Juggler vs Thinking Orbs: Features, Pricing & Which Is Better (2026)
A side-by-side comparison of Juggler and Thinking Orbs — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.
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.
Thinking Orbs
Yogesh
Thinking Orbs is a lightweight React library of animated orb status indicators for AI interfaces such as thinking, searching and compacting.
Key features
- State-Based Orbs: An Orb component with states like reasoning, searching, working, retrying, compacting and waiting to mirror what the agent is doing.
- Zero Dependencies: The React orb needs nothing but React and the plain JS version needs nothing at all, at about 3.8 KB gzipped.
- Customizable Props: Control variant, size, speed, density, dot size, tilt, pause and screen-reader label to fit any interface.
- Opt-in Shapes and Renders: Import extra shapes like cube and renders like halftone separately so only used code is bundled.
- Flexible Installation: Install from npm, pnpm, yarn or bun, or copy the component into a project with shadcn.
- Tintable with CSS: Color orbs with text-* utility classes so they match the host UI theme.
- Interactive Playground: A web playground to preview all states, shapes and renders before integrating.
- llms.txt Support: Publishes an llms.txt so coding assistants can integrate the library correctly.
Best for
- Chat Interface Status: Show a thinking or reasoning animation while an LLM responds.
- Agent Progress Display: Indicate searching, working or background-task states in an agentic coding UI.
- Context Compaction Feedback: Visualize compacting states when conversation history is summarized.
- Retry and Waiting States: Signal retries or waiting-for-input states with distinct orb variants.
- Design System Components: Add a polished AI loading indicator to an in-house React component library.
- Prototype AI Products: Quickly drop a refined status animation into demos and prototypes.