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- Learning Loop ♾️ 06-2025
Learning Loop ♾️ 06-2025
Your bi-weekly dose of learning AI, without the hype.

Hello peeps,
Hello everyone, and a very warm welcome to the 6th edition of AIpeeps!
What we’re covering today:
Top-P Sampling – probability-based sampling that makes text feel natural
ChatGPT GO (India) – new features, speed, and what I tested so far
Formatting in Excel – why it fails, what works, and community call-out
Wrappers in AI – why startups build on top of LLMs instead of building them
💡3 Curious things I learnt
1. Top-P Sampling
Top-P is another sampling method used by LLMs.
Here’s how it works:
You let the model choose from words that fall within a cumulative probability threshold.
Instead of restricting to a fixed number of top words (like in Top-K), Top-P looks at probabilities until the cutoff is reached.
This makes the text more natural, more human-like, and often more creative.

Top - P
👉 Last week: I explained Top-K — where you limit the model’s choices to K words.
👉 This week: With Top-P, you don’t limit the number of words, only the probability range.
Why it matters:
Top-K → great for consistency (predictable answers).
Top-P → great for fluency and creativity (varied but still coherent text).
Think of it as the difference between confining the model to a small menu (Top-K) vs letting it explore all dishes that meet a certain quality level (Top-P).
I’ve also shared some examples of how outputs shift when switching between these two:

Top P and Top K
2. ChatGPT GO
Yes — ChatGPT Pro is now available, but only in India 🇮🇳.
Makes sense, since India is the second-largest ChatGPT user base worldwide.
👉 Price: ₹399
👉 How to get it: Go to Upgrade → Select the plan → Pay via UPI

CHATGPT GO STEPS
What I’ve tried so far:
Projects
Independent memory, documents, and instructions grouped together.
Useful if you’re working on:
a business idea
a newsletter (like this one)
or even a long-term side project.
It keeps context separate so you don’t mix work with personal prompts.
Image generation
Noticeably faster compared to the free tier.
Took me under 60 seconds to generate an image.
As a free user, the same prompt used to take much longer.
💡 Note: That’s my initial exploration. In the next issue, I’ll cover more on add-on features in detail.
3. Formated Excel Output with ChatGPT
This one was a fail (at first).
When I tried asking ChatGPT to make Excel sheets with formatting + formulas, it only gave me raw data — no colors, no fonts, no neat formatting.
Here’s what I figured out:
You must spell out every detail: colors, fonts, column widths, and formulas.
If you just say “make it nice,” it won’t.
The more specific you are, the closer you get to the actual formatted sheet.
💡 I’m still working on this.
If you’ve managed to crack the perfect prompt for formatted Excel outputs, reply back — I’d love to share community wins here.
My prompt for below output - “create a table of SIP of 10K for 15 years in excel with nice formating having blue color and Arial 10 ; formulae of sum should also be there”

Formatted Output
🕵🏻Decoding the Jargon
Wrappers in AI
A wrapper = the same core product, just packaged differently.
Think about the food industry → same ingredients, different packaging or branding.
In the AI world:
There are only 5–7 core LLM providers (OpenAI, Anthropic, Google, etc.).
Most new AI startups are not building their own models.
Instead, they wrap around these LLMs with:
Better UI/UX
Domain-specific data (RAG)
New workflows or integrations
Example: platforms like Lovable don’t create the LLM — they wrap it with features that make it more usable for a niche.
So when you hear about “new AI tools,” most are wrappers built on top of the same few LLMs.
Try it Out this week:
Create a Project in ChatGPT Pro → test independent memory + docs.
Brainstorm wrapper ideas you could build around LLMs → think startup potential.
Use Top-P in your next prompt and compare it with Top-K → see the difference for yourself.
Hope you learned something new today!
🚀 “Found this useful? Pass it on to your close circle — knowledge hits different when it’s shared.”
Till next time,
Curiously yours,
Gaurav Jain
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