AI Engineering Playbooks
Step-by-step guides for common production scenarios. Each playbook gives you a proven process, from initial setup to deployment, with code examples and decision trees.
🚧 Playbooks Coming Soon
We're building comprehensive playbooks based on real production patterns. Subscribe to get notified when they're published.
Planned Playbooks
Building a Production RAG System
Complete guide from document ingestion to query handling: chunking strategies, embedding selection, vector stores, retrieval optimization, and monitoring.
Prompt Engineering Workflow
Systematic approach to designing, testing, and deploying prompts: from requirements gathering to A/B testing and version control.
Building an AI Chatbot
End-to-end chatbot implementation: context management, conversation memory, tool integration, error handling, and user feedback loops.
Evaluating LLM Outputs at Scale
Build evaluation pipelines: test set creation, automated grading, human review workflows, and continuous monitoring dashboards.
Agent Systems Architecture
Design and implement multi-agent systems: task decomposition, agent orchestration, tool use patterns, and failure handling.
Fine-tuning vs. RAG Decision Tree
When to fine-tune, when to use RAG, and when to do both: cost analysis, performance comparisons, and hybrid approaches.
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