Make AI Agent (New) connects an agent to tools, scenarios and knowledge inside the visual Scenario Builder. It is better understood as a configurable workflow component than a universal autopilot. Its documentation marks the new app as open beta, so exact entitlements and feature flags need a dated check against the tenant.
How it works
The official reference describes an agent module, supporting connections, tool selection, knowledge files, conversation context and third-party MCP tools. A scenario can become a callable tool with defined inputs and outputs. A module may read information or produce a side effect, so scope each tool carefully. Make’s docs distinguish the Make AI provider path from external model-provider connections and warn that product functionality and pricing can change during beta; a presently visible setting does not demonstrate availability for all regions or every old plan.
A practical, bounded workflow
Build a controlled document-intake scenario: verified webhook receives metadata, antivirus and file-type checks run first, a tool extracts a proposed document type and fields, and an ordinary router sends the structured result to a reviewer. After approval, a dedicated record-writing module creates a draft and then retrieves the new record to verify state. Use an explicit schema for document fields so the model cannot invent unsupported property names or destinations.
Failure modes and limits
Scenario complexity can obscure which module performed a write. Nested agent tools also risk re-entering the same scenario, exhausting credits or creating a recursion loop. Put depth, tool-call and duration ceilings outside model instructions. Treat a changed public tutorial as a signal to retest beta behavior, not proof that historical workflows used that configuration.
Deployment controls
Regardless of the vendor interface, define a deployment policy for tool scopes, input trust, required approvals, call limits, credential ownership and audit retention. Grant read operations separately from externally visible writes; require a deterministic controller to validate tool arguments. A natural-language system prompt is useful guidance, not the security boundary.
When to choose this approach
Use Make when its visual editor and mature module ecosystem reduce integration effort. If a task has fixed conditions and transformations, use a standard scenario with no agent at all. Keep AI 10 responsible for numeric plan/credit snapshots; this guide does not reproduce transient beta pricing, annual discounts or inferred enterprise availability.
What to evaluate before production
Measure field accuracy, rejected document rate, human review effort, tool invocations per file and total end-to-end latency. Feed in duplicate webhook events, empty files, malformed JSON and revoked credentials; verify that no model-generated value bypasses validation or writes to an unauthorized app connection.
Version, market and tier caution (25 October 2026): This is a technical and operational guide, not a live entitlement, pricing or geographic-availability certification. Numeric commercial limits and undocumented release dates are intentionally omitted. Reconfirm the exact account, deployment region, access policy and vendor release before procurement or publication.