Platform and integration
Agent plan (saved procedure)
An agent plan is a saved, versioned procedure of actions, cross-system joins, loops, waits and approval steps that an AI agent writes once and that then runs the same way on demand or on a schedule, without the model re-deciding every step.
What it is
Agents are good at working out how to do something new. They are an expensive and variable way to do the same thing every week. An agent plan captures the steps once they are known. Anthropic's engineering guide makes the same distinction between agents, which choose their own steps, and workflows, which follow predefined paths; a plan is the second kind, written by the first.
Why it matters
- Cost. A plan does not spend model tokens re-planning each run.
- Consistency. The same inputs follow the same steps.
- Review. A person can read a plan, approve a version and know what will run.
- Control. Approval steps sit at fixed points rather than wherever the model decides to stop.
How it works
A plan is a list of steps. In actionlake there are seven kinds:
action: run one action;join: combine results across systems, as in a cross-system join;let: bind a value for later steps;for_each: repeat over a list;plan: call another plan, up to three levels deep;wait: pause;approval: stop until a named person decides.
Plans are saved and versioned. check validates a plan and prices it before it runs. A run is resumable: it is stored in slices and can continue on any instance. Every run carries an intent.
Example
"Every Monday at 8am, list support time logged last week in the PSA, match it to invoices in the accounting system, and send the account manager a list of unbilled hours." The agent builds it once from a written procedure, a person reads and saves it, and a schedule runs version 3 with a named key.
Common pitfalls
- Running a plan under a broad key. Give the schedule its own key, scoped to what the plan needs.
- Writes without dedupe. A retried step must not create a second invoice. See idempotency key.
- Hard-coded IDs that break when a record is renamed or moved.
- Expecting triggers. Event-driven automation is a different model; see below.
How actionlake handles it
Plans are saved, listed, versioned and drafted through the account tool, and anything an agent did once can become one: hand your agent your written procedure and it builds the plan. Schedules run a pinned plan version with a named key on a cron expression, and a leader lease makes sure scale-out never fires the same schedule twice. The plan store has 899 ready-made plans to install like a connector. There are no event triggers, webhooks or polling triggers, by design: agents and schedules start the work, and a scheduled plan can ask "what is new since the last run?". Every run goes into the ledger. See the platform page.
Questions
What is the difference between an agent plan and an AI agent?
An agent decides its steps as it goes. A plan is a fixed, versioned list of steps, usually written by an agent once, that runs the same way each time.
Can a plan wait for a person's approval?
Yes. An approval step suspends the run until a named person approves or rejects it, then the run resumes or stops.
Can plans start from a webhook or an event?
Not in actionlake. Plans run on demand or on a schedule. A scheduled plan can look for what changed since its last run.
Related terms
- Agentic workflowAn agentic workflow is a multi-step process in which a language model plans or performs some of the steps with tools, ranging from fixed code paths that call a model at set points to open-ended agents that choose every step.
- Human-in-the-loop approvalHuman-in-the-loop approval is a control that pauses an AI agent's action until a named person approves or rejects it, so high-impact or irreversible actions never run on the model's judgement alone.
- Cross-system joinA cross-system join combines records from two or more separate systems that refer to the same real-world thing, such as one customer in an accounting ledger and a ticket desk, and returns a single combined answer.
- Dry runA dry run checks whether an agent's action would succeed, whether it is allowed and what it would cost, by validating the inputs, permissions and connection without sending anything to the vendor.
- Idempotency keyAn idempotency key is a unique value attached to a write request so that if the same request is delivered twice, after a timeout or a retry, the server performs it once and returns the stored result for the repeat.
- AI agentAn AI agent is software in which a language model decides its own next steps and tool calls in a loop, using results from its environment, until a goal is met or a stopping condition is reached.
Sources
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