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Agent shifts use an AI model to analyze code and generate changes. Before your team can run agent shifts, you need to connect an AI provider and enable the models you want to use.

Prerequisites

  • Fleetshift setup complete (webhooks connected)
  • An AWS account with access to Amazon Bedrock, a GCP project with access to Vertex AI, or an OpenAI API key
  • Permission to update Portal settings (app settings or plugin settings, depending on the provider)

Configure the AI provider

Fleetshift supports Amazon Bedrock, Google Vertex AI, and OpenAI as AI providers. You can configure one or more — Bedrock and Vertex AI power Claude models, while OpenAI unlocks GPT and o-series models.
Bedrock is configured as a Portal-wide AI provider in app settings.
  1. Go to App Settings > AI Models.
  2. Under Amazon Bedrock, select your credential source:
    • Default credentials uses the AWS credentials already configured in App Settings > Integrations > AWS.
    • Custom uses Bedrock-specific credentials. Enter the access key, secret key, and region.
  3. Click Save.
If you choose Default credentials, make sure your AWS integration already has an access key and secret key configured under App Settings > Integrations > AWS.The AWS credentials need the following IAM permission:

Enable Claude models

Fleetshift agents are powered by Claude when using Amazon Bedrock or Google Vertex AI. You need to enable the Claude models you plan to use with your chosen provider.
  1. In the AWS Console, go to Amazon Bedrock > Model access.
  2. Request access to the Claude models you want to make available.

Available models

You choose which model to use when creating each shift — this is not a global setting.

Claude models (Bedrock / Vertex AI)

OpenAI models (via opencode)

OpenAI models are available through the opencode harness. When you configure an OpenAI API key in the AI Gateway, the shift creation wizard shows opencode as a harness option. Select it and pick from the GPT models below.
If you have both OpenAI and Claude providers configured, you can switch between them on an existing shift. Edit the shift’s model in the shift configuration page, then re-run targets — useful for iterating on a prompt or building on top of previous work with a different model.

Next step

You’re ready to create and run your first shift.