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Everything in Reliant runs through workflows. Type a message, press enter, and you’re triggering a workflow. The agent reads your codebase, executes tools, responds. That’s a workflow. A workflow is a programmable sequence of AI operations. It defines which tools the agent can use, how approvals work, when to loop, and when to stop.

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The Agent Workflow

The default experience in Reliant is itself a workflow called builtin://agent. When you chat, you’re running this workflow. Here’s what happens when you send a message: The workflow sends your message to the LLM. The LLM responds, possibly requesting tool calls—reading files, searching code, making edits. The workflow executes those tools and sends the results back to the LLM. This loop continues while the LLM has tool calls to execute. When the LLM responds without requesting more tools, the task is complete. A single message like “add input validation to the signup form” might trigger dozens of iterations. The agent reads your codebase, identifies the relevant files, plans the changes, implements them, verifies they work. All within this loop.

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Execution Modes

The mode parameter controls how tool execution is handled. This is a regular workflow input you can set in the UI or in workflow YAML.
ModeBehaviorGood for
AutoAuto-approves all tool calls. Press Escape to cancel.Large refactors, trusted tasks, autonomous work
ManualRequires your approval before each tool execution.Learning Reliant, sensitive code, understanding what the agent is doing
PlanRead-only tools only. Can view files and search, but no edits or commands.Exploring unfamiliar code, creating a plan before executing it
You can switch modes mid-conversation. A common pattern: start in plan mode to analyze and create a plan, then switch to auto to execute it.

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Running Workflows

Workflows appear in the workflow selector in the chat interface. The default agent workflow is pre-selected, but you can choose others—including custom workflows you’ve created or advanced built-in workflows for specific patterns like TDD or code review. When you select a workflow, a parameters panel appears showing the configurable options:
ParameterPurpose
modeExecution mode (auto, manual, or plan)
modelWhich LLM to use (Claude, GPT, etc.)
temperatureResponse randomness (0 = focused, 1 = creative)
thinking_levelExtended thinking depth (low, medium, high, xhigh). xhigh is used on supporting models/providers and maps to the highest supported level elsewhere
toolsWhich tools the agent can access
spawn_presetsWhich presets are available for spawning sub-agents
You can adjust these parameters before each conversation. A complex refactoring might warrant a higher thinking level and lower temperature, while brainstorming might benefit from higher temperature.

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Understanding Presets

Presets bundle parameter values into reusable configurations. Presets allow you to quickly switch between different agent behaviors When you select the “researcher” preset, it configures the agent with a specialized system prompt for research tasks, lower temperature for focused analysis, and a curated set of read-oriented tools. You get a research-optimized agent without touching individual parameters. Reliant includes built-in presets for common development tasks: general coding, research, code review, documentation, refactoring, debugging, and more. You can also create custom presets in .reliant/presets/. For the complete list and customization options, see the Presets guide.

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Workflow Outputs

Workflows produce outputs that become available when the workflow completes. For the agent workflow, the primary outputs are:
  • message: The final assistant message from the conversation
  • response_text: The text content of that message
These outputs matter most when workflows are composed—when a parent workflow spawns child workflows and needs their results. The agent workflow’s thread also contains the complete conversation history, which persists in your session for later reference or continuation.

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Beyond the Agent Workflow

While the agent workflow handles most tasks, Reliant includes additional workflows for specialized patterns: plan-debate uses two agents: a proposer and a critic. The proposer suggests approaches, the critic identifies weaknesses, they iterate while disagreements remain. parallel-compete runs three agents on the same problem, then a reviewer picks the best solution. Good for comparing implementation strategies (SQL vs NoSQL, algorithm choices). tdd-loop implements test-driven development: write failing tests, implement while tests fail, refactor, repeat. For details on these patterns and how to build your own, see Multi-Agent Patterns.