A personal AI assistant can mean a conversation, a bot with connected tools or an automation you maintain. The useful choice depends on what happens after the answer. Start with your actual work and the decisions you want to keep.

Choose by the responsibility, not the label

For occasional questions, a conversation may be enough. For recurring follow-up, check whether the tool can revisit a responsibility without a fresh prompt. For a fixed sequence of steps, consider whether a conventional automation gives you clearer and more predictable control.

If the work often becomes a code change, examine the handoff. Ask where the coding agent runs, where its history appears and how you review its actions. A useful evaluation follows one complete task through to a decision you can inspect.

Look for a useful connection between conversation and action

Canopy combines personal bots with coding Threads. A bot can read granted connected accounts, start a coding task and follow its result. The Thread shows the agent's work, while relevant approvals also appear in the bot conversation. This keeps the handoff visible.

That combination fits a project brief that uncovers a bug, or a routine that sends a clear issue for investigation. A coding-only task can start directly in Threads. You do not need a bot in front of every instruction.

Evaluate account access and attention costs

List the accounts a recurring responsibility actually needs. Canopy supports named connected accounts with grants for selected bots and workers. A work account can stay separate from a personal account. External services may still require applications, tokens or administrator approval.

Then choose what deserves an interruption. Canopy routines can send messages according to your instructions while keeping background narration out of the conversation. Questions and approvals remain visible. Your first useful trial should include an action the bot must ask you to approve.

Include the operating requirements in your decision

Canopy can run locally in Desktop or on your own server, with workers executing harnesses. You connect a provider, such as Claude Code, Codex or Grok, through its official agent tool. Self-hosting gives you control of Canopy's services; it does not imply that a model runs locally.

Routine execution needs an available home gateway and assigned worker. Linked desktop apps can share configuration and readable history, but do not synchronize project files. A phone can use configured web access; native mobile apps are coming soon. Include these requirements in your trial.