Building Your First AI Project

Build your first AI project step by step, from choosing the problem through prototyping, evaluation, safety, and launch.

Let's think about it this way for a second

For your first AI project, thoroughly solving one small problem matters far more than picking the biggest model. "I'll build an AI chatbot" isn't clear enough. "Answer questions from 20 tutorials with a source link" is something you can actually measure.

Building Your First AI Project lesson illustration — Agents, Privacy, and Project — Building Your First AI Project

Let's connect this to everyday life

For your launch version, build a Myanmar AI Learning Assistant — it should search tutorial content, use the relevant passage to give a short answer, and show a link to the source lesson. Have it admit when it doesn't know, and add a user feedback button.

Problem, audience, and success metric
A small test dataset with expected answers
Server-side API, validation, and budget limit
Quality, safety, and privacy evaluation
Feedback, monitoring, and rollback plan

Let's try it hands-on together

text

Project Definition of Done
✓ မေးခွန်းလက်ခံနိုင်သည်
✓ ဆိုင်ရာ lesson ကိုရှာနိုင်သည်
✓ Source link ပါသောအဖြေပြန်သည်
✓ မတွေ့လျှင် မှန်ကန်စွာဝန်ခံသည်
✓ API key မပေါက်ကြားပါ
✓ Test questions 20 ခုတွင် quality စစ်ပြီးသည်
✓ Cost, latency, error logs စောင့်ကြည့်နိုင်သည်

You should see

You'll come away with a first AI project MVP that's genuinely usable and has been tested.

5-minute try-it

Build a lesson search assistant, then create an evaluation sheet with 20 questions, the expected source, and a pass/fail reason for each. Fix three of the failures before you deploy.

A quick word of caution

Don't treat AI output as the final word. Have a human review anything important — including code and user data — before it's actually used.

OpenAI API Quickstart — OpenAI

OpenAI — Retrieval — OpenAI