Module 5 · Thinkers Team

AI Development

Prompt engineering, resume transformation, interview coaching, and AI use case classification — all interactive.

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1 Prompt Engineering

Mastering the art of communication with AI is the first step. A great prompt includes four key ingredients: Context, Problem, What You've Tried, and What You Need.
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LLMs
Large Language Models predict the next token based on patterns in training data.
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Prompt Engineering
The art of writing inputs that reliably produce useful AI outputs.
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API Integration
Call Gemini, GPT, or Claude from your backend to add AI features.
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Use Cases
Summarization, classification, generation, code review, and more.
  • The Prompt Formula:
    1. Context: What are you working with? (e.g., Python, Flask, a specific library)
    2. Problem: What is the specific issue? (e.g., "I'm getting a 404 error")
    3. What You've Tried: Show your work. (e.g., "I've checked the routes and tested with Postman")
    4. What You Need: What is your desired outcome? (e.g., "I need a checklist of likely causes")
  • Iterate, Don't Quit: The first response from an AI is rarely perfect. Refine your prompt based on the AI's output. Winners iterate 3–5 times.
Start every prompt with a role: "You are a senior Python engineer." It anchors the AI's response style and expertise level.

2 Coding with AI

When it comes to generating code, specificity is everything. The right framework turns a vague request into a precise, actionable prompt.
  • The SPEC Framework: Specific, Platform, Examples, and Constraints.
  • 4-Step Debugging Template: Problem, Expected vs. Actual, Minimal Code, and What You Tried.
  • The 5 Security Non-Negotiables: SQL Injection, Hardcoded Secrets, Input Validation, XSS, and Authentication/Authorization.
Always ask the AI to explain its code. If it can't, the code probably isn't doing what you think.

3 Professional Applications

Leverage AI to accelerate your career, but know its limits. AI shines at structuring and drafting — your experience and authenticity make it real.
  • Resume Transformation with STAR: Turn weak resume points into compelling, quantified achievements.
  • Interview Preparation: Practice answering crucial questions about failure, project architecture, and your interest in the company.
  • Know When to Use AI: Great for summarizing and brainstorming, bad for highly specialized or sensitive topics.
Never submit AI-generated content verbatim. Edit it to reflect your voice and verify every factual claim.

4 Interactive: Resume Transformer

Paste a weak bullet point and generate three STAR-formatted versions — conservative, balanced, and bold — to see how framing changes impact.

Resume Bullet Transformer

Paste your weak bullet point and we'll generate 3 STAR versions!

The STAR method: Situation, Task, Action, Result. Lead with action verbs and end with a measurable outcome.

5 Interactive: Interview Analyzer

Practice answering common interview questions and get instant AI feedback on structure, specificity, and how well your answer addresses the question.

Mock Interview Analyzer

Type your answer to one of the questions below (250 words max).

Analysis Results

Use the STAR format for behavioral questions. Keep your answer under 2 minutes when spoken aloud — about 250–300 words.

6 Interactive: AI Use Case Sorter

Not every task is a good fit for AI. Test your instincts by sorting real-world scenarios — click each card to reveal whether it's a smart or poor use of AI.

Use Case Sorter Game

Click each scenario card to sort it — confirm if it's a good or bad use of AI.

Score: 0/6 correct

AI works best when tasks are well-defined, repeatable, and don't require real-time or highly sensitive data.
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