Turn Prompt Engineering Into a Testable Discipline
Stop guessing. Start measuring. Move beyond vibes and intuition with a framework built for structured problem solving and iterative prompt refinement.
Security Reviewer
v2.4.0 • Updated 2h ago
// System Prompt
"Act as a senior security engineer. Analyze the following code snippet for OWASP Top 10 vulnerabilities..."
Works
12/12
Model
GPT-4
Latency
1.2s
Prompt Engineering Has No Feedback Loop
Traditional prompting is a dark room. You tweak a word and hope it works better. We provide the light: a continuous cycle of measurement and refinement.
Problem
Define the desired outcome precisely.
Prompt
Construct the engineering input.
Score
Evaluate against objective metrics.
Improve
Iterate based on performance data.
Problems Turn
Prompts Into
Solutions
In Promptvexity, a Prompt is never standalone. It is always a solution to a specific Problem. This hierarchy ensures every token you write has a measurable purpose.
Defining Goals
Problems define strict constraints, objective success criteria, and hidden test cases.
Versioning Solutions
Branch prompts like source code. Compare v1 vs v2 head-to-head across the same problem sets.
Problem
Classify support tickets by urgency
v2.1 Fork
Community improvement → 97
The 3-Step Workflow
1. Browse Problems
Explore existing problem statements or create your own with clear evaluation metrics.
2. Submit Prompt
Draft your prompt solution. Attach your system instructions, few-shot examples, and model parameters.
3. Analyze & Improve
Run the evaluation engine to see exactly where your prompt succeeds and where it fails.
Built for Modern AI Operations
Versioning
Git-like history for every prompt iteration.
Evaluation
Automated scoring against ground-truth datasets.
Problem-Based
Prompts are scoped to specific business problems.
Model-Agnostic
Test across GPT-4, Claude 3, Llama 3, and more.
--- v1.0.2
+++ v1.1.0
// Evaluation Results:
Accuracy: 72% -> 91%
Latency: 0.8s -> 1.1s
The numbers speak for themselves
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