Msty AI Blog
Product releases, playbooks, and practical AI guidance for teams and individuals building with Msty.
81 posts
Local AI's Open-Weight Resurgence
Open-weight models are becoming practical for coding, long-document work, and agent workflows. GLM-5.2 shows that local and self-hosted AI is closing the gap with frontier cloud models.
Make Msty Claw Work Your Way with Extensions
Extensions let you make Msty Claw your own with custom commands, workflows, tools, themes, views, and agent behavior built around how you work.
Msty Claw 0.10.0: Extensions Make Claw Yours
Msty Claw 0.10.0 introduces Extensions for customizing Claw with themes, commands, workflows, tools, and agent behavior, plus Settings Search, push notifications, and workflow polish.
One Model Hub: Manage Every Model in One Place
One Model Hub gives Msty Studio one place for provider setup, local model discovery, custom imports, new installs, and installed models.
Introducing Msty Nexus: One Runtime for Your AI Stack
Msty Nexus gives you one place to manage local and cloud models, provider credentials, presets, and app access.
Msty Studio 2.8.0: Discover Hub, One Model Hub, and Native Provider Tools
Msty Studio 2.8.0 adds Discover Hub, One Model Hub, provider-native tools, and reliability improvements across model and workflow management.
Msty Claw 0.9.0: Better Usage Insights, Folder Triggers, and Local Document Parsing
Msty Claw 0.9.0 adds a clearer usage view, folder-triggered Tasks and Playbooks, local document parsing, and everyday workflow improvements.
Msty AI Newsletter Edition 002: NVIDIA RTX Spark, Msty Nexus, and Claw 0.9.0
Msty AI Newsletter Edition 002 covers our NVIDIA RTX Spark collaboration, the Msty Nexus reveal, Claw 0.9.0, and upcoming Studio, Stack, and Law updates.
Introducing Rules: Make Msty Claw Work the Way You Do
Use Msty Claw Rules to automate repeated guidance, block risky actions, run checks, and trigger useful follow-up steps.
Msty AI and NVIDIA RTX Spark: Bringing Powerful Local AI Closer to Everyone
Msty AI has been working with NVIDIA on RTX Spark, a major step toward faster, more private, and more capable local AI workflows.
Msty Claw 0.8.0: Making Agentic Work Feel More Connected
Msty Claw 0.8.0 introduces Pulse, Side Chat, and Handoff to an Agent for better connected workflows.
Msty Claw 0.7.0: From AI Workflow Friction to Reliable Team Execution
Msty Claw 0.7.0 improves long-running execution reliability, standardizes team workflows with Skills Hub, and strengthens continuity across tools and devices.
Msty AI Newsletter Edition 001: Studio 2.7.4, Claw 0.7.0, and What's Next
Msty AI Newsletter Edition 001 covers Studio 2.7.4, Claw 0.7.0, and upcoming updates across Msty Stack and Msty Law.
Next Gen Knowledge Stacks: Turning Scattered Work into Living Context
Msty Studio Next Gen Knowledge Stacks connect files, conversations, links, and projects so teams can make faster decisions with reliable context.
Media Studio: From Prompt to Asset
Msty Studio 2.7.0 introduces Media Studio, a connected workspace for creating, reviewing, refining, and reusing AI-generated images and videos.
Introducing Msty Claw: Give AI a Task and Let It Work
Msty Claw is a privacy-first AI task automation app that lets you delegate multi-step work, control access, and review structured outcomes.
Memory That Stays Useful: Why Msty Claw Uses Memory Packs
Most AI memory systems get noisier over time. Msty Claw uses modular Memory Packs so context stays focused, reusable, and optional.
Crew Conversations: AI Teamwork With More Control and Faster Outcomes
Crew Conversations in Msty Studio give you the feel of a real team meeting with AI experts, clearer control, and faster execution against real objectives.
Persona Studio: Build and Test Personas With Precision
Persona Studio gives teams a controlled way to design, test, and scale personas so AI behavior stays consistent while governance stays intact.
User Personas in Msty Studio: Personalization That Stays Consistent
User Personas help Msty Studio adapt AI behavior to your current role and context so output stays consistent across work and personal modes.