Cleo - The AI Product Manager vs Juggler: Features, Pricing & Which Is Better (2026)
A side-by-side comparison of Cleo - The AI Product Manager and Juggler — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.
Cleo - The AI Product Manager
kryptobaseddev / CleoCode
Agent-first task orchestration platform with persistent memory and multi-provider coordination for long-running developer workflows.
Key features
- Persistent Session Memory: Stores and surfaces long-lived context across agent sessions so work survives interruptions and agents can resume with historical state.
- Multi-Provider Coordination (CAAMP): Unified provider registry and managed agent packages (@cleocode/caamp) to integrate and coordinate multiple model providers and plugins.
- Long-Running Runtime Layer: Runtime supporting polling, server-sent events (SSE), and heartbeat mechanisms to run long-lived processes and background tasks reliably.
- Core Business Logic SDK: @cleocode/core provides task, session, memory, orchestration and lifecycle primitives for building structured agent workflows and pipelines.
- Command-Line Product: @cleocode/cleo offers a thin CLI wrapper to interact with the framework, run agents, and manage tasks from developer terminals.
- Batteries-Included Distribution: @cleocode/cleo-os bundles CANT bridge and TUI extensions for an out-of-the-box experience with additional tooling and interfaces.
- Agent-Managed Packages: Support for modular agent packages that encapsulate provider configurations, capabilities and reusable behaviors for consistent orchestration.
- Lifecycle & Interruption Resilience: Built-in structures for task lifecycles and state transitions so agent workflows can pause, resume, and recover deterministically.
- Agent-first task orchestration (structure, lifecycle, session management)
- Persistent memory across sessions and interruptions
- Multi-provider coordination and unified provider registry (CAAMP)
- Business logic SDK for tasks, sessions, memory and orchestration (@cleocode/core)
- Long-running process support with runtime layer (polling, SSE, heartbeat) (@cleocode/runtime)
- Command-line interface for developer workflows (@cleocode/cleo)
- Batteries-included distribution with bridge and TUI extensions (@cleocode/cleo-os)
- Provider & MCP management for multi-provider setups (@cleocode/caamp)
- Modular monorepo packaging (npm/pnpm, package.json, TypeScript) and native components (Cargo manifest present)
Best for
- Coordinating Multi-Agent Development Workflows: Orchestrate specialist agents (e.g., code-writing, testing, documentation) across a project while preserving shared context.
- Long-Horizon Project Work: Run background, long-running tasks (research, refactors, data processing) with runtime heartbeats and automatic resumption after interruptions.
- Provider-Agnostic Agent Pipelines: Build pipelines that combine outputs from multiple model providers and managed packages via a unified registry for redundancy and best-of-breed selection.
- CLI-Based Agent Operations: Enable developers to run, inspect, and manage agent tasks locally from the terminal using the CLEO command-line interface.
- Stateful Session Automation: Maintain project-specific memory and session history to let agents make decisions based on accumulated context and prior outputs.
- Packaging and Reuse of Agent Capabilities: Create and share modular agent packages for common tasks (e.g., QA, summarization, code generation) to standardize workflows.
- Embedding Agents into Products: Use the cleo-os distribution and CANT bridge to integrate orchestrated agent workflows into TUI tools or product demos.
- Coordinating multiple LLM/agent providers in complex software projects
- Building long-running agent processes that survive interruptions and maintain state
- Developer workflows requiring persistent task memory and session lifecycle
- Integrating provider registries and managing multiple model/connector providers (MCPs)
- Embedding agent orchestration into CLIs, TUI tools or server-side runtimes
Juggler
Julian Storer
A native desktop workbench for AI coding agents with branching conversation trees, inspectable tool calls and editable context.
Key features
- Branching Conversation Trees: Fork the session at any point, recursively, so competing approaches and tangents run side by side without polluting the main context.
- Miller Column Navigation: A Finder-style column layout lays out tool calls, item properties and nested sub-threads for long reading and editing sessions.
- Transaction Inspector: Open any model transaction to see the assembled system prompt, messages, tool definitions, output, token use, timing and stop reason.
- The Context Surgeon: Fold history into a new thread, move or copy items between branches, expand a branch back into its parent, and undo structural changes.
- Local or Remote Sessions: Run the desktop app locally or the headless binary on the machine holding the code, then attach from the app, a browser or a phone.
- Durable Sessions: Sessions are stored on disk as live-synced Yjs documents, so quits, relaunches and dropped connections do not lose the conversation.
- Automatic Context Sizing: Juggler measures the full request before each call, reserves room for the answer and compacts older history before limits become an error.
- Inspectable MCP Tools: Follow an MCP handoff end to end - schema offered, arguments generated, approval, result and errors - with server status, logs and per-tool filtering.
- JavaScript Extension SDK: Context items, LLM loop strategies, slash commands, viewers and Pinboard tabs are extensions you can fork or replace, under a permissive Apache-2.0 SDK.
Best for
- Exploring Competing Fixes: Branch a thread into two sub-threads to try different approaches to the same bug and compare results before committing.
- Auditing Agent Behavior: Inspect exactly what the model received and returned when an agent makes a surprising edit to the codebase.
- Remote Development: Run the server on a dev box or GPU machine where the repository lives and drive the same live session from a laptop or browser.
- Long Refactors: Keep a multi-hour session alive across quits and reconnects, with the agent paused awaiting approval for its next step.
- Provider Comparison: Drive Claude Code, Codex, Copilot, Gemini and local Ollama models through one interface to compare behavior on the same task.
- Custom Tooling: Write JavaScript extensions that add slash commands, file viewers or new LLM loop strategies to the workbench.