AI app for it and development · no coding needed
Parallel coding agent session control desk
Keep several agent sessions visible, alive and isolated in one local workspace.
Made for: Developers and small engineering teams running several AI coding agents in parallel on one machine
What it does for you
The problem
Parallel agent sessions are hard to see, keep dying on restarts or SSH drops, and can overwrite each other's files.
What it gives you
Reviewed, merge-ready change set per session
What you give it
Local agent sessionsrepository stateterminal outputpermission events
Build your own version of Shepherd Terminal, Chive and more
One app with what these 9 AI tools do, yours to keep and change: Shepherd Terminal, Chive, Canopy, AgentManager, Jackalope, Intelligent Terminal, Otty, AgentPeek, CC-BEEPER.
Everything these tools do, in one app
- Multi-session monitoring Shows the status of several parallel agent sessions in one place.Found in Shepherd Terminal, Chive, Canopy and 6 more
- Session persistence Keeps agent sessions and their context alive across app restarts, SSH drops, or window closures.Found in Shepherd Terminal, Canopy, Otty
- Attention alerts Notifies the user when a session needs input or requires attention.Found in Chive, AgentManager, CC-BEEPER
- Local-only data Keeps session data and prompts on the user's machine without cloud services or telemetry.Found in Chive, AgentManager, AgentPeek and 1 more
- Git worktree isolation Runs each agent session in its own branch and directory to prevent file conflicts.Found in Canopy, Jackalope
- Sandboxed agent runtime Wraps agent sessions in containers so the agent runs in a contained environment rather than directly on the host.Found in Canopy
- Review before merge Lets the developer inspect agent-produced changes before applying or merging them.Found in Jackalope, Canopy
- Terminal jump Navigates directly to the exact terminal pane, tab, or editor window for a session.Found in AgentManager
- Split panes and tabs Organizes multiple sessions side by side with split panes and tabs.Found in Shepherd Terminal, Canopy, Otty
- Voice interaction Supports voice input and spoken summaries for hands-free use.Found in Shepherd Terminal, CC-BEEPER
- Permission handling modes Controls how agent permission requests are accepted or denied.Found in CC-BEEPER
- Token and usage tracking Shows where tokens or quota were spent across sessions and accounts.Found in Canopy, Jackalope, AgentPeek
- Session history and summaries Captures tool call histories, diff counts, and final summaries after a session completes.Found in AgentPeek
- Multi-agent orchestration Automatically selects the best agent and account for a given task.Found in Jackalope
- Remote SSH connectivity Connects to remote development machines over SSH to access terminals and files.Found in Shepherd Terminal
- Automatic error detection Surfaces likely command failures and relevant guidance inline.Found in Intelligent Terminal
- Context-aware suggestions Reads recent shell output and offers suggestions or detects issues.Found in Intelligent Terminal
- GPU-accelerated rendering Uses GPU acceleration to keep rendering smooth with multiple agent processes.Found in Otty
How it works, step by step
- Show status of several parallel agent sessions in one board
- Keep sessions and context alive across restarts, SSH drops and window closures
- Alert the user when a session needs input or attention
- Keep session data and prompts on the local machine without cloud services or telemetry
- Run each session in its own git worktree, branch and directory
- Wrap sessions in a sandboxed container runtime
- Let the developer inspect agent changes before applying or merging
- Jump directly to the exact terminal pane, tab or editor window
- Organize sessions with split panes and tabs
- Support voice input and spoken session summaries
- Control how agent permission requests are accepted or denied
- Track token and quota use across sessions and accounts
- Capture tool call history, diff counts and final session summaries
- Select the best agent and account for a given task
- Connect to remote development machines over SSH
- Surface likely command failures and inline guidance
- Read recent shell output and offer context-aware suggestions
- Use GPU-accelerated rendering for many agent processes
Build it yourself with your AI system
Build this app yourself, no coding needed
Start with a quick version you can try in a few minutes. Like it? Then build the full app by copying and pasting our step-by-step instructions: everything is prepared for you.
Sign in to see how to build it yourself
Build a quick version to try, or get the full app pack for Parallel coding agent session control desk with the step-by-step building instructions. You don't need any technical skills: you copy, paste and answer a few questions. Both are included in the membership.
4 Have it built for you days to a few weeks
Rather not do it yourself, or want it fully tailored to your data, your way of working and your brand? Nexibeo builds Parallel coding agent session control desk with you.
