Runtime

Product Introduction

1. Definition: Runtime is a multi-agent orchestration and sandboxing platform designed to operationalize AI coding agents within enterprise workflows. It functions as a secure, policy-driven runtime environment for models like Claude Code, Cursor, and Codex.
2. Core Value Proposition: Runtime exists to enable non-engineering teams (e.g., Product, Marketing, Support) to safely and effectively leverage AI coding agents as teammates, while providing engineering and platform teams with the necessary guardrails, observability, and cost controls. Its primary value is turning coding agents from isolated developer tools into governed, collaborative, and context-aware assets integrated into tools like Slack, Linear, and GitHub.

Main Features

1. Pre-Warmed, Snapshotable Sandboxes: Runtime provides isolated, containerized environments that can be pre-configured with a company's specific toolchain, CLIs, APIs, internal packages (e.g., @acme/ops-cli), and MCP servers. These environments are snapshotted for fast boot times (seconds) and ensure agents operate within a controlled, reproducible context. Tools are installed via standard package managers like mise, brew, npm, and github.
2. Multi-Agent Orchestration & Proactive Automation: The platform allows the creation of specialized, named agents (e.g., @runtime-finance, an "alert-inspector" for #incidents). These agents can be triggered on-demand via @mentions in Slack or Linear, or configured to run proactively by monitoring channels for specific events. They autonomously conduct investigations, generate PRs, draft replies, and post findings.
3. Unified Mission Control & Real-Time Collaboration: A central dashboard provides live visibility into all active agent sessions, including tool calls, chain-of-thought, file changes, and real-time cost tracking. Multiple users can collaborate within a single live session, view a shared preview, and hand off work, enabling cross-functional teamwork between engineering, product, and design.
4. Enterprise Guardrails & Observability: Runtime enforces granular security and operational policies. This includes spend limits per agent/user/team, file access allowlists/denylists, approval gates for sensitive actions, and comprehensive audit logs. All data access is scoped to sandboxed mirrors or samples with PII redaction; production writes occur only through reviewed PRs or defined actions.
5. Extensive Native Integrations: The platform ships with first-class connectors for critical enterprise systems: data warehouses (Snowflake, BigQuery), billing (Stripe, NetSuite), HRIS (Rippling, Workday), CRM (Salesforce, HubSpot), observability (Datadog, Sentry), and engineering tools (GitHub, Linear, Jira). This allows agents to operate within the full company context.

Problems Solved

1. Pain Point: The high barrier and significant risk of deploying generative AI coding agents beyond a small group of expert engineers. Companies struggle with providing secure, governed access to company data and systems, managing unpredictable costs, and enabling non-technical teams to leverage automation.
2. Target Audience: Platform/Engineering Teams who need to safely roll out AI agent infrastructure; Product Managers turning PRDs into prototypes; Marketing Teams needing on-demand growth engineering; Support Teams querying data and automating triage; Finance & People Teams building internal dashboards and automations without engineering dependencies.
3. Use Cases: Automatically investigating and diagnosing a dbt_scheduled_core failed alert posted in a Slack channel; a sales team member asking a finance agent in Slack for a custom prospect report; a product manager tagging an agent in a Linear ticket to build a feature prototype; collaborative, real-time web copy iteration between marketing and design using a live preview sandbox.

Unique Advantages

1. Differentiation: Unlike standalone AI coding tools (e.g., Cursor, Devin) built for individual developers, Runtime is an enterprise-grade orchestration layer. It focuses on multi-user collaboration, cross-functional accessibility, and centralized governance, whereas competitors are single-player and lack built-in guardrails. It also differs from low-code platforms by providing the full power of code-level agents within a safe sandbox.
2. Key Innovation: The concept of "snapshotable team sandboxes" combined with proactive, channel-aware agents. This allows a company to codify its entire development environment and operational knowledge once, then deploy specialized agent "teammates" that can work autonomously in the communication channels where work already happens (Slack, Linear), dramatically reducing the activation energy for AI-driven automation.

Frequently Asked Questions (FAQ)

1. How does Runtime handle data security and prevent agents from accessing sensitive production data? Runtime agents operate exclusively within sandboxed environments that contain mirrored, sampled, or redacted data, governed by row-level security scopes and PII redaction policies. Agents cannot directly write to live production systems; all changes are made through reviewed pull requests or pre-approved, audited actions.
2. Can Runtime coding agents be used by non-engineers, and how do they interact with them? Yes, Runtime is specifically designed for cross-functional use. Non-engineers interact with agents through natural language in tools they already use, like Slack or Linear. They can @mention a team-specific agent (e.g., @runtime-support), ask a question or assign a task, and the agent will execute the work, reply with findings, and provide an "Open Session" button for deeper collaboration if needed.
3. What is the cost model, and how does Runtime control spending on AI agents? Runtime provides granular, real-time cost tracking per session, agent, user, and team. Platform administrators can set hard spend limits and configure approval gates for high-cost operations. This prevents runaway costs from unconstrained AI model usage, a common concern with direct API-based implementations.
4. Is Runtime a hosted service or can it be self-hosted on our own infrastructure? Runtime offers both a cloud-hosted SaaS version and a self-hostable enterprise deployment. The self-hosted option allows companies to run the entire platform within their own VPC, using their own cloud resources, AI models (e.g., private Azure OpenAI endpoints), and secret management, ensuring full data sovereignty and control.