Rerun - The easiest way to build AI agents for all your tasks
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Most AI agents are black boxes. Rerun isn't. Build no-code agents that run 24/7, chasing invoices, qualifying leads, clearing your inbox, and watch every step in real time. They pause for approval before anything sensitive. Each workspace gets its own private server. Start with the included model, or connect your own API key or subscription
Replies
Love how every workspace gets its own private server, that kind of isolation is honestly rare for no-code tools and shows you clearly thought through real business use cases, not just the demo.
Rerun
@ozanzbaykulvdq Yep, every workspace is on a private server for full control and total security
Excited to see what you're gonna build in the next few weeks
Love that I can actually see what the agent is doing in real time, that's the missing piece in most no-code tools. One idea: add a way to export the full execution log as a shareable link so I can send a client a recap of what the agent did without screen recording. Would save a ton of back and forth.
Rerun
@tubauwvo Thanks for your feedback, it’s already possible with the “Dashboard” option
You can drag’n drop pre-made widgets for monitoring, analysis, approval, etc.
Feel free to reach out to support for guidance
The live step viewing is genuinely useful, way more transparent than other agent builders I've tried. One thing that would seal the deal for me is a simple test mode where I can replay a past run with tweaked inputs, so I can fine tune prompts without spinning up real tasks each time.
Rerun
@kerimkkavuggeq Oh good catch, hadn’t thought of that yet! Adding it to the roadmap
honestly the live step viewer sounds super useful for debugging agents. one thing i'd love is the ability to rewind and replay a specific portion of an agent run instead of just watching it forward, especially when something weird happens and you wanna trace back what triggered it
Rerun
@azizileskaxtxg Rerun was really born from this simple realization. We’ve got agents, but we don’t fully get their journey. So, we built tools to monitor that. And honestly, it’s a joy to use every day
One thing that would really help me trust the agents even more is a simple replay button for past runs, so I can scrub through and see exactly what decisions were made when something went sideways. Live monitoring is great, but most of my debugging happens after the fact and right now I'd have to dig through logs to piece it together. A timeline-style playback view per run would make audits and post-mortems so much easier.
Real-time visibility is a huge plus here, love that. One thing I'd love is the ability to set custom approval thresholds per agent, so something like "auto-approve invoices under $500 but ping me for anything above that." Would save a lot of clicks on the routine stuff while still keeping the safety net for the bigger decisions.
Terminal Candy
the pause for approval before anything sensitive part is the right call. i live in coding agents all day and the failure mode is never the work, it's the thing it does confidently that you didn't want. how do you decide what counts as sensitive, is that configurable per agent?
I feel like debugging AI agents is becoming as important as building them. Have you found that users spend more time creating agents or understanding why they failed?
the live dashboard showing every run/token/decision is the part I'd actually use daily, most agent tools just give you a final log line and nothing in between. how configurable is the 'pause for approval on anything sensitive' rule - is that a fixed list of action types you ship with, or can you define per-workflow what counts as sensitive for your own use case?
HarnessRouter
Real-time step logs, approval gates, and a private server per workspace make always-on agents much easier to trust. Could teams set per-agent token budgets or automatic stop thresholds so a looping workflow cannot burn through connected model credits?