Gemini workflow placement

Use this reference to decide where a workflow belongs in Gemini: Gems, personalization, connected apps, Google AI Studio, Gemini API, or Vertex AI.

Start with the workflow layer, then choose the Gemini surface

Use this reference to decide whether a workflow belongs in a Gem, Gem instructions, Knowledge files, Gemini personalization, Connected Apps, Google AI Studio, Gemini API system instructions, Files API, File Search, tools, structured output, or Vertex AI.

Gemini setup decision

Choose the right Gemini surface first. Start by choosing the surface that matches the workflow scope. Gemini app chat, Gems, personalization, Google AI Studio, Gemini API, and Vertex AI are different implementation environments.

Use a Gem for a reusable Gemini workflow

Use a Gem when the workflow should be reused with stable instructions, optional Knowledge files, preview testing, and a dedicated assistant-like setup.

Go to Gems →

Use personalization for broad preferences only

Use Instructions for Gemini, Memory, and Connected Apps for broad personalization. Do not use them as the only home for one workflow or one project.

Go to personalization →

Use Google AI Studio for prototyping

Use AI Studio to test prompts, model settings, tools, structured output, and Gemini API behavior before moving the workflow into application code.

Go to AI Studio →

Use Gemini API / Vertex AI for production systems

Use API or Vertex AI surfaces when the workflow needs system instructions, tools, function calling, Files API, File Search, structured output, RAG, or backend validation.

Go to Gemini API / Vertex AI →

Review Gemini tools and advanced capabilities

Use this when the workflow depends on Deep Research, Deep Think, connected apps, retrieval, code execution, function calling, scheduled work, Gems, Spark, or Canvas.

Go to tools and capabilities →

Use normal Gemini chat only for one-off tasks

Use ordinary Gemini chat when the task does not need reusable instructions, Knowledge files, API behavior, retrieval, tools, or production validation.

Go to placement rules →

Use the API mapping for internal systems

Use the API mapping when Gemini is part of an internal agent, backend service, CI workflow, product feature, retrieval system, or production automation pipeline.

Open API mapping →

Primary surfaces

Gemini surfaces you can configure. These are the main Gemini surfaces relevant to workflow placement. Availability can vary by account type, Google Workspace configuration, region, language, product surface, model, and rollout state.

Gemini app chat
Use for one-off prompts, current questions, current documents, current tasks, or normal chat interaction. Do not use ordinary chat as the only home for reusable workflow rules.
Gems
Custom Gemini assistants for repeated tasks. Use a Gem when you need reusable instructions, a previewable workflow, and optional Knowledge files for recurring work.
Gem instructions
The instruction layer for a Gem. Use for persona, task, context, format, goals, desired behavior, workflow rules, output requirements, and verification expectations.
Gem Knowledge files
The reference layer for a Gem. Use Knowledge files for reusable source material such as policies, procedures, examples, documents, Drive files, and NotebookLM notebooks where supported.
Instructions for Gemini
Account-level personalization. Use only for broad preferences that should apply across Gemini chats. Do not use this as the default location for one project, one workflow, or one reusable assistant.
Memory
Personalization from past Gemini chats where enabled. Use as continuity/personalization, not as a deterministic instruction layer or reference repository.
Connected Apps
Google app connections that can help Gemini complete requests or personalize responses using eligible connected app context. Treat connected app data as contextual access, not as workflow rules.
Temporary Chat
Use when the conversation should not appear in Gemini Apps Activity or recent chats. Do not use Temporary Chat as a reusable workflow surface.
Google AI Studio
Developer prototyping surface for trying Gemini models, prompts, settings, tools, and getting code for API implementation.
Gemini API system instructions
Developer instruction layer for API workflows. Use for stable behavior, role, output format, and repeated constraints in application code.
Vertex AI system instructions
Google Cloud surface for production Gemini workflows. Use for system-level behavior on Vertex AI, while keeping sensitive secrets out of prompts and system instructions.
Files API
API file input layer for larger files or files reused across requests. Files are temporary and are not the same as a persistent File Search store.
File Search
Gemini API RAG surface. Use File Search to import, chunk, index, and retrieve relevant source material for model context.
Function calling and tools
Tool/action layer for external APIs, application functions, built-in Google tools, Code Execution, URL Context, Google Search grounding, Google Maps grounding, and Computer Use where supported.
Structured outputs
Output-control surface for JSON/schema-constrained responses used by applications, extraction workflows, UI rendering, validation, or automation.

