Post - March 08, 2025
Best prompt evaluation tools in 2025: a practical comparison for AI teams
Compare the best prompt evaluation tools in 2025 - features, scoring methods, CI integration, and pricing for AI teams building at scale.
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Prompt Engineering
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Post - February 07, 2025
Prompt Evaluation Systems: How to Safely Ship Prompt Changes, Model Upgrades, and Parameter Tweaks
Learn how to build prompt evaluation systems that catch regressions from prompt edits, model upgrades, and parameter changes before they reach production
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Post - January 28, 2023
Prompt Engineering for Engineers: From Zero-Shot to Automatic Prompt Design
A practical, code-backed guide to prompt engineering: zero-shot, few-shot, CoT, self-consistency, tree of thoughts, structured output, and automatic prompt design.
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Post - January 08, 2023
How to Qualify and Evaluate Prompt Changes in GenAI Image Classification Systems
Learn how to systematically evaluate and qualify prompt changes in LLM-driven image classification systems using metrics, testing frameworks, and best practices
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Post - September 14, 2022
Building a Customer Support Chatbot: An AI Engineering Architecture Case Study
Walk through a real architectural decision for building an AI customer support chatbot: foundation models, RAG, data needs, and differentiation.
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Post - September 13, 2022
ML vs. Foundation Models: A Real-World Architectural Decision for Product Classification
Walk through a real AI engineering decision: classical ML vs. foundation models for product category classification, with data and adaptation strategy.
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Post - September 10, 2022
Model Adaptation Techniques in AI Engineering: Prompt Engineering vs. Fine-Tuning and Their Data Needs
Compare prompt engineering, RAG, and fine-tuning as model adaptation techniques, and learn how their data requirements differ for AI applications.
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Post - September 04, 2022
The Three-Layer AI Engineering Stack: Application, Model, and Infrastructure Explained
Understand the three-layer AI engineering stack and how it differs from classical ML pipelines in structure, differentiation, and build order.
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Post - September 03, 2022
AI Engineering vs ML Engineering: How Foundation Models Are Reshaping the Production Pipeline
Explore how AI engineering differs from classical ML engineering in architecture, data needs, and evaluation when building on foundation models like LLMs
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