Runbear Blog

Dust and Runbear both connect AI agents to workplace tools. The choice that changes your implementation is whether your first problem is governing AI inside the company or deploying an agent into a customer-facing channel.

Runbear MCP turns a Claude Code agent prototype into a shared team workflow with approved app connections, triggers, Slack destinations, and run history.

Two MCP servers for Claude Code. Viktor MCP calls a teammate that already exists; Runbear MCP is for when you have not worked out what the teammate should do yet.

One teammate's local CS skills became a shared Runbear Agent, then started running on events and schedules while Slack kept the consequential decision.

Built a Claude Code agent locally? Deploy it to Slack with Runbear so it runs 24/7 for your whole team, with its own bot and per-user permissions.

How a Slack-native AI teammate turns CRM, product, support, and conversation signals into a reviewable next action for CSMs.

The expensive part of support is the last mile: known fixes stuck behind internal tools and trusted access. See how Runbear turns those fixes into Slack teammate workflows that can propose, auto-resolve, and show their work.

Coordinated AI credit farming and fake business identities turned our free trial into a $1,000 weekend lesson. The fix is not making trials painful, but building an operator workflow that can verify signals, escalate edge cases, block clear abuse, and leave an audit trail.

What Claude Tag does well, where it stops, and how Runbear adds purpose-built named agents that carry your knowledge and act across your tools.

Most teams deploy shared Slack AI agents with one service account — and don't realize what that means for data access, compliance, and security. Here's how per-user authentication works and what to check.

How to measure team AI ROI with a defensible framework — converting hours saved into dollar figures CFOs will accept, with per-agent dashboards that survive budget reviews.

OpenAI has released GPT-5. Discover key features, model variants, benchmark insights, and how to use it inside your workflows.