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AI agents are powerful, but debugging them is often harder than fixing them. When an agent fails, engineers spend hours digging through logs, prompts, and tool outputs trying to understand what happened. Capsule is the flight recorder for AI agents—recording prompts, tool calls, memory, and execution state into a replayable artifact so teams can replay failures, identify root causes faster, and build more reliable AI systems.
Hey Product Hunt 👋
A question for anyone building AI agents:
Have you ever had an agent fail in production and then spent hours trying to answer a simple question: "What exactly happened?"
You have logs. You have traces. You have prompts.
But reproducing the exact execution path is often harder than fixing the bug itself.
Engineering teams can spend hours reconstructing incidents before they can even start solving them. That's time that could be spent shipping features, improving products, or serving customers.
That's the problem that led us to Capsule.
Capsule records prompts, tool calls, model outputs, memory, and execution state into a replayable artifact so you can step through an agent run exactly as it happened instead of piecing it together from logs.
The goal is simple: spend less time investigating, reduce the cost of AI failures, and spend more time building.
We're still early and would love feedback from developers:
• How are you debugging agent failures today?
• What's the most frustrating AI bug you've encountered?
• What information do you wish you had during an incident?
We'll be here all day answering questions. Thanks for checking out Capsule 🚀
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About Capsule on Product Hunt
“The flight recorder for AI agents”
Capsule was submitted on Product Hunt and earned 0 upvotes and 1 comments, placing #155 on the daily leaderboard. AI agents are powerful, but debugging them is often harder than fixing them. When an agent fails, engineers spend hours digging through logs, prompts, and tool outputs trying to understand what happened. Capsule is the flight recorder for AI agents—recording prompts, tool calls, memory, and execution state into a replayable artifact so teams can replay failures, identify root causes faster, and build more reliable AI systems.
Capsule was featured in Software Engineering (42.7k followers), Developer Tools (515.4k followers), Artificial Intelligence (473.1k followers) and GitHub (41.3k followers) on Product Hunt. Together, these topics include over 211.7k products, making this a competitive space to launch in.
Who hunted Capsule?
Capsule was hunted by Anush Gupta. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
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Anush Gupta