> For the complete documentation index, see [llms.txt](https://docs.lingoql.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.lingoql.com/sub0/use-cases/ai-agents-and-automation.md). # AI agents and automation Sub0 fits AI products when you need agents to do real work, not just generate text. It gives agents a backend surface they can call safely, predictably, and at production speed. ### Why this matters Most AI products break at the execution layer. The model can plan, but it still needs a backend that can validate input, read and write data, call external systems, and trigger follow-up work. Sub0 gives you that layer without stitching together controllers, workers, schedulers, upload handlers, and socket servers by hand. ### What AI systems need from a backend #### Clear actions Agents work better when the backend exposes narrow, reliable operations. With Sub0, each resource defines one clear job, input shape, auth rule, and result shape. #### Safe execution Agents make mistakes. Your backend should catch them early. Sub0 helps you: * Validate payloads before work runs. * Protect resources with tokens and policies. * Limit what each action can do. #### Multi-step workflows Useful AI systems rarely stop at one API call. They fetch context, update state, call tools, queue follow-up work, and notify users. Sub0 handles that flow with [Action Chaining](/sub0/apis-abi/action-chaining.md), [Queueing](/sub0/apis-abi/queueing.md), [Cron Jobs](/sub0/apis-abi/cron-jobs.md), and [Webhooks](/sub0/apis-abi/webhooks.md). ### Building automation flows with Sub0 Sub0 is strong when an event should trigger a real business process. Examples: * A form submission creates a record, enriches it, and sends a follow-up email. * A support event creates a task, queues classification, and updates the customer thread. * A payment webhook verifies the event, updates state, and broadcasts the result. You define those flows in one backend system. That keeps the logic visible, repeatable, and easier to maintain. ### How Sub0 helps AI agents AI agents need tools they can call with confidence. Sub0 gives them a stable backend contract. #### Agents can read and act Agents can use Sub0 resources to: * Fetch records and filtered context. * Create or update data. * Trigger external API calls. #### Agents can continue work asynchronously Some tasks should not block the user. Use queues for heavy work, webhooks for inbound events, and cron jobs for scheduled checks. That lets an agent start work now and finish the rest in the background. #### Agents can react in real time When state changes, clients often need immediate updates. Sub0 can broadcast changes through [Websockets](/sub0/apis-abi/websockets.md), which is useful for copilots, dashboards, approval flows, and live operations tools. ### Real-world AI impact #### AI support copilot An agent can classify tickets, fetch account context, draft replies, and trigger escalations. Sub0 handles the protected reads, writes, queueing, and webhook callbacks behind that flow. #### AI operations assistant An agent can monitor events, detect failures, open remediation jobs, and push status updates. Sub0 provides the APIs, background execution, and real-time delivery layer. #### AI workflow builder An agent can turn a prompt into a business process that reads data, calls third-party services, and schedules follow-up actions. Sub0 gives that generated workflow a backend that already supports auth, validation, and execution primitives. #### AI internal tools A team can use agents to search records, update CRM data, summarize activity, and trigger internal automations. Sub0 keeps those actions structured and permission-aware. ### Why teams choose this approach Sub0 reduces the gap between an AI idea and a backend that can execute it. You do not need separate systems for: * Request handling * Background jobs * Scheduled tasks * External integrations You define the behavior once and let Sub0 run it. That is what makes AI features more shippable. ### Best-fit pattern Sub0 is a strong fit when your AI product needs all three: * structured data access * reliable tool execution * production workflow orchestration If your agent needs a backend it can interact with safely, Sub0 gives you that foundation. ### Keep going * [APIs (ABI)](/sub0/apis-abi.md) * [Practical Examples](/sub0/apis-abi/practical-examples.md) * [Speed up with Sub0 AI](/sub0/speed-up-with-sub0-ai.md) --- # Agent Instructions This documentation is published with GitBook. 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