Agentic Workflow OS
Structured Architectural Scaffolding for AI Development
Agentic Workflow OS is a development platform that orchestrates Multi-Agent Systems to plan, architect, and implement complex software projects. Unlike "Chat with Code" tools that rely on messy, unstructured conversation history, this system enforces a Context-First philosophy. It treats Agent Context as a file-system state machine, ensuring that your AI Engineer knows exactly what your AI Architect decided.
⚡ Why Use This?
Agentic Workflow OS - Because AI deserves structure, and developers deserve results.
Most AI coding tools suffer from Context Drift. After 20 messages, the AI forgets the architectural constraints you set in message #1.
AI for projects and work is like a rocket: it gives a quick boost of velocity if you have direction, but soon everyone realizes it's only a first-stage booster that stops midway once context is off. The velocity drops, and to carry forward and build production-grade applications needs a 2nd and 3rd stage booster with precision guidance to reach and stay in orbit. This project is that 2nd and 3rd stage.
Agentic Workflow OS solves this by:
- Strict Role Separation: Agents have clearly defined roles with explicit boundaries - architects handle specifications, engineers handle implementation, with enforced separation to prevent scope creep.
- Artifact-Driven Handoffs: Agents cannot proceed until they receive specific, validated artifacts from predecessors, ensuring dependencies are met before progression.
- Programmatic Agent Interaction: Agents operate in environments with terminal access, using CLI tools to search project state, log decisions, record handoffs, and progress through workflow stages - enabling structured, auditable AI collaboration without conversational drift.
The system operates on a Stateless Core / Stateful Edge model.
🔄 Workflow Comparison
| Feature | Agentic Workflow OS | ChatGPT + Manual | GitHub Copilot | VS Code + Cursor |
|---|---|---|---|---|
| Context Preservation | ✅ File-system state machine | ❌ Conversation drift | ❌ Session-based | ❌ Session-based |
| Role Separation | ✅ Strict agent boundaries | ❌ Single AI persona | ❌ Single AI persona | ❌ Single AI persona |
| Artifact Validation | ✅ Automated quality gates | ❌ Manual review | ❌ No validation | ❌ No validation |
| Audit Trail | ✅ Complete history | ❌ Lost in chat | ❌ No tracking | ❌ No tracking |
| Multi-Agent Coordination | ✅ Orchestrated handoffs | ❌ Manual coordination | ❌ No coordination | ❌ No coordination |
| Production Ready | ✅ Enterprise-grade output | ⚠️ Requires significant editing | ⚠️ Requires significant editing | ⚠️ Requires significant editing |
🚀 Quick Start
Environment Setup
Create and activate a Python virtual environment:
# Create virtual environment
python3 -m venv myproject-env
# Activate the environment
source myproject-env/bin/activate
# On Windows:
source myproject-env\Scripts\activate
Installation
Option A: Pip (Recommended)
pip install agentic-workstation
# First run will launch an interactive setup wizard
agentic --help
First-Time Setup: On first run, Agentic Workflow OS will launch an interactive setup wizard to configure your workspace and preferences. This creates
~/.config/agentic/config.yamlwith your settings.
Option B: From Source (Development)
git clone https://github.com/sujith-eag/agentic_workflow.git
cd agentic_workflow
pip install -e .
Uninstallation
Option A: Pip
pip uninstall agentic-workstation
Option B: Docker
# Remove the Docker image
docker rmi agentic-workstation
# Remove any running containers (if any)
docker rm $(docker ps -aq --filter ancestor=agentic-workstation)
🛠️ CLI & TUI Usage
For detailed CLI documentation, see CLI_REFERENCE.md. For interactive usage, use the Text User Interface (TUI) with agentic.
Available Commands
The CLI uses a context-aware design - commands available depend on whether you're in a project directory or not.
Global Commands (from repository root)
agentic init <name> --workflow <type> --description "desc"- Initialize new project with workflowagentic list- List all projects or show details for oneagentic delete <name>- Permanently delete a projectagentic workflows- List available workflow definitionsagentic config- View or edit global configurationagentic- Launch TUI in global mode
Project Commands (from within project directory)
agentic status- Show project status and workflow stateagentic activate <agent_id>- Activate specific agent sessionagentic handoff --to <agent_id> --artifacts "files"- Record agent handoff with artifactsagentic decision --title "Title" --rationale "Reason"- Record project decisionagentic end- End current workflow sessionagentic feedback --target <agent_id> --severity <level> --summary "Summary"- Record feedback for an agent or artifactagentic blocker --title "Title" --description "Desc" --blocked-agents "ids"- Record a blocker that prevents progressagentic iteration --trigger "Trigger" --impacted-agents "ids" --description "Desc"- Record an iteration in the development processagentic assumption --assumption "Assumption" --rationale "Rationale"- Record an assumption that may affect the projectagentic list-pending- List pending handoffs for the current projectagentic list-blockers- List active blockers for the current project
🖥️ CLI Interaction for AI use
These assets show the command-line help and workflow interaction screens.
Project Help Screen
Watch the project help screen video
Workflow Help Screen
Watch the workflow help screen video
🖼️ TUI for Human Flows
Project Creation Flow
Project Usage Flow
Project Usage Video
🏗️ Creating & Running a Project
1. Initialize a Project
Navigate to your empty folder and initialize a project.
