[Outcome 3] Hardware Constraints & Tradeoffs

[DiegoPICT]

Objective

Document the performance, latency, and accuracy tradeoffs when running AI coding tasks on each hardware tier.

What This Outcome Produces

USE-CASE-MATRIX.md (second section): Performance tradeoff data showing latency, throughput, accuracy, and practical viability for each task-tier pairing.

How It Builds

Participants contribute performance observations directly to findings/USE-CASE-MATRIX.md via PRs throughout Weeks 1–3. Each contribution is grounded in their actual benchmarking and real-world testing experience.

1. Create performance tradeoff sections in USE-CASE-MATRIX.md (latency, throughput, accuracy)
2. Participants add performance data via PR: "On 16GB tier, Tetris generation takes X seconds vs Y seconds on cloud"
3. Review PRs: ensure data is specific and quantified where possible
4. Merge and organize by task-tier pairing

Complete When

• Performance data captured for each meaningful task-tier pairing
• Tradeoffs are explicit (e.g., "slower but acceptable" vs "too slow to use")
• Data is quantified where possible (latency, accuracy degradation)
• Section marked ✅ when complete

Timeline

Active: Weeks 1–3 (participants add performance findings as they benchmark)
Due: July 16, 2026 (end of Week 3)

Resources

• findings/USE-CASE-MATRIX.md — Contribute second section here via PR
• QUICKSTART.md — Inference engine setup reference
• submissions/ — Review participant work and performance notes