Gems

Use Gems for reusable Gemini workflows. A Gem is the correct Gemini surface when the workflow should be reused with stable instructions, optional Knowledge files, preview testing, and user-facing access through Gemini Apps.

Where to configure this in Gemini

Create a Gem
In the Gemini web app, open Explore Gems, then select New Gem. Enter a Gem name, add instructions, and save the Gem.
Write Gem instructions
Put stable workflow behavior in the Gem instructions. Google recommends covering persona, task, context, and format when writing Gem instructions.
Use Gemini to rewrite instructions
Use this only as a drafting helper. After Gemini rewrites instructions, manually review scope, behavior, output format, and workflow boundaries before saving.
Add Knowledge files
After adding instructions, use the Knowledge section and select Add files. Add files from device upload, Google Drive, or NotebookLM where supported.
Use Drive files when freshness matters
When a file is added from Drive, Gemini can use the most recent version of the file. Use this only when the workflow should follow the current Drive version.
Use or avoid Knowledge citations intentionally
Use citations for evidence-sensitive workflows. Do not disable Knowledge citations for fact checking, policy review, research review, audit, or any workflow where users need source traceability.
Preview before relying on the Gem
Use the preview text box to test the Gem, then save or update it. Previewing alone does not replace reviewing the instructions and Knowledge behavior.
Edit, delete, pin, or share a Gem
Use the Gem management controls for maintenance and distribution. Management actions do not replace the instruction layer or Knowledge layer.
Verify setup
Ask the Gem to perform a task that requires its instructions and a task that requires its Knowledge files. If behavior is wrong, edit instructions. If source use is wrong, check the Knowledge files and citations.

Personalization

Separate personalization from workflow configuration. Instructions for Gemini, Memory, Connected Apps, and Temporary Chat affect personalization and chat behavior. They are not a replacement for Gems, Knowledge files, API system instructions, or retrieval.

Where to configure personalization in Gemini

Instructions for Gemini
In the Gemini web app, open Settings & help → Personal Intelligence → Instructions for Gemini. Add, edit, delete, or turn instructions on/off there.
Memory
Use Personal Intelligence settings to manage whether Gemini uses memory of past chats for personalization. Treat Memory as personalization, not workflow enforcement.
Connected Apps
Use Connected Apps when Gemini should connect to eligible Google apps to complete requests or personalize responses. Availability can vary by account type, Workspace edition, location, language, device, and app.
Temporary Chat
Use Temporary Chat when the conversation should not appear in Gemini Apps Activity or recent chats. Temporary Chat is not available in every account type or product surface.
Verify setup
Ask Gemini whether it is using broad personalization, then check Personal Intelligence and Connected Apps settings. For workflow-specific behavior, use a Gem or API system instruction instead of personalization.

Google AI Studio

Use AI Studio to prototype before implementation. Google AI Studio is the right surface for testing Gemini model behavior, prompts, settings, tools, and API-oriented workflows before moving the workflow into code.

Where to configure this in AI Studio

Prototype prompts
Use AI Studio to try Gemini models and experiment with prompts. When ready to build, use Get code to move the setup toward Gemini API implementation.
Test chat behavior
Use chat prompts when the workflow requires multi-turn behavior. Keep stable workflow rules separate from current task input when moving from prototype to implementation.
Prototype tools and structured output
Use AI Studio to test supported tool use, structured output, code execution, grounding, or other model/API behavior before implementing it in production code.
Verify setup
Confirm that the prompt, model, tool settings, output format, and API code match the intended workflow before moving the workflow into a backend, agent, or production environment.

Gemini API / Vertex AI

Use API surfaces for products, agents, and production workflows. Use Gemini API or Vertex AI when the workflow needs application control, system instructions, tool execution, structured outputs, files, RAG, validation, or production governance.

