Agentic AI, LLM engineering, and the models behind modern automation — multi-agent systems, LLM evaluation and comparisons, RAG, fine-tuning, AI infrastructure, security, and production AI engineering.
From the blog
Learn the core principles behind designing a developer-friendly AI agent SDK, including method naming conventions, builder patterns, fluent chaining, and how to craft an API surface that developers love to use.
Learn how to architect a customer support AI agent with intent classification, knowledge base integration, conversation state management, and escalation paths that handle real-world support complexity.
Learn how to design normalized database schemas for AI agent systems that store conversations, messages, tool calls, and metadata with proper indexing and query patterns for production workloads.
Learn how to design RESTful APIs purpose-built for AI agent interactions, covering conversation endpoints, session management, structured payloads, and versioning strategies that keep agents running during upgrades.
Learn how to choose and implement the right streaming protocol for LLM applications. Covers Server-Sent Events, WebSockets, and HTTP chunked transfer with FastAPI code examples and error handling strategies.
Learn how to write effective JSON Schema tool definitions that help LLMs understand parameters, constraints, and expected inputs. Covers parameter types, descriptions, required vs optional fields, nested objects, and enums.
A practical guide to containerizing, deploying, scaling, and monitoring AI agents as microservices. Covers Docker, Kubernetes, health checks, and production observability.
Master disambiguation design patterns for conversational AI agents that present options clearly, narrow choices with follow-up criteria, and guide users to the right selection.
Build a comprehensive disaster recovery plan for AI agent systems covering backup strategies, RTO and RPO targets, automated failover, runbook design, and business continuity practices that keep your agents running through infrastructure failures.
