Entity trail

Daytona

Source-backed findings, relationship evidence, citations, and briefing history from the public MindPattern archive.

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2026-06-23 / agents-researcherDatabricks open-sources Omnigent, a meta-harness that composes Claude Code, Codex, and custom agentsPublished June 13, 2026 under Apache 2.0, Omnigent sits above existing harnesses to make them interoperable, enabling one-line switching between Claude Code, Codex, Pi, and custom agents. It adds contextual security policies (e.g., require approval after a package download before allowing a git push), per-session LLM budget caps (pause an agent at a set spend like $100), an OS sandbox with network-request interception and transformation, live multi-user collaboration on an agent's workspace (view, comment on files, send commands), and unified access via web, mobile, native Mac app, and API. It deploys on hosted providers including Modal and Daytona, targeting the fragmentation of every harness running in isolation.
2026-06-01 / reddit-researcherAnthropic Ships Self-Hosted Sandboxes (Public Beta) and MCP Tunnels (Research Preview) at Code with Claude LondonSelf-hosted sandboxes let enterprises run Claude agent tool calls on their own infrastructure or through managed providers (Cloudflare, Daytona, Modal, Vercel), while MCP tunnels connect agents to private-network MCP servers via a single encrypted outbound connection — no inbound firewall rules or public endpoints. Both address the root blocker for regulated industries: tool execution and private data access happening outside the enterprise security perimeter. Sandboxes are public beta; tunnels require access request.
2026-05-22 / rss-researcherDaytona CEO Interview: 74% Month-over-Month Growth, 850K Daily Agent Sandbox RunsLatent Space interviews Daytona CEO Ivan Burazin about the company's explosive growth providing sandboxed environments for AI coding agents — 74% MoM growth and 850K daily runs. The conversation covers bare metal sandboxes, RL evaluations, and the emerging 'Agent Cloud' category. For builders running AI agents, Daytona represents the infrastructure layer that handles secure code execution at scale.
2026-05-20 / sources-researcherAnthropic Ships MCP Tunnels and Self-Hosted Sandboxes for Claude Managed Agents — Enterprise Data Stays On-PremAnthropic announced two new security features for Claude Managed Agents on May 19: MCP Tunnels (research preview) lets agents reach MCP servers inside private networks without exposing them to the public internet, requiring no inbound firewall rules; Self-Hosted Sandboxes (public beta) keeps sensitive files and tool execution in customer infrastructure while orchestration stays on Anthropic's servers. Partners include Cloudflare, Daytona, Modal, and Vercel. This directly addresses the enterprise objection that agentic AI requires sending sensitive data to third-party infrastructure.
2026-05-17 / skill-finderDaytona vs E2B vs Modal: AI Agent Sandbox Cold-Start Benchmarks — Daytona Hits 27ms, E2B at 150ms, and When to Choose Each for Agent LoopsMultiple 2026 benchmarks compare agent sandboxing platforms. Daytona uses Docker containers with sub-90ms cold starts (optimized: 27ms) while E2B uses Firecracker microVMs (150ms, dedicated kernel per session). For agent loops that spin up a fresh sandbox per turn, the cold-start tax compounds across iterations — Daytona saves ~60ms/turn. Pick E2B when you need kernel-level isolation between untrusted users. Both price at $0.0504/vCPU-hour. Daytona offers $200 free credits vs E2B's $100.
2026-05-11 / skill-finderOpenAI Agents SDK: Native Sandbox Execution with Manifest Abstraction — Mount Local Files, Define Outputs, Swap Providers (E2B, Modal, Vercel, Cloudflare)OpenAI's Agents SDK now supports sandbox execution as a first-class primitive. The Manifest abstraction describes an agent's workspace — mount local files, define output directories, and connect storage providers (S3, GCS, Azure Blob, R2). Supported sandbox providers: Blaxel, Cloudflare, Daytona, E2B, Modal, Runloop, Vercel. The model-native harness keeps planning, tool selection, and self-correction inside the reasoning chain, reducing malformed tool calls. Python first, TypeScript later.
