Three Infrastructure Tools Just Dropped for Production AI Development
Visual workflows, agent analytics, and secure smart contracts — the boring middleware finally arrives.
Three Infrastructure Tools Just Dropped for Production AI Development
Three fresh infrastructure tools just launched that solve critical gaps in the production AI development stack.
CC Workflow Studio brings drag-and-drop visual workflow design directly into VSCode for orchestrating multi-agent systems. Design complex agent interactions on a visual canvas, edit with natural language through Claude, Copilot, or Cursor, then export and run with one click. Finally, a proper visual editor for the multi-agent workflows everyone's building.
Hodoscope provides unsupervised learning analysis of AI agent behavior — the analytics tool for understanding what your agents actually do. It summarizes, embeds, and visualizes thousands of agent trajectories to discover unexpected patterns across different models and configurations. Essential for anyone running agents at scale who needs to understand behavioral drift.
Safe Solana Builder generates security-first Solana smart contracts with built-in vulnerability protection and audit trails. This Claude skill loads security knowledge into context to produce hardened programs with complete project scaffolds, security checklists, and pre-identified edge cases for both Anchor and Native Rust frameworks.
Each tool fills a specific hole in the production AI stack that developers have been working around with manual processes. The infrastructure layer for AI development is finally getting the boring, essential tooling it needs.
Featured Tools
Safe Solana Builder
A Claude skill that writes production-grade, security-first Solana programs with built-in vulnerability protection. It generates complete project scaf
CC Workflow Studio
A Visual Studio Code extension that provides a drag-and-drop workflow editor for designing AI agent orchestrations. Create and manage multi-agent work
Hodoscope
An open-source tool for analyzing AI agent behavior through unsupervised learning. It summarizes, embeds, and visualizes agent trajectories to help re
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