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Built by Poonam Soni (@CodeByPoonam), 216K+ followers, Founder of AI Toast. Six AI mentors cover news, building, coaching, careers, research, and debate.

The 5-minute loop

Dashboard Preview

An interactive look at what your daily Poonami session will feel like. Switch agents, answer the quiz, step through the lesson.

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Builder Agent · Monday, March 30

RAG vs Fine-tuning: When to use each

Concept

RAG (Retrieval-Augmented Generation) pulls external data at query time. Fine-tuning bakes knowledge into model weights. RAG is cheaper and stays current; fine-tuning is faster at inference but expensive to update.

Agent takes

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News Agent

The RAG vs fine-tuning debate is heating up as retrieval systems get faster. Watch this space.

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Research Agent

Academic literature shows RAG reduces hallucination by ~34% on knowledge-heavy tasks.

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Career Agent

Knowing when to use RAG vs fine-tuning is one of the top AI interview questions right now.

Coach Agent Quiz

When should you choose RAG over fine-tuning?

Lesson anatomy

1

Key concept

2

Real example

3

Tool / workflow

4

Quiz

5

Action task

Your progress

Week 15/7 days

Top 23% of learners this week

News Agent · Today

Meta releases Llama 4 — biggest open-source model yet

Signal

Open weights shift power back to developers. Self-host frontier intelligence with zero API costs.

5 min readRead lesson →
Builder Agent

# your prompt

Summarise this PDF and extract the 3 key action items

→ RAG pipeline · LlamaIndex

PromptAutomateShip

Zero code required. Works in 5 minutes.

Coach Agent

Flashcard · Day 3

What is RAG?

Retrieval-Augmented Generation — pulls live data at query time. No retraining needed.

5 day streak · 90% retention rate

Career Agent

How to land an AI role without an ML degree

Ship 3 AI projects publicly

Document your workflows

Rewrite your LinkedIn summary

Today's action

Write your AI professional summary →

Research Agent

Benchmark breakdown: what the scores actually mean

GPT-588
Claude 476
Gemini71

MMLU benchmark · Third-party data

Debate Agent

AI will take your job — and that might be fine

For

Technology always creates new jobs. History proves it.

Against

Not for the same people, or in the same timeframe.

Form your own view. Both sides, every time.

Your progress

Week 3

5

Day streak

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5 of 7 agents completed today

Coach · Quiz

What is the primary advantage of open-weight models?

They always outperform closed models
Self-hosting removes API costs and privacy concerns
Easier to fine-tune than GPT-4
Approved for regulated industries

Correct! +10 streak points