Chevngko.dev

21/04/2025

This post is dedicated to every dev who thought ‘Let’s deploy real quick’ and lived to regret it.



🧠 Powered by: CoreframeAI™ · Build Agents That Think in Loops

14/04/2025

Not everything that breaks is a bug.
Sometimes, it’s a blueprint in disguise.

I’ve spent years inside computer vision pipelines — seeing where labeling workflows break, where feedback gets lost, and where the system fails the builder.

That friction didn’t make me quit.
It made me design a system.

That’s why I created CoreframeAI — not another platform, but a modular architecture to turn research into working agents.

If you’ve ever thought “there has to be a better way to build this”… this might be the system you're looking for.

💡 Read the full log: https://medium.com//founder-log-1-the-week-i-realized-vision-models-can-think-b62e6bdb1385
🔗 More at coreframeai.com

— Chevngko · Founder of CoreframeAI

12/04/2025

Saturdays remind me why I got into AI building in the first place:

Curiosity. Coffee. Code.
Not everything is urgent—some days you just learn at your own pace.

Who else uses weekends to gently nudge their projects forward?

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11/04/2025

You’re really missing out if you’re not using AI to improve your workflow.

I don’t mean replacing what you do.
I mean speeding up the parts that slow you down:
→ Debugging
→ Note sorting
→ Idea structuring
→ Research overload

AI doesn’t take the work away.
It takes the waste away.

And if you’re building anything — code, content, strategy — you owe it to yourself to try it for a week.

I made the switch. Now I can’t imagine working without it.

💬 What’s one task you wish AI could take off your plate right now?

11/04/2025

Let’s be real — before I started using LLMs in my workflow, coding felt like a constant state of CTRL+Z.

Endless bugs. Mental fatigue. Tabs on tabs of Stack Overflow.
I wasn’t learning. I was firefighting.

When I started using LLMs not just for Q&A, but as a thinking partner, the game changed:

⚙️ Faster prototype cycles
📈 Smarter prompts = clearer outputs
🔁 Tighter feedback loops that kept me in flow

But here’s the deeper shift no one’s talking about:

🧠 LLMs are evolving faster than our habits.
And with the new Ironwood TPUs from Google Cloud, we’re entering the Age of Inference:

🔹 Real-time responses, not minutes of latency
🔹 Cost-effective scaling — even for indie devs
🔹 Model deployment at speeds that match user expectations

It’s not about training bigger models anymore.
It’s about making smart ones available, fast, and cheap.

The next wave of LLM-powered apps will come from builders who see infrastructure not as “someone else’s job” — but as a creative lever.

I’m adapting my workflow. Are you?

Full article here (🔥 read):
https://blog.google/products/google-cloud/ironwood-tpu-age-of-inference/

We’re introducing Ironwood, our seventh-generation Tensor Processing Unit (TPU) designed to power the age of generative AI inference.

10/04/2025

After hours of coding, take a walk.

10/04/2025

🚨 New Page. New Energy. Let's Build.

Hey there 👋 Welcome to this space where we build with AI, learn in public, and share ideas that turn procrastination into ex*****on.

This isn’t just another tech page.
It’s a space for:
✅ Small, consistent projects
✅ Big shifts in mindset
✅ Showing up — even when it’s messy

Whether you’re an ML beginner, indie hacker, or just AI-curious, there’s something here for you.

💡 Let’s grow together — one idea, one post, one repo at a time.

Hit “Follow” if you're ready to stop scrolling and start building.