What's in the app pack
Included in the Complete AI Training membership.
- The building instructions your AI follows, step by step
- The questions your AI will ask you about your business before it starts
- A clickable demo you can open in your browser, to see how it should work
- A detailed blueprint of the screens, the information it keeps and the checks it runs
Become a member to get the app packAlready a member? Sign in
The files, for the technically curious
- START-HERE.mdHow to build it with your own AI (read first)3 KB
- README.mdOverview and links4 KB
- questions.mdQuestions to answer before you build2 KB
- prompt-cloudflare.mdThe full build prompt, hosted on Cloudflare25 KB
- prompt-vps.mdThe same build on your own server (Docker)25 KB
- spec.jsonData model, API, AI pipeline, acceptance criteria12 KB
- demo/index.htmlThe working demo on sample data201 KB
Questions
Do I need to know how to code?
No. You copy and paste the prompts on this page into ChatGPT or Claude, and the AI does the building. When it asks you something, you answer in your own words.
What does it cost?
The quick version, the app pack and the step-by-step instructions are for members: you pay the membership price, not a price per app (see the plans). Building the full app uses your own ChatGPT or Claude subscription. Putting it online is often cheap or no cost at the start, and your AI tells you before anything costs money.
How long does it take?
The quick version: about two minutes. The real app: an afternoon for a first version you can use, longer if you want every feature.
Can I change it to fit my business?
Yes. Tell your AI what to change in plain words, like “add a column for the price” or “use our logo and colours”. Or have Nexibeo build and customise it for you.
More detailsHow the AI works, safeguards and what to build first
Keep several agent sessions visible, alive and isolated in one local workspace. For developers and small engineering teams running several AI coding agents in parallel on one machine, convert local agent sessions, repository state, terminal output and permission events into a reviewed, merge-ready change set per session. The benefit is a testable hypothesis, measured through sessions completed without lost context and review time per merged change; do not assume that AI output alone produces business value.
Confirm the buyer's problem and scope, collect local agent sessions, repository state, terminal output and permission events, then follow this sequence: 1. Show status of several parallel agent sessions in one board. 2. Keep sessions and context alive across restarts, SSH drops and window closures. 3. Alert the user when a session needs input or attention. Resolve uncertain cases with qualified reviewers, approve reviewed, merge-ready change set per session, and measure sessions completed without lost context and review time per merged change against a documented baseline.
How the AI works
Use AI to interpret permitted inputs, suggest structured mappings and generate candidate outputs for the three stated task modules. Use deterministic code for arithmetic, schema validation, hard constraints and reproducible tests. Review source-linked explanations and uncertainty before accepting results. One local machine and one repository layout; final merge and release decisions remain with the developer. A model suggestion is never a verified fact, professional decision or authorization to act.
Safeguards
Preserve code ownership, source attribution, license accuracy and usage permissions. Developers approve substantive changes and release scope. One local machine and one repository layout; final merge and release decisions remain with the developer. Keep all consequential actions under authorized human control and do not fabricate missing inputs, permissions, professional judgments or market evidence.
What to build first
Pilot scope: One local machine and one repository layout; final merge and release decisions remain with the developer. Implement one approved input format, a bounded representative case set and the first two task modules: show status of several parallel agent sessions in one board; keep sessions and context alive across restarts, SSH drops and window closures. Support the third module with operator review: alert the user when a session needs input or attention. Include source references, corrections, basic organization access, approval states, export and value measurement. Use managed operator assistance for unresolved exceptions. The cost estimate covers this narrow prototype, not unrestricted multi-tenant scale, complex production integrations, specialist certification or physical operations.
What it can connect to
Developer-owned repositories, authorized terminals and permitted local tools. Local git, container runtimes, SSH hosts and editor or IDE destinations. Start with file exchange and validate destination specifications before promising direct publishing. Start with authorized file exchange. Validate current provider access, usage rights and schema behavior before promising a connector.
The screens in detail
Primary screens: Session board, Session detail with terminal and diff, Review and merge queue. Use a status grid for sessions, a large central terminal and diff canvas, and a right-hand panel for permissions, token use and history. Let users compare agent branches side by side. Display running, waiting for input, failed and merged states. Provide a jump-to-terminal action and a local-only data notice. Make the task-specific outcome reviewed, merge-ready change set per session visible beside its evidence, review state and value baseline.
