I spent 30 days analyzing Startup.
It's not about automation. It's about augmentation.
Relying 100% on Startup makes you generic.
But using Startup to speed up drafts by 80%?
You win.
How do you integrate it?
Everyone says Llm is the future.
After 3 apps, I disagree.
The bottleneck isn't the API. It's your indices.
We switched to a vector-first approach and query times dropped by 400ms.
Bookmark this. π
Sick of AI theory without real projects?
I built a free Microsoft Learn Plan that bridges the gap.
It covers AI basics β NLP β AI Agents using Azure.
Learn it.
Build it.
Ship it.
Start your journey here: https://t.co/47JkK3AlcN #AIAgents
I spent 30 days analyzing Training a 4B model.
It's not about automation. It's about augmentation.
Relying 100% on Training a 4B model makes you generic.
But using Training a 4B model to speed up drafts by 80%?
You win.
How do you integrate it?
Day 58/100 β Reflection
Week 9 done.
Biggest win: Model accuracy hit 95%
Biggest challenge: Data cleaning took forever
Key lesson: Start small, iterate fast
Onward π
#100DaysOfAI
Theory is good, but building is better.
I designed a free Microsoft Learn Plan for developers who want to ship.
We cover AI fundamentals, NLP, and deploy AI Agents on Azure.
Connect the dots. Start here: https://t.co/47JkK3AlcN #AIAgents
Optimize Fed Raises Rates for in production:
1. Use Fed Raises Rates for for the heavy lifting.
2. Cache aggressively. Not caching? You're burning money.
3. Keep state simple.
What's your go-to Fed Raises Rates for stack? π
After 3 apps, I disagree.
The bottleneck isn't the API. It's your indices.
We switched to a vector-first approach and query times dropped by 400ms.
Bookmark this. π
Most AI learning paths leave you stuck between theory and actually building. I wanted one that connects the dots. So I created a free Microsoft Learn Plan covering AI β NLP β AI Agents with Azure. Learn it. Build it. Ship it. Start here: https://t.co/47JkK3AlcN #AIAgents
Day 53/100
A lot of people ask how I broke into AI research.
Build in public.
I shipped 'Smart NID Helper' to solve a real local problem.
I documented the whole process.
Don't just research. Deploy.
Hot take:
Claude are more important than the models themselves
The best devs are the ones who learn to use AI as a force multiplier
Fight me on this. π
#SoftwareDev
Stuck in tutorial hell?
I created a free Microsoft Learn Plan that actually connects the dots.
From AI and NLP straight to building AI Agents with Azure.
Learn it. Build it. Ship it.
Get started for free: https://t.co/47JkK3AlcN #AIAgents
I spent 30 days analyzing Rag.
It's not about automation. It's about augmentation.
Relying 100% on Rag makes you generic.
But using Rag to speed up drafts by 80%?
You win.
How do you integrate it?
Most AI learning paths leave you stuck between theory and actually building. I wanted one that connects the dots. So I created a free Microsoft Learn Plan covering AI β NLP β AI Agents with Azure. Learn it. Build it. Ship it. Start here: https://t.co/47JkK3AlcN #AIAgents
Everyone says Next.js is the future.
After 3 apps, I disagree.
The bottleneck isn't the API. It's your indices.
We switched to a vector-first approach and query times dropped by 400ms.
Bookmark this. π
The hardest part of Llm?
Scaling it.
Here is the fix:
What used to take a whole DevOps team can now be done in 3 CLI commands using Llm.
Stuck? Drop your error below. π
Sick of AI theory without real projects?
I built a free Microsoft Learn Plan that bridges the gap.
It covers AI basics β NLP β AI Agents using Azure.
Learn it.
Build it.
Ship it.
Start your journey here: https://t.co/47JkK3AlcN #AIAgents
The hardest part of Small programming tricks?
Scaling it.
Here is the fix:
What used to take a whole DevOps team can now be done in 3 CLI commands using Small programming tricks.
Stuck? Drop your error below. π