The Tool Desk
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An AI-agent front end should interpret a run, not wait for one finished response. Give the browser a typed event-to-UI contract that distinguishes progress, tool activity, handoffs, approvals, errors, cancellation, and completion. Keep that contract separate from both the agent runtime and the transport carrying its events. This is a practical architecture recommendation—not a measured recipe for AdTech scale.
Why an agent run needs more than a loading indicator
A conventional request often has a simple shape: send input, wait, render a response. An agent run can be a loop. The runtime may call a tool, transfer work to another agent, continue processing, and only then return a final result. Treating every streamed event as user-facing text hides what is happening and can make an unfinished run look complete.
OpenAI’s Agents SDK documents separate streamed event categories, including message output, handoff requests and completions, tool calls and outputs, reasoning items, and approval requests. Its streaming guide describes streaming as a way to update the interface before the final result is ready. The application should decide which events are useful and safe to show; the presence of an internal event does not make its raw contents appropriate for the user.
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What should the UI’s event contract contain?
Define an application-level contract that translates runtime activity into stable, user-understandable events and run states. The runtime can change its orchestration, and the wire protocol can change, without requiring every interface component to understand those internals.
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Represent lifecycle states explicitly
A useful starting model is queued, running, waiting for tool, waiting for approval, resumed, completed, failed, and cancelled. These are proposed application states, not a prescribed SDK enum. Map each transition to a stable event or server-side state update; do not infer completion merely because the connection stopped producing data.
Translate events into visible actions
| Run activity | UI interpretation | Design consideration |
|---|---|---|
| Progress or message output | Show a concise status or a user-facing partial result. | Distinguish partial output from a completed answer. |
| Tool call or tool output | Show that a named action is underway or has returned. | Render only details appropriate for the user; avoid dumping raw payloads by default. |
| Handoff request or completion | Indicate that work is being transferred or has returned. | Expose the useful transition without making the user follow internal orchestration. |
| Approval request | Present the pending action and an explicit approve or reject choice. | Keep the run visibly paused until a decision is applied. |
| Failure, cancellation, or completion | Show a distinct terminal outcome. | Do not collapse these outcomes into one generic stopped state. |
If you need a starting point for the contract, use an event envelope with a run identifier, event type, sequence or ordering information, and a typed payload. This is an application design proposal, not a wire format specified by the cited SDK. Keep user-visible text separate from internal tool data and reasoning-related events.
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How should the front end handle approvals, cancellation, and reconnects?
Approvals
When an action needs approval, show what is pending and provide a clear approve or reject path. The documented SDK flow exposes interruptions and allows an application to make that decision and resume from run state. Model the pause as part of the run lifecycle rather than as an unrelated modal that can become detached from the run.
Cancellation
Cancellation is a lifecycle event, not merely a browser animation or a closed connection. The SDK guidance says to await stream completion and cleanup; where a turn remains unfinished, resuming from stored state may be appropriate. Show a cancelled state only after the server-side run outcome is known.
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Reconnects
A dropped browser connection does not, by itself, establish whether the agent run stopped. Keep connection status separate from durable run status. On reconnect, reconcile with the server before showing a result as complete or offering a resume action. The sources describe persistence and resume patterns, but do not prescribe a complete recovery architecture for an AdTech deployment.
How do orchestration, the UI contract, and transport fit together?
- Agent runtime: owns the agent loop, tool dispatch, and handoffs.
- Event-to-UI contract: defines the events and states the interface understands, including which information is safe to expose.
- Transport: delivers those events between server and browser.
Keeping these responsibilities distinct is an architectural inference from the documented event interface and protocol discussion. It helps contain change: a runtime or transport can evolve without making every UI component depend on its implementation details.
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Transport is a separate choice from the interface contract. OpenAI documents HTTP streaming and an optional Responses WebSocket transport; its JavaScript SDK describes connection reuse when desired and ordinary streaming when reconnecting between runs is acceptable. That is a vendor-specific capability description, not evidence that WebSockets outperform server-sent events (SSE) or are preferable for a particular traffic pattern.
Thoughtworks Technology Radar Volume 34, published in April 2026, describes AG-UI as an event-driven protocol for synchronizing agent and interface state over transports including SSE and WebSockets, and classifies it as Trial. The Radar also cautions that putting UI widgets alongside tools through MCP may reduce the need for a separate UI protocol in some designs. That Trial label is the Radar’s maturity classification, not a standards-body certification; check current maintenance, compatibility, and adoption before choosing it. See the Thoughtworks Technology Radar Volume 34.
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Which implementation approach fits the application?
The documented approaches offer different ownership boundaries, not a performance ranking. Choose based on who should own the runtime and state, which integrations already exist, and whether the interface needs a separate interoperability layer.
| Approach | What the source describes | Questions to evaluate |
|---|---|---|
| Application-owned runtime | OpenAI says its Agents SDK runs in the application and suits cases where the server owns deployment, tools, state, and approval decisions. | Does the application need direct control over runtime and storage? Does this fit its existing deployment, language, and observability needs? |
| Framework plus routing gateway | A Vercel guide dated June 17, 2026 describes AI SDK functions such as streamText and generateObject, and a Gateway handling authentication, routing, usage tracking, failover, and billing. The guide says these components are loosely coupled and can be used independently. |
How much provider flexibility, billing visibility, and operational ownership does the team need? Does the framework fit the application? |
| Separate interface protocol | Thoughtworks’ April 2026 Radar describes AG-UI as a Trial-stage event-driven protocol using transports including SSE and WebSockets. It notes that MCP approaches that package UI with tools may affect whether a separate layer is needed. | Is interoperability worth the translation layer? Is the protocol sufficiently maintained and compatible for the deployment, and do tools need to supply their own UI? |
These are vendor-documented capabilities and an editorial assessment of design trade-offs, not an independent endorsement or comparative test. The cited sources do not establish relative latency, throughput, or cost for these approaches.
What does high load change—and what must be measured?
For a high-load AdTech system, investigate connection management, admission control, queueing, backpressure, workload isolation, persistence, and operational visibility against the actual run pattern. Agent runs can vary in duration and in how often they invoke tools or wait for approval, so a stream that works for a short interaction may behave differently under sustained or bursty workloads.
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- Measure latency, throughput, concurrency, failure behavior, and cost in the specific deployment; do not infer capacity from an SDK event model.
- Test backpressure and queue behavior so slow consumers or long-running runs do not silently degrade other work.
- Track run state and terminal outcomes alongside transport health so operators can distinguish a failed run from a disconnected client.
The JavaScript Agents SDK documentation gives a default maxTurns value of 10. That is a per-run safety default, not a concurrency, throughput, or capacity limit. The cited materials provide no validated AdTech-specific latency, concurrency, throughput, availability, or cost figures. Set targets from workload definitions and deployment-specific tests instead of borrowing unsupported numbers.
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