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Domain-Specific LLM Cost Optimization Strategy & Implementation

  • Apr 2
  • 3 min read



Duration: 10–14 days following Assignment 1

Type: Individual Assignment

Difficulty Level: Advanced

Marks: 100



This assignment requires you to create an original, domain-specific cost optimization strategy for a real-world LLM application that you research or design. Unlike Assignment 1 (general framework), Assignment 2 demands independent research, creative problem-solving, and domain expertise.





Learning Objectives


  • Research real LLM cost challenges in a specific industry.

  • Design novel optimization strategies tailored to domain constraints.

  • Justify design decisions with cost-benefit analysis and risk assessment.

  • Implement a proof-of-concept for your strategy.

  • Communicate your findings in a professional research report.





Task Overview

Choose one of the following domains and create an optimization strategy:


  • Customer Support Chatbot — Handle 50K queries/month with <$500/month LLM cost

  • Document Analysis & Extraction — Process 10K documents/month at <$200 cost

  • Content Generation Platform — Generate 1000 articles/month at <$300 cost

  • Real-Time Recommendation Engine — Personalize search results for 100K users at <$400/month

  • Healthcare AI — Analyze patient records compliance-aware at <$600/month

  • Custom Domain — Propose your own with instructor approval by day 3





Requirements


  • Research: interview users, analyze real cost data, or use public case studies

  • Cost Baseline: establish current (or hypothetical) costs and pain points

  • Innovation: propose 3–5 novel cost optimizations specific to your domain

  • Proof-of-Concept: implement a working prototype or detailed simulation

  • Analysis: compare your strategy to industry benchmarks; project cost savings

  • Risk Assessment: identify risks, trade-offs, and mitigation strategies





Deliverables




1. Research Report (16–20 pages)


  • Domain analysis and cost drivers

  • Literature review (3–5 academic/industry sources)

  • Your optimization strategy (detailed design)

  • Proof-of-concept implementation or simulation

  • Cost/benefit projections (1–3 year TCO)

  • Risk analysis and mitigations

  • Ethical considerations (if applicable)




2. Jupyter Notebook


  • Working code or detailed simulation

  • Cost projections and visualizations

  • Benchmark comparisons

  • Sensitivity analysis (e.g., 'If usage doubles, costs increase by X%')




3. Presentation Slides (8–10 slides) for peer review



Marking Rubric

Criteria

Marks

Domain Research & Analysis

20

Problem Identification

15

Innovation & Originality

25

Technical Implementation

20

Cost Projections & Rigor

10

Report & Presentation Quality

10

Total

100





Resources & Support


Course Materials: All 9 chapters + provided sample datasets

Office Hours: Weekly; book via Moodle

Discussion Forum: Post technical questions (response time: 24–48 hours)

Feedback Schedule: Assignment 1 feedback within 10 days of submission





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