AI agents are increasingly making real decisions in businesses. They qualify leads, respond to customers, analyze data, and sometimes trigger actions that affect revenue or customer experience. As these systems move from suggesting to actually deciding, mistakes become inevitable.
When that happens, responsibility becomes unclear. The user configured the system, the company built the product, and the underlying models often come from another provider. If an AI agent makes the wrong call and it impacts a customer or revenue, where should accountability actually sit?
Curious how others are thinking about this. Who should be responsible in such cases, and are there any legal guidelines or draft regulations emerging around this?
Human-in-the-loop inside workflows is my favorite feature.
The moment I saw a workflow pause for human review and then continue automatically… I was sold.
The TinyComposer node surprised me. The emails it writes are not “AI-ish” they’re actually usable, on-tone, and fit the context perfectly.
Love the “one command for everything” idea. Half my day is spent jumping between tools and random scripts anyway. If TinyCommand can genuinely replace that duct-tape setup, I’m in.
@kshitij_mishra4 Thanks for this!
That’s exactly the pain point we set out to solve. Most teams end up stitching together forms, sheets, workflow tools, scripts, and email systems just to keep simple processes running.
With TinyCommand, the goal is to bring all of that into one place so you can collect data, automate actions, and send communications without the duct tape.
Excited for you to try it & we’d love to hear your thoughts once you do!
@joyal_a_johney Thanks for your support!
Appreciate that the platform doesn’t hide complexity, just makes it easier to work with.
Congratulations on the launch 🎉 🎉
@shubham_pratap Thanks for your support!