Spin up an internal competitor-research dashboard that humans and agents both edit
Run a lead enrichment pipeline where one agent researches and another sends alerts
Self-host the platform on an air-gapped Kubernetes cluster with per-app permissions
Let a non-technical PM describe an app in English and have Second scaffold it
Local try-it currently requires an Apple Silicon Mac; Intel Mac, Linux, and Windows builds are not yet shipped.
Second is an open-source platform for building internal software at companies, with a focus on letting AI agents work alongside human teammates inside the same apps. The project is at the npx try-it stage, currently shipping for Apple Silicon Macs, with Intel Mac, Linux, and Windows listed as coming soon. The pitch is that most workplace tools were not designed for AI agents, so they end up either ignoring them or bolting them on. Second tries to treat agents as first-class users from the start. The basic idea is that a non-technical team member can describe an internal app they want, for example a competitor research dashboard or a lead enrichment pipeline, and Second builds it. Once the app exists, AI agents read and write to the same real-time MongoDB database as the human team, get tools that are scoped specifically to the app, and can run scheduled or long-running jobs in the background. Users bring their own agent runtime. Claude Code and Codex are supported today, and OpenCode is marked as coming soon. The README says you can switch runtimes and models per message or per app without restarting the conversation. Several agents can also run in parallel on the same app, for example one handling research while another sends alerts and a third does enrichment. The product targets two audiences. Teams get a no-code surface for building apps and a shared workspace where humans and agents collaborate live. Platform engineers get one-time workspace setup, draft and review and publish lifecycles, fine-grained permissions per app and per agent and per integration, audit logs, and the option to deploy on their own Kubernetes cluster, on-prem, or air-gapped. The license is Apache 2.0. The README also points enterprise customers toward a sales contact for SSO, runtime setup, cost management, and SLA support.
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