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Learn how to create a multi-agent email generation tool with dynamic content pipelines with AI Tinkerers & PromptLayer
An Inside Look at Production AI Systems That Actually Convert
Join AI Tinkerers for a technical deep-dive into how PromptLayer engineered a multi-agent email system achieving 50-60% open rates & 7% positive reply rates. See the actual architecture, learn the engineering decisions, & understand the production patterns behind a revenue-generating AI system.
What You'll Learn
This educational session reveals the technical architecture & engineering decisions behind a production multi-agent email system, covering:
Key Technical Insights
Architecture & Optimization
Multi-agent systems outperform monolithic approaches for specialized email generation
Dynamic model selection (gpt-4o-mini to gpt-4.5) based on complexity requirements
Strategic QA pipeline placement: effective for subject lines, counterproductive for content
Cost optimization achieving $0.002 per lead through intelligent resource allocation
Production Engineering
Prompt version control managing 33+ iterations with safe deployment practices
Real-time web scraping with parallel processing & robust fallback strategies
Failure handling through retry logic, escalation paths, & performance monitoring
Cross-functional systems enabling non-technical teams to operate AI workflows
Workshop Format
Main Demonstration (20 minutes): Inside Agent #1 - Research & Scoring See how PromptLayer's team architected their lead processing pipeline:
Live walkthrough of canonical URL resolution logic
Examination of parallel web scraping + LLM processing architecture
Analysis of relevance reasoning prompts & scoring algorithms
Deep-dive into branch gating decisions & cost trade-offs
Real debugging session of production prompt failures
Technical Deep-Dives (10 minutes): Refining the Rough Edges
Agent #2: Subject line generation with cascading QA loops
Agent #3: Template-based sequencing & why they removed QA here
Integration architecture with CRM systems & webhook patterns
All demonstrations use their actual production code & real performance data
Who Should Attend
Technical Audience Seeking Production Insights:
Senior engineers evaluating AI system architectures
Technical leaders planning AI implementations
ML engineers interested in production deployment patterns
Platform engineers supporting AI workloads
CTOs/Technical founders scaling AI-powered products
Presenter
Jared Zoneraich - CEO & Co-founder at PromptLayer. Built effective AI hyperpersonalization sales campaigns that let him shut down all his BDR roles. Leading the development of production prompt management infrastructure used by hundreds of AI companies. Will share both the technical architecture & business context behind engineering decisions.
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