Where to configure Gemini API / Vertex AI workflows

System instructions
Put stable behavior rules in system instructions. Use this for role, persona, output format, task rules, formatting requirements, and repeated workflow behavior.
Runtime request
Put the current user request, current file, current document, current task, or current constraints in the runtime request. Do not use runtime input as the only home for stable rules.
Files API
Use the Files API for larger files or files intended for multiple requests. Files API storage is temporary; do not treat it as persistent knowledge storage.
File Search
Use File Search for RAG. File Search imports, chunks, indexes, and retrieves relevant source material to provide context to the model.
Function calling
Use function calling for custom tools that your application executes. Your application receives tool-call JSON, executes the function, and returns the function result to Gemini.
Built-in tools
Use built-in tools when the workflow needs Google Search grounding, Google Maps grounding, URL Context, Code Execution, File Search, or Computer Use where supported.
Structured output
Use structured output when the response must match a JSON/schema-like shape for extraction, UI rendering, validation, or downstream automation.
Vertex AI system instructions
Use Vertex AI system instructions for Google Cloud workflows. Google notes that system instructions guide behavior but do not fully prevent jailbreaks or leaks; do not put sensitive secrets in them.
Verify setup
Test system instructions, runtime requests, tool calls, structured outputs, files, and retrieval separately. Validate outputs outside the model before using them in product, backend, CI, or production workflows.

Tools and advanced capabilities

Map Gemini capabilities by surface, execution owner, and control boundary

Use this section to separate Gemini research modes, connected apps, retrieval, execution tools, reusable configuration, automation, and workspace surfaces. These capabilities are not the same as stable instructions, memory, or source material.

Capability Type Surface Execution owner Primary use Control boundary
Deep Research Search/research mode Gemini Apps Gemini-managed research workflow Plan, search, synthesize, and produce sourced research reports. Verify source coverage, connected-source access, citations, and plan fit before using the report as evidence.
Deep Think Reasoning mode Gemini Apps where available Gemini-managed reasoning mode Use extended reasoning for complex planning, analysis, or problem solving. Do not treat longer reasoning as automatic correctness; verify outputs against supplied evidence and task constraints.
File upload and file analysis File/data capability Gemini Apps Gemini app surface Analyze uploaded documents, spreadsheets, images, videos, notebooks, or code folders. Keep uploaded files separate from reusable knowledge; verify document scope and source freshness.
Connected Apps Connected app layer Gemini Apps User-authorized Google or third-party service Use Gmail, Drive, Docs, Calendar, Maps, YouTube, GitHub, device, or Workspace context where available. Confirm account, plan, region, app permissions, and whether the action reads data or changes external state.
Gems and custom instructions Reusable configuration Gemini Apps Gemini app configuration Create reusable assistants, stable behavior instructions, or repeated task setups. Use for stable task behavior, not for secrets, one-off evidence, or runtime-only constraints.
Canvas Workspace surface Gemini Apps Gemini workspace surface Create and revise documents, apps, drafts, or structured outputs in an editable workspace. Do not treat Canvas output as source material; review generated content before publishing or implementation.
Scheduled actions and Gemini Spark Scheduled/proactive work Gemini Apps / Gemini Spark where available Gemini-managed scheduled workflow Run repeated prompts, scheduled actions, or lightweight workflow automation. Verify trigger conditions, connected-app access, notification behavior, and whether the workflow can take external action.
Spark skills Reusable configuration Gemini Spark Gemini Spark configuration Reuse instructions, files, context, and task setup across Spark workflows. Use for repeatable workflow setup; do not use as an enforcement layer or secret store.
Google Search and Google Maps grounding Platform-managed tool Gemini API / Vertex AI where supported Google-managed tool execution Ground responses in web or location/map context. Verify grounding metadata, source provenance, model support, and whether the selected surface supports the tool.
URL Context and File Search Retrieval/source capability Gemini API / Vertex AI where supported Google-managed retrieval Retrieve context from URLs or indexed files for RAG-style workflows. Verify retrieved context, indexed source set, chunking assumptions, and whether retrieval actually supports the claim.
Code Execution and Computer Use Execution tool Gemini API where supported Google-managed or client-controlled execution boundary, depending on tool Run code-backed computation or operate a browser/computer environment where supported. Validate outputs, inspect side effects, and require approval for external, destructive, or user-visible actions.
Function Calling Application-owned tool call Gemini API / AI Studio prototype Application-owned execution Let the model request custom functions, APIs, database lookups, or business-system actions. Validate schema, arguments, permissions, side effects, and returned results outside the model.
Live API and media generation Agentic / media capability Gemini API / Gemini Apps where available Gemini-managed generation or realtime interaction surface Build realtime voice/vision experiences, generate images, or use media workflows where supported. Verify availability, model support, safety requirements, and whether generated media needs review before use.

