Introducing Advanced AI Observability: See the Whole Agent Journey
From the source: Kong BlogWhen an AI application fails, knowing that an individual model call returned a 200 isn’t enough. You need to know what led to it. Kong stitches the interactions associated with an AI session together, giving developers a view across the sequence of model…
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API & AI Summit 2026 Launch Recap
Standing up a production agent means taking it through six stages: At API & AI Summit, we announced the evolution of Kong Konnect into the AI Connectivity Platform and announced a slate of launches built around that idea. Here's what we launched, where…
Kong AI Gateway 2.2: Built for what comes next in AI
AI is not just producing different answers. It is starting to do different kinds of work. JEV introduces a different model for using AI: instead of generating text, it returns typed, probabilistic decisions that software can act on directly. By returning…
Introducing Kong AI Registry: Self-Service Discovery for Agents
API management solved a similar problem for developers. Instead of asking a platform team every time they needed an API, developers could go to a Developer Portal, discover what was available to them, and start building, within the governance boundaries…
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The app your agent built in minutes stays on the same Postgres from prototype to petabyte.
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More data, more tools and more control so your agent has what it needs to observe your project, investigate issues and propose fixes, autonomously.
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RustRover vs VS Code + rust-analyzer: What Changes in Your Rust Workflow
As the team behind a dedicated Rust IDE, we’re naturally curious to see how RustRover stacks up against other popular setups for Rust development and the strengths and trade-offs of each one. This article is the first in a series where we’ll look at different Rust workflows. We’re not unbiased, but we want to give […]