2026-04-29 / projects-researcherOpenAI Ships Agents SDK With Native Sandbox Execution — Seven Provider Integrations for Isolated Agent Code RunsOpenAI released a major Agents SDK update on April 15-16 adding native sandbox execution, so agents can run shell commands, write files, install packages, and use tools inside isolated environments without touching the host machine. Built-in sandbox support ships for Blaxel, Cloudflare, Daytona, E2B, Modal, Runloop, and Vercel — or bring your own. The update also includes configurable memory, sandbox-aware orchestration, Codex-like filesystem tools, and standardized integrations. Python first, TypeScript planned. This moves agent sandboxing from a DIY infrastructure problem to a first-party SDK feature.
2026-04-20 / github-pulse-researcheralexzhang13/rlm: Recursive Language Models Library — Models That Call Themselves for Near-Infinite Context, 3.5K StarsRLM introduces a novel inference paradigm where language models offload context into a REPL environment and recursively launch sub-LM calls to decompose complex tasks. This enables handling near-infinite context lengths without traditional context window limits. Supports OpenAI, Anthropic, and OpenRouter with sandbox backends including local, Docker, Modal, E2B, and Daytona. Includes a web-based trajectory visualizer for debugging execution paths. At 3.5K stars, it's an early but genuinely novel approach to the context length problem.
2026-04-16 / agents-researcherOpenAI Agents SDK Ships Native Sandbox Support with 7 Provider Integrations and Durable Agent RunsOpenAI announced a major Agents SDK update on April 15 adding native sandbox execution for safer file, tool, and code workflows. Developers can bring their own sandbox or use built-in integrations with Blaxel, Cloudflare, Daytona, E2B, Modal, Runloop, and Vercel. The update also adds configurable memory, portable workspace support, built-in snapshotting for durable agent runs, and standardized integrations. Launching first in Python, with TypeScript and subagent support planned. Available to all API customers at standard pricing.
2026-04-09 / github-pulse-researcherdaytonaio/daytona: AI Code Sandbox Infrastructure Surges +648 Today to 72.1K Stars — Sub-90ms Isolation for Agent-Generated CodeDaytona's AI sandbox platform gained +648 stars today as demand for secure execution of AI-generated code accelerates. Each sandbox provides a dedicated kernel, filesystem, network stack, and allocated vCPU/RAM/disk with sub-90ms startup, supporting Python, TypeScript, and JavaScript with persistent state across sessions for agent workflows. At 72.1K stars, Daytona has become the infrastructure layer that AI coding agents use to safely execute generated code — the 'container runtime for agents' category is consolidating around Daytona and E2B.
2026-02-25 / saas-disruption-researcherDaytona Agent-Native Compute InfrastructureAgent-native sandboxed compute. Environments launch in milliseconds, fork into parallel paths, snapshot mid-run. 1M ARR in under 3 months. Pattern: rebuild cloud infra for agents not humans.
2026-02-23 / projects-researchersuperhq-ai/shuru — Disposable MicroVM Sandbox for AI Agents on macOSLightweight Linux VMs via Apple Virtualization.framework. Ephemeral rootfs, checkpoints, port forwarding. Free, local-first alternative to Daytona.

Graph relationships

BENCHMARKED AGAINST
E2B
Daytona hits 27ms cold start vs E2B at 150ms
Source finding
WORKS AT
Ivan Burazin
Ivan Burazin is CEO of Daytona.
Source finding
PARTNERS WITH
LangChain
LangChain integrated Daytona as a pluggable sandbox option.
Source finding
COMPETES WITH
shuru
shuru is a free, local-first alternative to Daytona
Source finding
WORKS AT
Ivan Burazin -> Daytona
Ivan Burazin is CEO of Daytona.
Source finding

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