabs/le… 官网：walkinglabs.github.io/learn-harness-… 课程结构很清晰：12 节理论 + 6 个实战项目，用同一个桌面应用贯穿推进，边做边演进。 从最基础的对比实验起步，逐步把整套工作环境搭起来；每个项目的产出，直接接到下一个项目继续用，越做越稳。 更贴心的是，它还提供可直接复用的模板文件：拷进自己的项目就能上手，不用完整学完，也能立刻提升 AI 的稳定性和可控性。 如果你已经在用 Claude Code 或 Codex 做真实开发，却总觉得 AI 时好时坏、难以复现，这门课很值得花时间看看。

@_hashcode @the_morowooluwa @0xSaint_ The queues are very long and the school isnt even batting an eye about helping thee situation and the next thing is to send us all home

@the_morowooluwa @0xSaint_ Jesus Christ

Can someone please give me a rundown of what’s going on with transportation inside OAU?

Anthropic pays engineers $750,000+ a year to understand how LLMs work. Stanford just put a 2 hour lecture that covers 80% of it for FREE. Bookmark this. Give it 2 hours today.

free-claude-code (Free & Open Source) github.com/Alishahryar1/f…

Ten years ago, we set out to build something that would alter the way a generation thinks about saving and investing money. Today, over 6 million people have responded with their trust. They’ve built in discipline and consistency. In quiet moments, they’ve written goals that read like letters to their future selves. What started as a simple product has evolved into culture and a part of our everyday lives. The first-ever Piggyvest documentary is now live on YouTube 💙 youtu.be/ccuqOm2k0j4?si…

There are 2 career paths in AI right now: The API Caller: Knows how to use an API. (Low leverage, first to be automated, $150k salary). The Architect: Knows how to build the API. (High leverage, builds the tools, $500k+ salary). Bootcamps train you to be an API Caller. This free 17-video Stanford course trains you to be an Architect. It's CS336: Language Modeling from Scratch. The syllabus is pure signal, no noise:  ➡️ Data Collection & Curation (Lec 13-14) ➡️ Building Transformers & MoE (Lec 3-4) ➡️ Making it fast (Lec 5-8: GPUs, Kernels, Parallelism) ➡️ Making it work (Lec 10: Inference) ➡️ Making it smart (Lec 15-17: Alignment & RL) Choose your path. (I will put the playlist in the comments.) ♻️ Repost to save someone $$$ and a lot of confusion. ✔️ You can follow @techNmak, for more insights.

@iadorekior What do u mean yall speak African smh

Why is no one talking about this? @nvidia is offering around 80 AI models via hosted APIs absolutely for free. You get access to MiniMax M2.7, GLM 5.1, Kimi 2.5, DeepSeek 3.2, GPT-OSS-120B, Sarvam-M etc. This plugs straight into OpenClaude, OpenCode, Zed IDE, Hermes agent and even with Cursor IDE. Setup: – Grab API key: build.nvidia.com/models – base_url = "integrate.api.nvidia.com/v1" – api_key = "$NVIDIA_API_KEY" – select model (e.g. minimaxai/minimax-m2.7) If you’re building or experimenting, this is basically free inference. Lock in and start building today anon. Thank me later.