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Khwand
Test, harden, and monitor AI agents
Khwand helps teams test, harden, and monitor AI agents before they break in production. Catch regressions, prompt drift, tool failures, and reliability issues with automated evaluations built for agentic systems.
Hey Product Hunt 👋
Khwand started from a frustration we kept seeing everywhere in AI development: teams can build AI products incredibly fast — but keeping them reliable in production is still painfully hard.
You can vibe-code a feature in an afternoon, ship an agent workflow, or wire up a powerful LLM app quickly. But the moment prompts drift, models update, edge cases appear, or user behavior changes, things quietly break. Traditional CI/CD wasn’t designed for software where the logic itself is probabilistic.
We built Khwand because we wanted an answer to a simple question:
**How do you ship AI-native software with confidence?**
At first, we thought the solution was “better testing.” But while building, our thinking evolved. We realized static tests weren’t enough for systems powered by LLMs. AI apps need something closer to an autonomous quality layer — one that stress-tests changes, catches regressions, benchmarks model behavior, and fixes failures *before* users experience them.
That shift completely changed our approach and became the foundation of Khwand.
Today, Khwand acts like a self-healing CI/CD layer for AI-native software — helping teams test, validate, and stabilize LLM-powered apps and agentic workflows without relying on guesswork.
This launch is exciting because we know we’re not the only ones wrestling with brittle AI systems and unpredictable behavior. If you’re building with LLMs, agents, or vibe-coded products, we’d genuinely love to hear: **what’s been your biggest reliability headache so far?** 👀
About Khwand on Product Hunt
“Test, harden, and monitor AI agents”
Khwand was submitted on Product Hunt and earned 0 upvotes and 1 comments, placing #9 on the daily leaderboard. Khwand helps teams test, harden, and monitor AI agents before they break in production. Catch regressions, prompt drift, tool failures, and reliability issues with automated evaluations built for agentic systems.
On the analytics side, Khwand competes within Productivity, Developer Tools and Artificial Intelligence — topics that collectively have 1.6M followers on Product Hunt. The dashboard above tracks how Khwand performed against the three products that launched closest to it on the same day.
Who hunted Khwand?
Khwand was hunted by Fahad Hafeez. 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.
For a complete overview of Khwand including community comment highlights and product details, visit the product overview.
Fahad Hafeez