AI Agent Task Board: Manage Claude Code, Cursor & Gemini CLI in One Place
AI Agent Task Board: Manage Claude Code, Cursor & Gemini CLI in One Place
TL;DR: An AI agent task board is a shared workspace where you create tasks, route them to the right AI agent (Claude Code, Cursor, Gemini CLI, OpenCode), and track results -- all from one dashboard. No more terminal juggling. Here's how to set one up in 5 minutes.
Quick Answer: An AI agent task board is a web dashboard that connects multiple AI coding tools (Claude Code, Cursor, Gemini CLI, OpenCode) so you can assign tasks, route work between agents, and see results in one place. Ivern AI provides a free task board with real-time streaming, pipeline workflows (Research → Code → Review), and BYOK pricing at $0.10-$0.25 per task. Setup takes 5 minutes.
If you use more than one AI coding tool, you already know the pain:
- Claude Code runs in Terminal 1
- Gemini CLI runs in Terminal 2
- Cursor runs in VS Code
- Your to-do list is in Notion or a sticky note
- You manually decide which agent handles which task
- You copy-paste context between them when one needs another's output
An AI agent task board fixes all of this. One dashboard. All agents connected. Tasks route automatically.
In this guide:
- What is an AI agent task board
- Setup in 5 minutes
- How task routing works
- Real examples
- Cost breakdown
Related: How to Coordinate Multiple AI Coding Agents · BYOK AI Platform Comparison · Multi-Agent AI Pipeline Workflows · AI Agent Workflows · Windsurf vs Cursor · AI Agent Cost Per Task · Autonomous AI Agent Examples
What Is an AI Agent Task Board?
An AI agent task board is a project management dashboard designed specifically for AI agents. Think of it like a Kanban board where the team members are AI agents instead of humans.
How it differs from a regular task board:
Scroll to see full table
| Regular Task Board (Jira, Linear) | AI Agent Task Board |
|---|---|
| Assign tasks to humans | Assign tasks to AI agents |
| Humans pick up tasks | Agents auto-pick up assigned tasks |
| Status updated manually | Status updates via streaming |
| Comments are text | Comments include code, diffs, analysis |
| One task = one assignee | One task can flow through multiple agents |
| No cost tracking | Cost per task tracked automatically |
The workflow:
You create a task → Task routed to Agent A → Agent A completes →
Output flows to Agent B → Agent B completes → Final result on dashboard
Each step streams in real time. You watch agents work from the dashboard, not from terminal windows.
Setup in 5 Minutes
Step 1: Create an Account (1 minute)
Go to ivern.ai/signup. Free account, no credit card. You get 3 squads and 15 tasks to start.
Step 2: Add Your API Key (30 seconds)
In Settings, add your Anthropic or OpenAI API key. This powers the AI agents. Keys are encrypted with AES-256 and never shared.
If you don't have a key:
- Anthropic: console.anthropic.com -- $5 minimum
- OpenAI: platform.openai.com -- $5 minimum
- Gemini CLI: Free with Google account (no key needed)
Step 3: Create a Squad (1 minute)
Click Create Squad. Name it. Add agents:
Scroll to see full table
| Agent | Model | Role |
|---|---|---|
| Researcher | Gemini 2.5 Pro | Codebase analysis, documentation (free) |
| Developer | Claude Sonnet | Feature implementation, debugging |
| Reviewer | Claude Haiku | Code review, test verification ($0.02/task) |
Step 4: Connect Terminal Agents (1.5 minutes)
In separate terminals:
# Connect Claude Code
npx @ivern-ai/agent install --key YOUR_IVERN_KEY --provider claude
# Connect Gemini CLI
npx @ivern-ai/agent install --key YOUR_IVERN_KEY --provider gemini
Each agent registers with the task board and waits for assignments.
Step 5: Create Your First Task (30 seconds)
From the dashboard, click New Task:
"Analyze the authentication module and identify security vulnerabilities."
Click Assign to Researcher. The task routes to Gemini CLI. Results stream back to the dashboard in real time.
That's it. You're managing AI agents from a task board.
How Task Routing Works
Task routing determines which agent handles which task. There are two approaches:
Manual Routing
You pick the agent when creating the task. Good for when you know exactly which agent should handle it.
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- Researcher → codebase analysis, documentation, large-context tasks
- Developer → implementation, debugging, production code
- Reviewer → code review, test verification, quick checks
Pipeline Routing (Automatic Flow)
You define a sequence of agents. The output of one feeds into the next:
Research (Gemini, free) → Implement (Claude Sonnet) → Review (Claude Haiku)
This is ideal for multi-step work where each phase builds on the previous one. For a deeper dive on building sequential pipelines, see our Multi-Agent AI Pipeline Workflows guide.
Example task with pipeline routing:
"Add a /notifications endpoint. Researcher: analyze existing API patterns. Developer: implement the endpoint with proper error handling. Reviewer: verify tests and code quality."