# From repository root (global context)
agentic init MySaaS --workflow planning --description "My SaaS application project"
Available workflows: planning, implementation, research, workflow-creation
2. Agent Workflow Orchestration
Agents operate in environments with terminal access, using CLI commands to orchestrate structured workflows:
-
Navigate to Project:
cd projects/MySaaS -
Session Activation: User or Agents run
agentic activate A-01to start their session and receive context. -
Context Processing: Agents access the generated
active_session.mdfile containing their role, instructions, and project state. -
Artifact Generation: Agents produce required deliverables and save them to specified artifact paths.
-
Handoff Execution: Agents execute handoff commands to progress the workflow:
agentic handoff --to A-02 --artifacts "artifacts/project_brief.md,artifacts/requirements.md"
The system validates artifact existence and workflow rules before allowing progression. The from agent is automatically inferred from the active session.
-
State Management: Agents can log decisions, record blockers, and query project status using CLI commands throughout the process.
3. Review Status
View the decision tree and current state.
agentic status
📦 Workflows
The system supports pluggable Workflow Manifests with four main workflow types.
1. Planning (15 agents: A-00 to A-14)
- Goal: Turn a 1-sentence idea into a full Tech Spec.
- Key Agents:
A-00 Orchestrator & Project ControllerA-01 Project Guide & Idea IncubationA-02 Planning & Requirements AnalystA-03 Architecture & Technical Design AnalystA-04 Security & Compliance ScrutineerA-05 Infrastructure & DevOps Planning ArchitectA-06 Data Architecture & Storage Planning SpecialistA-07 API & Integration Planning SpecialistA-08 UX & Interaction Planning SpecialistA-09 Developer Workflow & Engineering Standards Planner
2. Implementation (10 agents: I-00 to I-05 + specialists)
- Goal: Turn specs into production code.
- Key Agents:
I-00 Implementation OrchestratorI-01 Scaffold & DevOps ArchitectI-02 Backend & Data EngineerI-03 Frontend & UX EngineerI-04 Quality & Validation SpecialistI-05 Release & Integration ManagerI-DOC Documentation Sprint AgentI-DS Data Store Implementation SpecialistI-PERF Performance Optimization AgentI-SEC Security Hardening Auditor
3. Research (12 agents)
- Goal: Conduct thorough research, analysis, and reporting.
- Use Cases: Literature review, data analysis, academic research, market research.
4. Workflow-Creation (9 agents)
- Goal: Create and customize new workflow packages.
- Use Cases: Meta-workflow development, process automation.
Custom Workflows
You can create your own workflows by placing a manifest in:
- Project:
./.agentic/workflows/my-custom-flow/workflow.json - User global:
~/.config/agentic/workflows/my-custom-flow/workflow.json - System: Bundled in package (not recommended for custom)
Workflow manifests include workflow.json, agents.json, artifacts.json, etc.
🛠️ CLI Commands
Global Commands (from repository root)
# List available workflows
agentic workflows
# Initialize new project
agentic init MyProject --workflow planning --description "My project description"
# Launch TUI (Terminal User Interface)
agentic
# Show CLI help
agentic --help
Project Commands (from within project directory)
# Navigate to project
cd projects/MyProject
# Show current project status
agentic status
# Activate an agent session
agentic activate A-01
# Record handoff between agents (from agent inferred from active session)
agentic handoff --to A-02 --artifacts "requirements.md,architecture.md"
# Record project decision
agentic decision --title "Technology Stack Selection" --rationale "React + Node.js chosen for full-stack consistency"
# End workflow session
agentic end
⚙️ Configuration & Setup
Automatic Setup
On first run, Agentic Workflow OS automatically launches an interactive setup wizard that configures:
- Default workspace (where projects are stored)
- Editor command (for opening files)
- UI preferences and logging levels
Configuration Files
Global Config (~/.config/agentic/config.yaml):
default_workspace: "~/AgenticProjects"
editor_command: "code"
tui_enabled: true
check_updates: true
log_level: "INFO"
Project Config (.agentic/config.yaml in each project):
workflow: planning
strict_mode: true
excluded_paths:
- "node_modules"
- ".git"
custom_overrides:
governance:
require_reviews: true
Manual Configuration
If you prefer to set up configuration manually or modify existing settings:
-
Create global config directory:
mkdir -p ~/.config/agentic
-
Create config file:
cat > ~/.config/agentic/config.yaml << 'EOF' default_workspace: "~/AgenticProjects" editor_command: "code" tui_enabled: true check_updates: true log_level: "INFO" EOF
-
Create workspace directory:
mkdir -p ~/AgenticProjects
Re-running Setup
To re-run the setup wizard or modify configuration:
# Remove config to trigger setup again
rm ~/.config/agentic/config.yaml
agentic
🛠️ Development
This project is built with Python 3.10+.
- Core:
src/agentic_workflow - Manifests:
src/agentic_workflow/manifests(Canonical Definitions) - Templates:
src/agentic_workflow/templates(Jinja2 templates) - Build:
pyproject.toml(Hatchling) - Tests: Not included in deployment
License: MIT
Release files for agentic-workstation 1.0.12
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| agentic_workstation-1.0.12.tar.gz | 6.0 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| agentic_workstation-1.0.12-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 6.4 MB
Release files / agentic_workstation-1.0.12.tar.gz
| Download URL | agentic_workstation-1.0.12.tar.gz |
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| Size | 6.0 MB |
| Tags | Source |
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Release files / agentic_workstation-1.0.12-py3-none-any.whl
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| Tags | Python 3 |
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