*# 🚀 My AI Agents Intensive Journey — Solo but Worth It
I joined the AI Agents Intensive as a solo participant with one goal:
build something real instead of just completing theory.
For my capstone, I built an AI tool that uses an LLM to summarize YouTube videos into short, meaningful takeaways. The idea was simple: save time by converting long content into short, structured output.
🎯 What I Built
- Extracts content from YouTube videos
- Uses an LLM to process and generate summaries
- Outputs clean, short, understandable insights
Not perfect — but functional.
⚠️ Challenge I Faced
The biggest roadblock wasn’t accuracy — it was slow inference.
Responses were taking too long, sometimes long enough to break the workflow.
It wasn’t a code issue — it was an optimization problem.
🛠️ How I Solved It
Instead of switching models or rebuilding everything, I optimized how the model processed the context.
- Removed unnecessary steps
- Simplified the workflow
- Improved prompt structure
- Tested with different videos until the performance was consistent
It wasn't a magic fix — just iteration and patience.
📚 What I Learned
This project changed how I look at AI:
- A good idea isn’t enough — execution matters.
- Speed matters more than complexity.
- Working solo forces you to think like an engineer, tester, and user.
The biggest lesson:
You improve models by thinking — not just by adding more compute.
🚀 What’s Next
This project is just a starting point. Next steps:
- Fine-tune the model
- Improve inference efficiency
- Handle a wider variety of video content
There’s still a lot to improve — which is good, because improvement means growth.
🏁 Final Reflection
This intensive wasn’t just a course — it was momentum.
It proved that you don’t need perfection or a team to build something useful.
If I had to summarize the experience in one line:
You don’t need to know everything to start —
but you do need to start to learn anything.
---his is a submission for the Google AI Agents Writing Challenge: Learning Reflections*
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