A product discussed on AI Engineer.

Stop AI Agent Hallucinations: 5 Techniques + Production Patterns - Elizabeth Fuentes, AWS
Jul 11, 2026 · 55:19
Elizabeth Fuentes (AWS) presents five code-based techniques to stop AI agent hallucinations, each with measurable before/after metrics. Semantic Tool Selection filters 29 tools to the 3 most relevant per query, cutting token usage from thousands to under 300 per call. Graph-RAG replaces vector similarity with structured graph queries (using Neo4j), enabling precise aggregation and multi-hop reasoning that vanilla RAG fabricates. Multi-Agent Validation uses an Executor-Validator-Critic swarm to catch fabrications, achieving a 92% detection rate. Neurosymbolic Guardrails enforce business rules in Python hooks that the agent cannot skip, achieving zero rule violations. Agent Steering guides agents to self-correct when soft rules fire, completing tasks without hard failures—demonstrated by booking 50 guests by intelligently splitting into two rooms.

Spec-Driven Development: Agentic Coding at FAANG Scale and Quality — Al Harris, Amazon Kiro
Jan 9, 2026 · 1:03:50
Al Harris, principal engineer at Amazon, presents Spec-Driven Development (SDD) with Kiro, an agentic IDE that transforms prompts into structured requirements (EARS format), designs, and property-based tests to ensure code correctness. He argues that upfront specification—augmented by MCP servers for external context—improves reproducibility and quality over pure vibe coding. The talk includes a live demo: building an S3-backed checkpointer for a LangGraph dad joke generator, then discovering Agent Core’s native memory is more idiomatic. Harris contrasts SDD with Cursor’s planning mode, explains how specs evolve as living documentation, and discusses handling session length, context pruning, and brownfield codebases. The result is a claim that spending 5–10 minutes on specs yields higher accuracy and reliable, testable outputs.

Claude plays Minecraft!
Feb 15, 2025 · 18:16
Derek from AWS demonstrates building Rocky, an autonomous Minecraft agent using Amazon Bedrock, Claude 3 Haiku, and serverless AWS services, proving agentic workflows enable AI to reason and act beyond chatbots. He explains the architecture: Minecraft server on ECS with Mineflare bot framework, agents for Bedrock with return of control, and prompt engineering for tasks like digging and building. In a live demo, Rocky jumps, finds players, digs a hole, and builds a double-decker couch from a chat command, inferring parameters from natural language. The code is open-source and built with CDK/CloudFormation, emphasizing that agentic AI can operate in complex 3D environments through tool orchestration and managed prompt design.
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