Tutorials Prompt Engineering Tutorial

AI Coding Copilot — PromptVerse Project

AI Coding Copilot — PromptVerse Project: free step-by-step lesson with examples, common mistakes, and interview tips — part of Prompt Engineering Tutorial on Toolliyo Academy.

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Prompt Engineering Tutorial · Lesson 91 of 100

AI Coding Copilot

Prompts ✓Apps

Apps · 2 — RAG & agents · ~10 min · Module 10: Real-World AI Projects

What is this?

PromptVerse Dev Copilot answers integration questions with cited internal docs and fenced code matched to your stack.

Why should you care?

Ship a copilot that never guesses endpoint URLs — it searches OpenAPI first, then writes code.

See it live — copy this example

Copy the prompt into ChatGPT, Claude, or your LLM API playground and compare outputs.

SYSTEM: PromptVerse Dev Copilot. Search docs before coding. Cite doc slug. Output: explanation + single fenced code block + test snippet.
USER: How do I list orders with pagination in Node?
EXPECTED OUTPUT SHAPE:
{ explanation: string, code: string, doc_slugs: string[], test_hint: string }

What happened?

  • System mandates search-then-code.
  • Expected JSON shape lets IDE render explanation, code tab, and doc links separately.

Practice next

  1. Paste system+user into playground.
  2. Verify output has doc_slugs array.
  3. Check code uses pagination param from docs.
  4. Add language: typescript strict.
  5. Require error handling in snippet.

Remember

Search before generate. Structured copilot output. Citations required.

Orders API question

Junior dev asks pagination question.

Outcome: Copilot returns cited fetch loop + unit test hint.

Interview prep for this lesson

Practice these questions aloud after reading—each links to a full structured answer.

Junior Detailed
Describe a real-world scenario where Production mattered in a Prompt Engineering project.
Short answer: Interviewers want a crisp definition, a practical example from your projects, and awareness of trade-offs—not textbook dumps. Explain a bit more How to structure your answer (60–90 seconds) Define Productio…
Junior Detailed
Explain Concepts in the context of Prompt Engineering.
Short answer: Interviewers want a crisp definition, a practical example from your projects, and awareness of trade-offs—not textbook dumps. Explain a bit more How to structure your answer (60–90 seconds) Define Concepts…
Mid Detailed
What are common mistakes teams make with LLMs when using Prompt Engineering?
Short answer: Interviewers want a crisp definition, a practical example from your projects, and awareness of trade-offs—not textbook dumps. Explain a bit more How to structure your answer (60–90 seconds) Define LLMs in p…
Senior Detailed
How would you debug a production issue related to RAG in a Prompt Engineering application?
Short answer: Interviewers want a crisp definition, a practical example from your projects, and awareness of trade-offs—not textbook dumps. Explain a bit more How to structure your answer (60–90 seconds) Define RAG in pl…
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Prompt Engineering Tutorial
Course syllabus

Prompt Engineering Tutorial

Module 1: Prompt Engineering Foundations
Module 2: Basic Prompting Techniques
Module 3: Advanced Prompt Engineering
Module 4: Structured Outputs
Module 5: RAG Systems
Module 6: AI Agents
Module 7: AI Automation
Module 8: Prompt Security & Ethics
Module 9: Performance & Optimization
Module 10: Real-World AI Projects
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