Quick Start

Get Reliant running, chat with your codebase, and run your first workflow.

1. Connect an AI provider

Open Settings → AI.

Select your provider: Claude Code, Codex, Anthropic, OpenAI, OpenRouter, and others.
Authenticate:
- Most providers: enter an API key, then click Test Connection and Add Provider.
- Claude Code or Codex: click Login and complete OAuth in your browser.

Using the web UI instead of the desktop app? Run reliant auth serve in your terminal first — OAuth needs a localhost helper. See Provider Authentication for details.

2. Open a project

Click Open Existing Project and select your code folder. Reliant indexes your files automatically. Or click Create New Project to start fresh.

3. Start chatting

Type a message and press Enter:

“Explain the structure of this project”
“What does the main file do?”
“Add input validation to the signup form”

This is the default agent workflow running. Your message goes to the LLM, the LLM calls tools (read files, search code, make edits, run commands), results go back to the LLM, and it loops until the task is done. So far this is like any other ADE.

4. Run a built-in workflow

This is where Reliant gets different. Instead of manually driving each step, pick a workflow and let agents execute a defined process. Click the workflow selector (defaults to “Agent”) and try one of these:

Workflow	When to use it	What happens
gsd	You have a clear feature to build	Discuss → research → plan → parallel implementation → verify
superpowers	You want test-driven development	Brainstorm → plan → write failing tests → implement → review
simplify-first	You’re working in messy code	Analyze simplifications → refactor → verify → then build
spec-driven	You want to nail requirements first	Write spec → plan approach → implement
get-it-right	Complex change in a large codebase	Attempt → evaluate → improve/restart → diagnose → final implementation

Select a workflow, type your request, and watch multiple agents collaborate on the task.

5. Build your own workflow

Create a YAML file in your project to define a custom process:

.reliant/workflows/review-and-refactor.yaml

name: review-and-refactor
version: v0.0.1
description: Reviews code, then refactors based on findings
status: published
tag: agent

entry: [review]

inputs:
  model:
    type: model
    default: ""

nodes:
  - id: review
    workflow: builtin://agent
    thread:
      mode: inherit
    args:
      model: "{{inputs.model}}"
      mode: auto
      system_prompt: |
        Critically review the code the user points you to. Focus on:
        - Unnecessary complexity
        - Duplicated logic
        - Unclear naming or structure
        Be specific. Reference exact code.

  - id: refactor
    workflow: builtin://agent
    thread:
      mode: inherit
      inject:
        role: user
        content: |
          Based on your review above, refactor the code to address the
          issues you found. Make minimal, focused changes.
    args:
      model: "{{inputs.model}}"
      mode: auto

  - id: verify
    run: npm test

edges:
  - from: review
    default: refactor
  - from: refactor
    default: verify

This workflow: criticizes the code → refactors based on its own critique → runs tests to verify nothing broke. Three steps, zero manual intervention. See Creating Custom Workflows for the full guide.

The interface

Area	Purpose
Navigation Bar	Chats, Worktrees, Workflows, Settings
Sidebar	Context for the selected navigation item
Chat Area	Message input at bottom, history above

Execution modes

Control how much autonomy the agent has with Auto (full autonomy), Manual (approve each action), or Plan (read-only exploration). You can switch modes mid-conversation — a common pattern is to start in Plan mode to analyze, then switch to Auto to execute. See Execution Modes for details.

Optional: memory files

Memory files provide persistent context to the AI across conversations. Global: ~/.reliant/reliant.md

# My Guidelines
- Always write tests
- Use descriptive variable names

Project-specific: reliant.md in your project root

# Project Context
- TypeScript/React project
- Uses Prisma for database

Learn more: Memories & Context

Next steps

Key Concepts — Understand the essential terms
Workflows Overview — How workflows power Reliant
Workflow Control — Pause, resume, and live parameter updates
Creating Custom Workflows — Build your own
Workflow Examples — Copy-and-adapt patterns and complete workflows

Getting Started

Workflows

Workspace & Git

Agent Features

Settings

Architecture

Reference

Help

About

1. Connect an AI provider

2. Open a project

3. Start chatting

4. Run a built-in workflow

5. Build your own workflow

The interface

Execution modes

Optional: memory files

Next steps

​1. Connect an AI provider

​2. Open a project

​3. Start chatting

​4. Run a built-in workflow

​5. Build your own workflow

​The interface

​Execution modes

​Optional: memory files

​Next steps

1. Connect an AI provider

2. Open a project

3. Start chatting

4. Run a built-in workflow

5. Build your own workflow

The interface

Execution modes

Optional: memory files

Next steps