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Quick tip from client work: every AI agent I ship gets a human escape hatch on day one. A lead who wants a person should reach one in one tap, no chatbot loop, no ticket form, no waiting for an email reply. The agencies that skip this learn the hard way, one frustrated prospect tells ten people the bot trapped them. Automation should speed up the conversation, not stand between a buyer and a human. Build the exit first, then build the agent.
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Did a motion for the Cockpit concept ⁕ 🔈 ON
Design & Creative Direction: Me
Motion & Sound: Claude Code
Cockpit is an AI agent management platform concept that helps teams:
- Set boundaries
- Monitor activity
- Manage approvals
- Track knowledge sources
- Measure performance and costs
It brings together five key AI UX challenges:
👉 Autonomy
👉 Observability
👉 Human Approvals
👉 Context
👉 Analytics
The idea is simple:
As AI agents become more capable, the experiences we design around them need to make their actions more transparent, predictable, and manageable.
Thanks!
Human approvals is the part most agent UIs skip. Good call making it one of the five challenges.
I’ve been working on a small skill called Manual Orchestrator to make longer projects with AI agents easier to manage.
The problem started with a familiar situation: one chat would accumulate plans, implementation details, corrections, and test results. By the time I was ready for the next phase, I wanted a fresh conversation without losing the decisions we’d already made.
Manual Orchestrator gives that process some structure. One chat acts as the orchestrator: it breaks the work into stages and writes a prompt for the next one. I run that prompt in a new session, then bring the result back. The orchestrator reviews it against the stage’s criteria before preparing the next prompt. If something needs fixing, I go back to the same worker session.
The skill also keeps a record in the project with the current stage, decisions, evidence, and next steps. That makes it easier to pause, resume, or hand the work to another session.
The handoff is manual. I choose when to open a session and carry the result back. The orchestrator and worker sessions can also use different agent CLIs, with the prompt adapted to the capabilities available.
It’s open source and still a work in progress. I’m using it to learn what helps in practice and where the workflow needs to improve. Installation has been checked for Codex, Claude Code, and Gemini CLI, but the full workflow hasn’t been tested across every CLI or version.
If you try it, I’d be interested in hearing what works and where it gets in your way.
I didn't agree with you fully because there are ways to remove the ai slope, I think a human skill + ai is a killer combo 💀...
But in short AI has given us the speed of 10x even sometimes its 100x, so the thing you have to learn is the basics process:
(Input -> Process -> Output)
and then you have to guide the ai and it will slay it off like a pro🔥
Trust me bros its true 🙌
Manual work is always better than ai slop you can use ai for some clips but full video made with ai is unprofessional and a waste of money and resources