Build an AI Research Assistant
Master the foundations of practical AI engineering by building an automated research assistant that parses user inquiries, executes tool-driven web and literature queries, evaluates source credibility, and synthesizes structured analytical briefs.
Project Roadmap
Complete each milestone to build your final deliverable step by step.
Define the Assistant
Specify the agent's objective, persona, core capabilities, and strict operational boundaries.
Prompt Foundations
Transform weak, open-ended research queries into rigid, high-precision structured prompts.
Structured Outputs
Enforce strict JSON schema responses with typed fields for hypotheses, findings, and citations.
Information Retrieval
Incorporate source retrieval context and teach the assistant to handle conflicting data gracefully.
Tool Use Basics
Configure simulated function calling so the assistant can trigger external search and calculation tools.
MCP Basics
Connect your assistant architecture to standard Model Context Protocol (MCP) data endpoints.
Evaluation & Refinement
Stress-test the research assistant against edge cases, hallucinations, and safety constraints.
Final Showcase & Mentor Review
Final Milestone • Mentor ReviewAssemble the complete research assistant suite, export the portfolio deliverable, and submit for foundation review.
🎯 Final Deliverable
A fully functioning AI Research Assistant prompt engine and tool executor capable of synthesizing multi-source research into structured executive summaries.
🧠 Skills Mastered
- ✓Role & Persona Definition
- ✓Constraint Engineering
- ✓Few-Shot Context Injection
- ✓JSON Schema Enforcement
- ✓Information Retrieval Strategies
- ✓Tool-Calling Architecture
- ✓Evaluation & Iteration Rubrics
🛠 Tools & Concepts
"This project is the core foundation for everything in modern AI. By understanding how to constrain outputs and ground agents with external tools, you will be able to build any specialized AI assistant."
— UFI AI Academy Team