A deprecated AI endpoint needs a migration plan grounded in current official guidance, not an old tutorial that still shows working legacy calls. Perplexity can help locate the right documents, but a migration brief should connect the shutdown status to your application’s features and stored data. This workflow prepares a precise, testable transition plan.
Primary product documentation checked on 8 October 2026. The worked examples are fictional editorial examples, not claims of hands-on testing inside Gemini or Perplexity.
Identify the deprecated dependency exactly
Record endpoint path, SDK method, model identifiers, API version where relevant, and the application features that use them. Search the code and configuration when authorized access is available. A product name alone may hide several dependencies with different timelines. Separate deprecated models from deprecated endpoints and libraries.
In a fictional application, the team used the Assistants API for conversation state and tool execution. Current OpenAI migration guidance checked on 8 October 2026 states that the Assistants API was sunset on 26 August 2026. The brief must treat that as a completed shutdown, not a future deadline, and avoid planning around legacy retrieval calls that are no longer available.
Locate the current official migration route
Ask Perplexity to find the vendor’s deprecation notice, migration guide, replacement reference, and relevant SDK documentation. Open those sources and record checked dates. Verify that the guide describes the replacement currently recommended, because migration documents can themselves contain transitional objects with later deprecation notices.
OpenAI’s current Assistants migration guide directs integrations toward the Responses API and discusses conversation state. Use it alongside the current deprecations page and replacement references. Do not copy an old code example merely because it appears inside a migration article; inspect whether the surrounding text describes a historical pre-shutdown path.
Map features and data to the replacement
Create a table of existing behavior, replacement capability, application changes, stored data needed, and unresolved gaps. Include instructions, tools, message history, asynchronous handling, file references, and error behavior where applicable. A renamed method is rarely a complete migration if the state model or orchestration responsibility changes.
For the fictional application, identify the conversation history already stored by the application and the configuration needed to recreate behavior. Do not promise that shutdown legacy objects can still be fetched. Use available authorized records and document any missing history. The migration brief should make data limitations visible before implementation begins.
Define representative migration checks
Choose checks that reflect actual application behavior: a simple response, a multi-turn interaction, a tool call, an interrupted operation, and an error path if those features are used. Write expected outcomes from the application’s requirements before running the new implementation. The test should verify user-visible behavior and data continuity, not merely that the replacement API returns HTTP success.
Use fictional or approved test inputs and keep credentials out of the brief. Record SDK versions and configuration so results are reproducible. If a replacement feature behaves differently, describe the user impact and required adaptation. A fluent response does not prove that tool execution, history, or retries work correctly.
Prepare rollout and recovery around current reality
Write the implementation sequence, owners, validation evidence, data handling, and rollback or recovery options that are actually available. If the old endpoint has already shut down, rolling back to it is not a viable recovery plan. Consider reverting application changes while keeping a supported service route, or temporarily disabling the affected feature through the organization’s approved process.
Keep the migration brief dated and link to the official sources. Recheck deprecations before committing to a replacement object or long-lived pattern. After implementation, update the brief with observed results and remaining limitations. The goal is a supported application behavior, with an honest account of what could and could not be carried forward.
Validate the evidence and hand over the result
Run the review in two passes. First, check the source records without reading the generated conclusions. Select a small but representative sample: a clear record, a contradictory record, an incomplete record, and a record that changed after the review began. Write down the expected treatment of each. This gives you a reference for judging the output instead of accepting a plausible narrative because it looks organized.
Then inspect the generated result against those expectations. Open every source supporting a consequential conclusion. Check the surrounding paragraph, the relevant table heading, and any qualifying note. A link to the correct document is only the beginning of verification. The document may support a narrower claim, describe a different version, or use a different unit. Record a correction beside the affected item rather than quietly changing its meaning.
Count the inputs and outputs where a one-to-one relationship is expected. Explain every omitted record and every merged record. When several source items become one conclusion, retain the individual references so the reviewer can reverse that grouping. When one source item produces several actions, preserve the connection so a later source correction can update all affected actions. Never interpret an empty output as evidence that there are no problems until you have checked source coverage.
Keep proposed wording separate from approved wording. An AI system can suggest how to express a finding, but the source owner still needs to confirm the underlying facts when records disagree. Use explicit states such as supported, disputed, missing evidence, and awaiting owner confirmation. Avoid a single confidence score that disguises those different reasons for uncertainty. A disputed statement with two strong sources needs a different next step from a statement with no accessible source.
Before handover, ask a colleague to use the result without your explanation. Can they locate the original evidence, identify unresolved items, and understand what changed since the last version? Fix the places where they need to guess. Save the source manifest, the prompt, the reviewed result, and the correction history together. A useful deliverable should remain understandable after the conversation that produced it has ended, and it should make the next review cheaper because the evidence trail is still intact.
Frequently asked questions
Does deprecated always mean already unavailable?
No. Check the official shutdown date and current status for the exact dependency.
Can old tutorials be used unchanged?
Only after checking them against current reference and deprecation guidance. Legacy examples may be historical.
Is a method rename a complete migration?
Not necessarily. State, tool execution, data, and error handling may require application changes.
What if legacy history was not preserved?
Document the missing data and plan around available authorized records rather than promising retrieval from a shut-down endpoint.
Can rollback use a sunset endpoint?
No. Recovery must use a route that remains supported and available.