Verification checklist

  • Verify the capability exists on the selected Gemini surface, model, plan, account, and region.
  • Separate Gemini-managed tools from application-owned function calls.
  • Verify connected-app permissions before relying on Gmail, Drive, Calendar, GitHub, or Workspace data.
  • Verify source provenance for Deep Research, grounding, URL Context, and File Search outputs.
  • Require validation and approval before external, user-visible, destructive, or irreversible actions.
  • Do not use tools, Canvas, Gems, Spark skills, or custom instructions as a substitute for stable source material or policy enforcement.

Layer placement map

Where each workflow layer belongs in Gemini. Use this table after classifying the workflow layer. The goal is correct placement, not feature listing.

Workflow layer What belongs here Best Gemini placement Do not use for
Instruction layer Stable role, behavior, workflow rules, output format, constraints, verification rules. Gem instructions, Gemini API system instructions, Vertex AI system instructions. Use Instructions for Gemini only for broad personalization. Source files, secrets, one-off input, temporary notes, or mutable business state.
Reference / source material layer Policies, examples, docs, Drive files, notebooks, source documents, research packs. Gem Knowledge files, Files API, File Search stores, URL Context, app-owned retrieval, or Drive-connected sources where supported. Behavior rules that must always apply; those belong in the instruction layer.
Reusable workflow layer Repeatable assistant behavior, recurring tasks, reusable procedures, stable response formats. Gem for app users; API orchestration for products/internal systems. One-off chat prompts that must be manually reconstructed every time.
Runtime prompt layer The current question, current file, current document, current task, current constraints. Gemini app chat, Gem chat prompt, API request contents, AI Studio prompt. Permanent workflow policy, source governance, credentials, or long-lived reference material.
Tool / retrieval layer External functions, built-in tools, search grounding, URL retrieval, code execution, RAG, app data. Function calling, built-in tools, File Search, Google Search grounding, URL Context, Google Maps, Code Execution, Connected Apps. Unvalidated writes, sensitive operations, or production side effects without application-side controls.
Personalization layer Broad preferences, past-chat personalization, connected app personalization. Instructions for Gemini, Memory, Connected Apps settings. Formal verification, project memory, deterministic workflow control, or source-of-truth storage.
Verification layer Source checks, schema checks, citation checks, policy checks, output acceptance criteria. Gem instructions, API validation layer, structured output validation, application-side evals, final verification prompt. Informal “looks good” review for publication, client delivery, production use, or automated actions.

Placement rules

Use the smallest stable Gemini surface that matches the scope. The same rule can be correct or incorrect depending on whether it is chat-specific, Gem-specific, account-wide, API-level, retrieval-level, or production-system behavior.

If the workflow is one-off
Put the current task in Gemini app chat or the current API request. Do not create a Gem unless the workflow will recur.
If the workflow should repeat in Gemini Apps
Create a Gem. Put behavior in Gem instructions and reusable source material in Knowledge files.
If the rule should apply broadly across Gemini chats
Use Instructions for Gemini only for broad preferences. Do not put one project or one procedural workflow there.
If source material should be reused
Use Gem Knowledge files, Drive-connected files, File Search, Files API, URL Context, or application-owned retrieval depending on the surface.
If the workflow is developer-facing
Prototype in Google AI Studio, then implement stable behavior through Gemini API or Vertex AI system instructions.
If the workflow needs tools
Use built-in tools or function calling. Keep tool execution and side effects under application-side validation and permission controls.

Misplacement guardrails

What not to put in the wrong Gemini surface. Most Gemini workflow failures come from mixing reusable instructions, source files, personalization, runtime input, retrieval, and tool execution.

  • Do not put reusable workflow rules only in ordinary Gemini chat if the workflow should repeat.
  • Do not put large reusable source material in the prompt when it belongs in Gem Knowledge, File Search, Files API, URL Context, or retrieval.
  • Do not use Instructions for Gemini as the home for one project-specific or workflow-specific procedure.
  • Do not treat Memory or Connected Apps as deterministic workflow control.
  • Do not disable Knowledge citations for evidence-sensitive workflows.
  • Do not put secrets, API keys, credentials, private tokens, or privileged environment values in Gem instructions, Knowledge files, prompts, or system instructions.
  • Do not rely on system instructions as a complete security boundary. Use application-side authorization, validation, logging, and evals.
  • Do not assume a capability is available to every user or model. Account type, Workspace settings, region, language, product surface, model, and rollout state can affect availability.

Official source check

Official Google references used for this mapping. Use these references to verify Gemini terminology and feature boundaries before updating this page again.

Next steps

Use this platform mapping to place the workflow, then continue to comparable platform maps or the API placement path.