Bringing Visualizations to Life in Multi‑Agent Systems With Vega‑Lite
Learn how Databricks Agent Bricks, Unity Catalog Functions, and Vega‑Lite let multi‑agent systems return governed, portable visualizations instead of just raw tables.
I started a new chapter of my Agentic Engineering Patternw guide about anti-patterns - things NOT to do
So far I only have one: Inflicting unreviewed code on collaborators, aka dumping a thousand line PR without even making sure it works first https://t.co/rg6LVi9zkk
TLDR: Our coding agent went from Top 30 to Top 5 on Terminal Bench 2.0. We only changed the harness. Here’s our approach to harness engineering (teaser: self-verification & tracing help a lot).
The Goal of Harness Engineering
The goal of a harness is to mold the inherently spiky intelligence of a model for tasks we care about. Harness Engineering is about systems, you’re building tooling around the model to optimize goals like task performance, token efficiency, latency, etc. Design decisions
An up-to-date repository of interface components based on examples from the world of design systems, designed to be a reference for anyone building user interfaces.
In case you were wondering why to use https://t.co/UAlnEZ7IhK
Meet your new benchmark leader. It's 1000x faster than grabbing a VM from a warm pool (daytona, e2b). And 10000x faster than booting a VM (vercel, etc.)
Use the right tool for the job!
Also, 🫡 to the bro on HN who
✨ LangChain's Skills: give your agent specialized capabilities on-demand.
Skills work via progressive disclosure: specialized prompts are loaded only when needed based on the context.
🪶 You can easily develop and share skills across teams because they're super lightweight (a