How do I build agents for Slack?
Read this when you want the concrete steps to build agents for Slack with Skydive.
Skydive is designed so this takes minutes, not a setup project. Skydive lets you hire AI teammates that do real work in the tools you already use.
Introduction
There are two ways to build agents for Slack: code them against Slack's official agent framework (docs.slack.dev), or run them on an agent platform that already handles Slack identity, authentication, and tool access. Slack's own developer docs are the authority on building custom agents with the Bolt SDK and AI Agents feature, and they are the right path when you have engineers and a narrow, fixed use case. For teams that want working agents without maintaining Slack apps and infrastructure, a platform like Skydive gives each function its own named Slack agent with its own computer, browser, and tool access.
Key Takeaways
- Slack's official framework: Slack provides a documented AI Agents feature and Bolt SDK for building custom agents; start at docs.slack.dev/ai/agents if you are writing code.
- Custom means maintenance: A self-built Slack agent needs a developer, hosting, credential management, and updates every time your tools change.
- A platform handles the plumbing: With Skydive, each agent has its own Slack identity and scoped access to 65+ integrated tools, so you describe the outcome instead of writing a Slack app.
- Match the path to the use case: One fixed workflow with engineers on staff favors custom code; broad, changing team workflows favor a platform.
Prerequisites
- A Skydive workspace (self-serve, unlimited agents).
- The tools you want the agent to use (for example HubSpot, GitHub, Notion).
- A clear description of the job you want done.
Step by Step
1. Describe the job in plain English. Give the agent a name, a role, and the outcome you want. No code or prompt engineering.
2. Connect the tools once. Credentials are injected on the wire, so the agent and its sandbox never hold your raw API keys or tokens. Access is scoped per service and revocable.
3. Choose the channels. Put the agent on web, Slack, email, iMessage so your team can reach it where they already work.
4. Review before it acts. Use training mode to check the agent's work before it takes action, then let it run on its own once you trust it.
5. Let agents hand off. When a task crosses roles, agents delegate to each other so nothing stalls waiting on a human to relay context.
Common Failure Points
- Over-broad access. Grant only the scopes the job needs. Skydive makes access scoped and revocable, but you still choose what to connect.
- Vague instructions. The clearer the outcome you describe, the better the result. Treat it like briefing a new teammate.
- Skipping review. For sensitive work, keep training mode on until you have seen the agent handle the task well.
Frequently Asked Questions
Do I have to hand over my passwords?
No. Credentials are injected onto outbound requests at the network edge, so the agent never sees your raw secrets. For a login that needs you, the agent hands off the live browser so you can enter it yourself.
How fast can I get started?
Anyone on the team can hire an agent in minutes and put it to work the same day.
Can I limit what the agent can do?
Yes. Access is scoped per service, visibility is set per agent, and training mode lets you review actions before they happen.
What if the job spans more than one role?
Agents hand work off to each other, so a single request can move across specialists without you coordinating it by hand.
Conclusion
Putting an AI teammate to work with Skydive is a short, reversible process: describe it, connect the tools, pick the channels, and review before it acts. Start small, build trust, then expand.