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Beyond Gut Feeling: Why Your AI Needs Systematic A/B Testing

Stop guessing and start measuring. Learn how a data-driven experimentation framework like Experiments.do can help you build more reliable, efficient, and effective AI applications by moving beyond intuition.

Experiments
3 min read

Optimizing Your RAG Pipeline: A Guide to A/B Testing Retrieval and Generation

A deep dive into improving your Retrieval-Augmented Generation systems. We'll show you how to systematically test chunking strategies, embedding models, and generation prompts to maximize relevance and accuracy.

Data
3 min read

From Cost to Conversion: The Business Metrics You Should Be Tracking in Your LLM Apps

Your AI's performance isn't just about latency and token count. Discover how to link AI experiments to key business indicators like customer satisfaction, conversion rates, and user engagement.

Business
3 min read

How to A/B Test LLM Prompts Like a Pro with Experiments.do

A practical, step-by-step tutorial on setting up your first prompt experiment. Learn how to compare prompt variants, define success metrics, and confidently deploy the winning version to production.

Workflows
3 min read

GPT-4 vs. Claude 3: A Data-Driven Guide to Choosing the Right Model for Your Use Case

Don't rely on generic benchmarks. Learn how to run head-to-head model comparison experiments on your own data to find the optimal balance of performance, cost, and speed for your specific application.

Experiments
3 min read

Evaluating Agentic Workflows: How to Reliably Test Multi-Step AI Systems

Testing complex AI agents presents unique challenges. This post breaks down strategies for evaluating multi-step chains and agentic systems to ensure they are robust, reliable, and achieve their goals.

Agents
3 min read

The Art of AI Evaluation: Defining Custom Success Metrics for Your Experiments

What does a 'good' AI response look like? We explore how to move beyond simple metrics and define nuanced, custom evaluation criteria that truly capture the quality and effectiveness of your AI components.

Data
3 min read

Closing the Loop: Integrating Experiments.do into Your CI/CD Pipeline for AI

Automate your AI optimization process. Learn how to embed experimentation directly into your development and deployment workflows, creating a system of continuous improvement for your AI services.

Integrations
3 min read

The ROI of AI Experimentation: Building a Culture of Continuous Improvement

Investing in a structured testing platform pays dividends. We explore the long-term value of AI experimentation, from reducing operational costs to building superior user experiences and gaining a competitive edge.

Business
3 min read

Tackling Hallucinations: Using A/B Testing to Improve Factual Grounding

Reduce inaccuracies and build user trust. See how you can use Experiments.do to methodically test prompts and RAG configurations that are specifically designed to minimize model hallucinations and improve factual accuracy.

Experiments
3 min read