A saved AI image workflow can break even when your prompt has not changed. The model behind it may have been retired, renamed, or removed from the app you use. If a familiar Nano Banana option has disappeared, the first thing to check is the exact model version—not your wording.
For creators reviewing their workflows this week, there is a concrete reason to do that audit. Google's Gemini API pricing documentation lists an October 2, 2026 shutdown date for gemini-2.5-flash-image. Adobe's model-retirement documentation also identifies October 2 as the start of Google's Gemini 2.5 (with Nano Banana) deprecation, while noting that removal from Adobe apps would begin September 10. These are related but different timelines: a provider's API lifecycle and an application's model availability are not interchangeable.
This guide explains how to migrate an AI image workflow without losing your approved assets, production brief, or delivery schedule. It is a migration checklist, not a claim that every Nano Banana model or every image-generation service has stopped working.
What the retirement notice means for your workflow
The important detail is the version. A family name such as Nano Banana is not enough to identify the engine that produced an image. An old tutorial, saved integration, or project note can point to a retired version even when newer options remain available.
Before changing anything, distinguish three situations:
- The option is missing from an app: check that app's current model menu and support documentation. Its removal schedule may differ from the underlying provider's schedule.
- An automated request fails: inspect the configured model identifier and the returned error. Authentication, quota, and malformed inputs can also cause failures; do not assume every error means retirement.
- The request succeeds but the result changes: record which model actually ran, where that information is exposed. A different result alone does not prove a model switch.
Google's pricing notice recommends migrating affected Gemini 2.5 Flash Image workflows to Gemini 3.1 Flash Image or Gemini 3.1 Flash Lite Image. Treat those as provider-listed migration options, not a promise that they appear in your preferred app or reproduce an old image exactly.
1. Save a migration package before experimenting
Start with one important recurring job: a catalog scene, an illustrated newsletter header, or a portrait series. Preserve its last approved result and all inputs you are entitled to retain. A screenshot of the prompt is not a complete production record.
- The original reference image, not just a compressed chat preview.
- The final approved export and any editable layout file.
- The exact prompt, including instructions added during follow-up edits.
- The model name or identifier, app, and generation date, if known.
- Output dimensions, aspect ratio, and any recorded generation settings.
- Client restrictions, usage permissions, and the deadline.
If a detail is unknown, label it unknown instead of guessing. Keep originals separate from experiments, and use a simple version convention such as catalog-scene-approved-v1 and catalog-scene-migration-test-v1.
2. Turn the old prompt into a portable visual brief
Copying a prompt is useful as a baseline, but copying the intended result is the real goal. Separate the brief into what must stay fixed and what may change. That makes it easier to adapt wording without accidentally accepting a different deliverable.
For example, a product scene might use this brief:
Create a landscape editorial photograph using the supplied ceramic mug as the product reference. Preserve its handle shape, matte blue glaze, and proportions. Place it on a pale wooden table beside a closed notebook. Use soft morning light from the left and leave the right third uncluttered for a headline. Do not add text, logos, extra handles, or additional mugs. The background may vary; the product identity must not.
Use a reference-capable workflow for that instruction. In text-only generation, a prompt cannot preserve an uploaded product that the model never receives. For exact commercial product representation, retain the original product photograph or composite it into the finished scene if generated versions alter material details.
3. Choose a replacement by required capabilities
Do not select a replacement solely because it is newer. First check whether it accepts the inputs and produces the outputs your job needs.
- Input compatibility: does the available interface accept your reference images and file formats?
- Edit behavior: can you revise an existing image, or does the workflow only generate new ones?
- Delivery fit: can you obtain the required dimensions and aspect ratio without an unsuitable crop?
- Usage terms: do the applicable terms fit the intended client or commercial use?
- Budget: what do retries, edits, and exports cost in the actual app or API you will use?
A model's presence in one provider's API does not establish its availability in AI Photo Generator or another third-party product. Check the options visible in your account before planning a production job around them.
4. Run a small migration rehearsal
Use one archived brief and its approved reference output. Generate a small batch with your candidate workflow, then attempt one realistic revision—for example, replacing the background while preserving the subject. Compare the exports at their intended display size and inspect important details at full resolution.
Write acceptance rules before picking a favorite. For the mug example, reject any output with an altered handle, inaccurate glaze, an extra object overlapping the product, or insufficient headline space. A beautiful image can still fail the assignment.
Record the total spend and hands-on correction time. As an illustrative calculation, if twelve attempts cost $3 and three meet the brief, generation cost per accepted image is $1, before editing labor. These are example numbers, not quoted model prices.
5. Switch deliberately, with a fallback
For a manual workflow, update the project template and keep the last approved assets available. For an integration, change the model configuration in a test environment or a small controlled job first. Validate the response format, image handling, and downstream export before changing the production default.
Do not build a rollback plan around a model scheduled for shutdown. A practical fallback is an already approved asset, a separately tested supported workflow, or manual editing. If no replacement passes the brief, preserve the existing creative rather than lowering the acceptance standard to meet an arbitrary migration date.
Frequently asked questions
Does this mean all Nano Banana image generation is unavailable?
No. The notices cited here identify Gemini 2.5 Flash Image or Gemini 2.5 with Nano Banana. They do not establish that every later model carrying the Nano Banana name is unavailable.
Will a replacement recreate my old image exactly?
Do not plan around an exact recreation. Keep the original approved file. Use the new workflow to meet a documented visual brief, and review differences before replacing an existing asset.
Can I use AI Photo Generator for a new workflow?
You can explore the text-to-image and image-to-image options in AI Photo Generator. Choose from the models and controls currently available to you, then rehearse one real brief before committing a larger batch. This article does not announce support for a particular replacement model.
Sources and scope
The retirement context was cross-checked against Google's Gemini API pricing documentation and Adobe's generative AI model retirement notice, with Adobe's partner-model documentation providing application context. Dates describe the published notices, not a live availability test of every service. The migration procedure and acceptance examples are practical editorial recommendations.