Chronos is the temporal compute layer for autonomous systems. It branches, evaluates, and collapses a million possible futures in milliseconds — so agents make decisions like humans do: by thinking first.
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Maker
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We're excited to finally share what we've been building.
Most AI helps you answer the next question. We wanted to build something that helps you make better long-term decisions.
Our workspace remembers your goals, knowledge, and previous decisions, so every conversation builds on the last instead of starting from scratch. We're just getting started, and we'd love your feedback on what works, what doesn't, and what you'd like to see next.
Thanks for checking it out!
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Love the concept of branching and collapsing futures in real time. One thing I'd love to see is a visual timeline debugger where you can scrub through the simulated branches and see exactly which decision paths were considered and dropped, plus the scoring that killed each one. Would make trust and tuning way easier.
One of our goals is to make the reasoning behind each decision transparent, not just present the final recommendation. Being able to scrub through different branches, see which paths were explored, and understand why some were discarded would make the system much more trustworthy.
Definitely adding this to our ideas list, thanks for the suggestion!
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love the branching futures idea, would be cool if you added a visual timeline view so we can scrub through the collapsed branches and see which decision path the agent actually took versus the alternatives it considered.
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Maker
@helindiyar5o3i Love that idea. We actually have something similar on our roadmap. Thanks for the suggestion!
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Tried this on a scheduling agent and the branching eval was way faster than the Monte Carlo setup I had been running. Genuinely impressed by how quickly it collapsed the futures down to a clean decision path.
Love the concept of branching and collapsing futures in real time. One thing I'd love to see is a visual timeline debugger where you can scrub through the simulated branches and see exactly which decision paths were considered and dropped, plus the scoring that killed each one. Would make trust and tuning way easier.
@berkekanatrqdx I really like that idea.
One of our goals is to make the reasoning behind each decision transparent, not just present the final recommendation. Being able to scrub through different branches, see which paths were explored, and understand why some were discarded would make the system much more trustworthy.
Definitely adding this to our ideas list, thanks for the suggestion!
love the branching futures idea, would be cool if you added a visual timeline view so we can scrub through the collapsed branches and see which decision path the agent actually took versus the alternatives it considered.
@helindiyar5o3i Love that idea. We actually have something similar on our roadmap. Thanks for the suggestion!
Tried this on a scheduling agent and the branching eval was way faster than the Monte Carlo setup I had been running. Genuinely impressed by how quickly it collapsed the futures down to a clean decision path.