Some guy on Reddit just handed out a 12-week plan to break into quant finance for free.
He went from bombing mock interviews alone in his bedroom to 3 offers in a single month.
Then he wrote down every single step that got him there:
> Weeks 1-3: foundation - probability, mental math, easy coding
> Weeks 4-7: second pass on everything, start applying before you feel ready
> Weeks 8-10: mock interviews until they stop humiliating you
> Weeks 11-12: don't cram, just sleep and stay sharp
Ex-NVIDIA engineer who built Unsloth explained RL, kernels, reasoning, quantization, and agents in 2 hours 42 minutes - better than $5000 fine-tuning bootcamps.
pick the base model -> write triton kernels for 2x faster fine-tune -> quantize to 4-bit -> run GRPO/DPO -> ship a reasoning model on your single GPU.
That loop is why Unsloth is the default way to fine-tune Llama, Qwen, Gemma, and Phi on hardware you already own.
Unsloth + Triton kernels + 4-bit quantization + GRPO/DPO + single-GPU fine-tuning - that's the stack.
Watch and save it, then fine-tune your first model tonight.
My friend applied to 200 tech jobs in two years. No PhD. No Stanford.
Last month Anthropic offered him $750,000.
I asked him how he broke in from zero.
He sent me a course that was never supposed to get out. A 3-hour video to build a full LLM from scratch.
A developer teaches you exactly how LLMs like ChatGPT and Claude are actually built.
I watched it last night.
Halfway through, I realized it's embarrassingly simple to break into an AI lab.
Bookmark this and read the article below.
• 00:00 - intro to LLMs
• 05:43 - LLM transformer architecture
• 40:24 - training the LLM
• 1:30:27 - modernizing the LLM
• 2:33:53 - scaling the LLM
Andrew Ng just dropped a 3-hour course on how to become an AI Engineer in 2026:
• 00:00 - How to build agentic AI systems
• 04:25 - Future of AI engineering
• 23:38 - AI Prompting full course
• 2:52:17 - Creating an app with AI in 30 minutes
This 3-hour watch could replace 10 AI engineering courses on the internet.
Watch it today, then read how to run a self-improving system in the article below.
If you look closely at this bus, the heaviest hitters are already on board. @Harri_obi, @NzubeEzudo, @Goddesswriter1, and more.
The only question left is, why are you still standing at the bus stop?
We aren’t just traveling for the vibes, we’re moving as a collective to the Solana Summit Nigeria 2026. The builders are ready, the tech is cooking, and the entire ecosystem is converging in Akwa Ibom.
Don't get left behind in the Web2 dust.
Secure your seat right now.
The registration link is in the comments!
My friend makes $1.2 million a year as an Anthropic engineer.
I asked him how he learned prompting so well.
He sent me a video that was never supposed to get out. Their core team's prompting playbook.
You won’t find anything better about prompting than this video.
I watched it last night.
Halfway through, I realized I've been using Claude completely wrong for two years.
Watch it, then read the article below.
🚨 A SENIOR ANTHROPIC ENGINEER JUST DROPPED AN 11-PAGE PDF ON LOOP ENGINEERING.
The core shift: stop prompting the agent. Build the system that prompts it.
Inside the autonomous loop:
- Discover → Finds its own work (failing CI, open issues).
- Isolate → Uses separate git worktrees to prevent collisions.
- Verify → A second agent reviews the work. (Never let agents self-grade).
- Persist → Writes to disk, not temporary context windows.
- Schedule → Runs automatically on a timer.
This is a great framework for building more reliable agentic systems
link to the guide below.
Read it, then check out this ace article on Loop Engineering by @akshay_pachaar 👇
Google just dropped a free 8-minute lesson on building your first AI agent.
This is the clearest explanation of AI agents and loops you'll find anywhere.
People are paying $500 for courses that teach less than this.
Watch it, then read the step by step guide on building loops for your agents below.
PS: On their career page at https://t.co/XykWZ3uicy
There's also opening for:
- Fullstack Engineer
- Data scientist
- AI consultant
- Full stack developer
- Devops Engineer
AINinza is hiring AI/ML engineers with Flutter Experience
If you've shipped Flutter apps that actually run in production, you already understand half the AI engineering job. Both worlds care about the same things:
- Code that survives real users, not demo environments.
- Latency that matters.
- State management across complex flows.
- Failure modes that only surface at scale.
- Working with stakeholders who care about outcomes, not architecture diagrams.
- What AINinza is hiring for:
LLM Engineers. Orchestration, prompt engineering, eval harness design, production observability.
RAG Architects. Hybrid search, document parsing, citation handling, schema design for retrieval.
Voice AI Engineers. TTS, ASR, multi-turn voice flows, latency optimization, telephony integration.
- What you get:
Real production AI work, not LLM demos or toy prototypes.
Backed by 10+ years of Aeologic enterprise engineering.
Ship in 4 to 8 week project cycles, not 18-month transformations.
Aeologic compensation and benefits.
If this is you, apply directly: https://t.co/GSbowwgvqJ
Yesterday, from Lagos to Uyo, Enugu to Bauchi, members across 30 states came together to celebrate @SuperteamNG @ 3 🎂
Every cake represents a local community, friendships formed, careers launched, products built, and people who chose to show up and build something bigger than themselves.
Three years of building.
Three years of opportunities.
Three years of proving that world-class talent exists in Africa.
Grateful to everyone who has been part of this journey.
@SuperteamNG is home.
Connecting with Nasarawa community, yesterday was an impact celebration of Nigeria’s best crypto community.
SuperteamNG changed the story for many of us, became a learning hub, career guide, and place to earn while building on @solana
Happy 3rd Anniversary