Each agent executes in sequence. The dashboard shows progress through each phase.
Real Examples
Example 1: Feature Request
Task: "Add dark mode toggle to the settings page"
Pipeline: Researcher → Developer → Reviewer
Scroll to see full table
| Phase | Agent | What Happens | Time | Cost |
|---|---|---|---|---|
| Research | Gemini CLI | Finds existing theme patterns, CSS variables, and settings API | 30s | Free |
| Implement | Claude Sonnet | Builds dark mode toggle component, updates CSS, adds API endpoint | 2min | $0.12 |
| Review | Claude Haiku | Checks for accessibility issues, verifies responsive design, runs tests | 30s | $0.02 |
Result: Production-ready dark mode in 3 minutes for $0.14.
Example 2: Bug Investigation
Task: "Users report slow loading on /dashboard"
Pipeline: Researcher → Developer
Scroll to see full table
| Phase | Agent | What Happens | Time | Cost |
|---|---|---|---|---|
| Research | Gemini CLI | Profiles the dashboard route, identifies N+1 queries and missing indexes | 45s | Free |
| Fix | Claude Sonnet | Adds database indexes, implements query batching, adds caching | 1.5min | $0.10 |
Result: Dashboard loads 4x faster in 2.5 minutes for $0.10.
Example 3: Code Review Batch
Task: "Review all unreviewed PRs. For each: summarize, flag risks, approve or request changes."
Single Agent: Reviewer (Claude Haiku)
Result: 5-10 PRs reviewed in 3-5 minutes for ~$0.10 total.
Cost Breakdown
Per-Task Costs
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| Task Type | Agents Used | Typical Cost |
|---|---|---|
| Simple fix (single agent) | Developer | $0.05-0.15 |
| Feature with review | Developer + Reviewer | $0.10-0.20 |
| Full pipeline | Research + Dev + Review | $0.10-0.25 |
| Codebase analysis | Researcher only | Free |
| Batch PR review | Reviewer only | $0.05-0.15 |
Monthly Cost (Daily Usage)
Scroll to see full table
| Usage Level | Tasks/Week | Monthly API Cost |
|---|---|---|
| Light | 10 | $2-4 |
| Moderate | 30 | $5-10 |
| Heavy | 100 | $15-30 |
Compare to subscription alternatives:
- GitHub Copilot: $10-19/month (single agent, no task board)
- Cursor Pro: $20/month (single agent, no task board)
- ChatGPT Plus: $20/month (single agent, no task board)
The task board approach is cheaper and more capable because you only pay for what you use and each task goes to the optimal agent.
The Dashboard Features You Need
When choosing an AI agent task board, look for:
Real-Time Streaming
Watch agents work as they produce output -- don't wait for completion. This lets you spot issues early and redirect if needed.
Cost Tracking Per Task
Every task shows its token usage and cost. This prevents bill surprises and helps you optimize agent assignments.
Task History
All completed tasks are searchable. You can reference past work when creating new tasks, giving agents better context.
Multi-Model Support
The task board should support multiple providers (Anthropic, OpenAI, Google) so you can use the best model for each task type.
Squad Templates
Pre-built agent configurations save setup time. A "Dev Team" template should include Researcher, Developer, and Reviewer out of the box.
Frequently Asked Questions
How is this different from a regular project management tool?
Regular tools (Jira, Linear, Trello) manage human work. An AI agent task board manages AI agent work. The key differences: agents pick up tasks automatically, results stream in real time, and costs are tracked per task.
Do I need to know how to code to use this?
No. The Ivern task board is a web interface. You type tasks in plain language and assign them to agents. No terminal, no YAML, no Python required. For a full walkthrough, see our no-code AI agent tutorial.
Can multiple people share a squad?
Yes. Team members can create tasks and assign them to agents. Everyone sees the same task board and results.
What happens if an agent fails a task?
The task status changes to "failed" on the dashboard. You can reassign it to a different agent or retry with better instructions.
Can I use this for non-coding tasks?
Yes. The same task board works for research, writing, analysis, and other tasks. Create squads for different use cases: Dev Team, Content Team, Research Team. For examples, see our AI Agent Content Writing Workflow and AI Agent Sales Outreach Workflow.
How secure is my API key?
Keys are encrypted with AES-256 at rest. They're decrypted only when making API calls on your behalf. Keys are never shared, logged, or accessible to other users.
Get Started
- Sign up free at ivern.ai/signup
- Add your API key (Anthropic $5, or use Gemini CLI for free)
- Create a squad with your agent roles
- Connect terminal agents with one command each
- Assign your first task from the dashboard
Stop juggling terminal windows. Start managing AI agents from one place.
For data on how developers manage multi-tool workflows, see our 2026 Developer Survey: 73% of 312 developers use 2+ AI tools, and 62% struggle with tracking what each agent is doing.
For content-focused workflows, see how one prompt generates blog posts, social media, and emails with an AI content factory, or compare BYOK AI platforms that let you use your own API key.
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