Practical guides for AI product teams on A/B testing prompts, optimizing for business outcomes, and building better AI products through experimentation
If you're building an AI-powered product, prompt performance isn't just about clever wording - it's about business impact. A/B testing is how you find out which prompts actually improve conversion, retention, cost, or user satisfaction in production.
Read Article →Prompt optimization isn't just about clever wordsmithing - it's about running experiments that improve real business outcomes. Here are ten practical A/B test ideas AI product teams can try today.
Read Article →A/B testing is a proven playbook in SaaS and consumer apps. But LLM-powered products break many of the old assumptions. To test prompts effectively, product teams need to understand what's different.
Read Article →In AI product circles, people often mix up "evals" and "A/B testing." They're related, but they serve different purposes. If you're building an AI product, knowing when to use which is critical.
Read Article →Prompt optimization doesn't have to be guesswork. There's a repeatable workflow that helps AI product teams move from "I think this prompt is better" to "I know this prompt improves our business."
Read Article →Everyone talks about "prompt optimization" - but what does it actually mean when you're building an AI product? For product teams, it must mean something deeper: does this prompt improve the business?
Read Article →TwoTail makes it easy to experiment with prompts, models, and policies in production. Get early access and start optimizing for real business outcomes.