Hybrid search🕵️‍♂️ brings together the precision of lexical search and the intuition of semantic search. It uses both traditional scoring and vector similarity to surface the right results at the right time and help you build search that actually understands your data.

Context engineering VS prompt engineering: what's the difference?

Think of prompt engineering as writing the instruction, and context engineering as building the full environment so the AI can follow it.

Expose your Elastic agent and tools as an MCP server to integrate with your preferred client with Elastic Agent Builder, or build your own interface.

Build a custom tool for your agents with Elastic Agent Builder.

Next demo: Agent Builder and MCP

All you need is a natural language agent definition, and you have a custom AI assistant to help you talk to your Elastic data thanks to Agent Builder.

Elastic Observability is using unsupervised ML + GenAI assistants to turn logs into real-time incident response intelligence. Walk through a step‑by‑step investigation that detects anomalies, surfaces root causes, measures user impact, and accelerates remediation.
www.elastic.co/observabilit...

Follow along to create a custom agent with Elastic Agent Builder.

Next demo: How to create custom tools

Want to chat with your data? Pick an index and walk through this step-by-step notebook to create a tool and build an agent in 10 minutes with Elastic Agent Builder: github.com/elastic/elas...

Introducing Elastic Agent Builder, designed to give your agents the best context and tools. Build precise agents fast, connect all your data where it already lives in Elasticsearch, and create custom tools for any use case.

Learn more: www.elastic.co/search-labs/...

👋 Welcome to Elastic Dev — your new go-to for hands-on demos, cheat sheets, concept explainers & more. Get the latest on search, data & GenAI straight from the source.

Expect:
- Practical demos & how-tos
- Posts & technical deep dives
- Open source updates
+ more

Ready, set, build. Hello, world.