Overview
What this challenge is about.
Build a 3-agent system for biotech patent prior-art memos and compare against a baseline. Get a verifiable certificate.
The scenario
The firm (12 attorneys, around 200 active matters) spends about 8 attorney-hours per first-pass prior-art memo; even a 30% time cut translates into a meaningful capacity gain at their billing rates.
The Brief
What you'll do, and what you'll demonstrate.
Determine whether a multi-agent system produces better first-pass prior-art memos than a single-agent baseline, on the firm's own historical cases.
Earning criteria — what you'll demonstrate
- Design multi-agent systems with explicit role decomposition
- Benchmark multi-agent vs. single-agent on a real task
- Apply human-rater evaluation to LLM-generated long-form outputs
- Communicate agent risk to a non-technical legal audience
Program Fit
Where this fits in your program.
Sharpens the same skills your degree expects you to demonstrate.
AI Agents and LLM-Based Agents
Master · Ai Systems
Strong alignment
This challenge maps to AI Agents and LLM-Based Agents at the Master level. It sharpens the same practical skills your coursework expects — but in a real industry context with actual constraints and deliverables.
Skills
Skills you'll demonstrate.
Each one shows up on your verified credential.
- Llm Agents
Apply llm agents to solve real industry problems and demonstrate production-level capability.
- Multi Agent Collaboration
Apply multi agent collaboration to solve real industry problems and demonstrate production-level capability.
- Agent Evaluation
Apply agent evaluation to solve real industry problems and demonstrate production-level capability.
- Prompt Engineering
Apply prompt engineering to solve real industry problems and demonstrate production-level capability.
- Retrieval Augmented Generation
Apply retrieval augmented generation to solve real industry problems and demonstrate production-level capability.
- Python
Write clean, efficient Python for data processing, automation, and backend services.
Careers
Career paths this challenge builds toward
Completing this challenge demonstrates skills that transfer directly to these roles:
AI Engineer
Designing and shipping a multi-agent system for a real legal customer is the kind of project that lets an AI engineer specialize into vertical AI roles.
This challenge sharpens
- multi-agent-collaboration
- llm-agents
- retrieval-augmented-generation