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 Persona & Scope
Define domain boundaries, tone, role, and audience for the research assistant.
Prompt Foundations & Constraints
Transform generic queries into structured, constraint-enforced system prompts.
Structured Outputs (JSON Schema)
Enforce rigid JSON outputs for seamless downstream software integration.
Information Retrieval & Synthesis
Design fact extraction pipelines that synthesize multiple technical sources.
Tool Use & Function Calling Basics
Enable the assistant to query external APIs and calculation tools.
Model Context Protocol (MCP) Simulation
Integrate MCP servers for structured context injection.
Evaluation, Guardrails & Benchmarking
Implement automated safety filters, hallucination checks, and benchmark test suites.
Final Capstone Showcase & Mentor Review
Final Milestone • Mentor ReviewBundle all deliverables and submit for human mentor evaluation and certification.
🎯 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