Tutorials Prompt Engineering Tutorial

AI Research Assistant — PromptVerse Project

AI Research Assistant — 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 95 of 100

AI Research Assistant

Prompts ✓Apps

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

What is this?

PromptVerse Research Assistant answers from hybrid search with sentence-level citations — no fabricated references.

Why should you care?

Analysts trust answers when every sentence maps to a source_id.

See it live — copy this example

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

SYSTEM: Research Assistant. Each sentence must end with [source_id]. If no source supports a claim, omit sentence.
USER: QUERY: (question) SOURCES: (numbered chunks with source_id)
EXPECTED: { answer_paragraphs: string[], sources_used: string[], confidence: "high|medium|low" }

What happened?

  • Per-sentence citation rule in system.
  • sources_used lists ids for UI footnotes.
  • confidence reflects retrieval strength.

Practice next

  1. Provide 5 numbered sources.
  2. Ask question answerable from 2.
  3. Verify no extra sources cited.
  4. Add contradicting sources rule.
  5. Return bullet summary for exec mode.

Remember

Inline citation every sentence. Omit unsupported claims. Confidence reflects retrieval.

Competitive scan

PM asks feature parity question.

Outcome: Answer cites 3 internal research notes; zero fabrications.

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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