From Zero-Shot to High-Performance Outreach: Testing & Tuning With Galileo

Zero-shotting an SDR outreach app is easy. Making it consistently good is the hard part. In this demo, we walk through how Galileo helps you test, iterate, and dramatically improve the emails, LinkedIn messages, and call scripts generated by your agent. You’ll see how to integrate Galileo with just three lines of code, capture every tool call and model invocation, and use built-in metrics and custom evaluations to move from generic output to personalized, high-quality outreach. We’ll explore how prompt versions evolve, how dataset-driven experimentation works, and how guardrails protect your app from toxic or unsafe output. Whether you’re building outbound automation, personalization engines, or sales-assist agents, this walkthrough shows how Galileo lets you move fast while still improving reliability and quality. 🔍 What you’ll learn - How to integrate Galileo into a LangGraph/LangChain SDR assistant with a few lines of code - How to track all tool calls, model calls, and session activity - How to use built-in metrics like completeness, context relevance, correctness, and chunk attribution - How to create and apply custom metrics (Email Score, LinkedIn Score) - How to iterate and improve prompts with dataset-level testing - How personalization hooks boost quality using company research, pain points, funding events, and growth signals - How to add protection rules to block PII, toxic content, and unprofessional output - How Galileo acts as the feedback engine for better outreach 🚀 Why it matters SDR workflows depend on message quality. Galileo gives you the testing, evaluations, and guardrails you need to reliably improve messaging—without guesswork, manual scoring, or risky production testing. Try the product for free: http://app.galileo.ai/sign-up?utm_medium=organic&utm_source=youtube 📍 Chapters 00:00 Overview of the SDR Outreach Assistant 00:32 How the App Works (Leads, Vector Store, Research) 00:57 Zero-Shot Output and Its Limitations 01:18 Why Improving Output Matters 01:39 Under the Hood: LangGraph Nodes & Workflow 01:57 Integrating Galileo With Three Lines of Code 02:20 Tracking Sessions, Tool Calls, and Model Calls 02:47 Improving the Email Prompt in Galileo 03:08 Testing Prompt Versions Against Real Leads 03:43 Reviewing Past Prompt Iterations 04:04 Using Logs to Inspect Research and Personalization 04:26 How Galileo Surfaces Key Personalization Signals 04:55 Using Built-In Metrics for Quality Scoring 05:24 Creating Custom Metrics (Email & LinkedIn Quality) 05:59 Using Chunk Attribution for RAG Analysis 06:27 Adding Protection Rules With Guardrails 07:08 Blocking PII, Toxicity & Unprofessional Output 07:24 Ensuring Safe, High-Quality Outreach at Scale