Discover the latest news, updates, and articles from the team and community.
Platform teams are responsible for production. Every other team wants to build its own tools with AI. An AI Session builds internal software with your whole workspace as context, within your permissions, and ships it through your deployment pipeline.
How is dbt actually orchestrated, and why does running it as one job beat one task per model? A primer on dbt as a compiler with a scheduler attached, the five ways teams wrap it, and why both Dagster and astronomer-cosmos converged on a single dbt invocation with per-model state projected out of it.
How does Windmill automate its own support? A Windmill pipeline funnels Discord, Slack and email tickets into one Discord queue, triages them with Claude, drafts replies, and dispatches fixes.
Before we shipped a single line of AI Sessions, we had already spent months supervising AI coding agents on our own codebase, through Webmux, the open-source dashboard we built for ourselves. Here is how that daily use shaped the product.
How do I automate Windows servers without Docker? Windmill runs natively on Windows as a service with PowerShell, C#, MSSQL Kerberos auth, and Teams integration.
How do I build an AI Discord bot that accesses Stripe without leaking API keys? Use Windmill sandboxed tools to give the AI capabilities, not credentials.
Introducing workflow-as-code: define complex workflows in TypeScript or Python with checkpointing, parallelism, and fault tolerance built in.
Introducing improved Git sync and workspace forks: sync workspaces to Git, fork for feature development, and deploy via CI/CD.
Introducing AI sandboxes: run Claude Code, Codex, or custom agents in isolated environments with persistent volumes on Windmill.