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CASE STUDY  04 / 04

AI Engineering 2024 Ongoing

Engineering Evaluation System for AI Tools

A repeatable evaluation system for comparing AI tools and models against fixed tasks, criteria and evidence rather than demos or subjective impressions.

This case separates the implemented structure, my personal contribution and the boundary of what can be shown publicly.

Engineering Evaluation System for AI Tools project interface Anonymized reconstruction
AI 工具评测矩阵 · 基于实际评测维度的脱敏重构图 The public interface is reconstructed from the actual evaluation dimensions. Displayed scores illustrate the record structure and are not a published benchmark or third-party performance claim.

Problem, structure and delivery.

01 / Problem

Operating problem

AI tools change quickly and marketing demonstrations hide the gap between “works once” and “works reliably.” Without a consistent method, selection becomes subjective and difficult to reproduce.

02 / Approach

Delivery path

Derived fixed tasks and dimensions from real workflows, changed only the tool under test, and recorded both successful behavior and failure boundaries in a versioned structure.

03 / Architecture

System structure

The system combines a fixed task set, assessment dimensions and a versioned record template. Each run preserves the workflow and evidence format so results remain comparable.

The trade-off behind the interface.

Constraint
Tools changed quickly, marketing noise was high, subjective impressions were not reproducible, and public leaderboards did not represent reliability or integration cost in real engineering work.
Alternatives considered
  1. 01 Follow popularity and anecdotal recommendations
  2. 02 Use public leaderboards alone
  3. 03 Evaluate fixed scenarios with stable dimensions and versioned records
Why this choice
Built a standard task set from real work, fixed the process and dimensions, changed only the tool under test, and recorded both failure boundaries and appropriate contexts.
My contribution
Designed the method, tasks, record format and comparison dimensions, ran the evaluations, and separated public observations from personal judgment and unverified conclusions.
Result and reuse value
Turned tool preference into a traceable selection process that eliminates poor workflow fits earlier and preserves changes across versions.
Public evidence boundary
The public interface is reconstructed from the actual evaluation dimensions. Displayed scores illustrate the record structure and are not a published benchmark or third-party performance claim.
View in decision records

What remained after delivery.

  • Replaced subjective impressions with reproducible evaluation
  • Established reusable benchmark tasks and evidence records
  • Exposed tool boundaries and appropriate operating contexts
  • Reduced time spent testing unsuitable tools

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