What's new in Linux kernel for PostgreSQL

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Ryu, whose father-in-law is still part of Kim Jong Un's inner circle, says the debate around Kim's heir may be a goal in itself.

Babies are beautiful. I always want to smile at them in the street, perhaps because they are a rarer and more precious sight in this ageing country or because they remind me of my grandchildren. There are about 3.5 million children aged four and under, while dogs on the streets are a more plentiful 13.5 million. Is the dog boom compensating for fewer children? As time goes by, there are going to be ever more grandparents and ever fewer children to beam at foolishly.

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——“功成不必在我,功成必定有我”

Платон Щукин (Редактор отдела «Экономика»)

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Scenario generation + real conversation import - Our scenario generation agent bootstraps your test suite from a description of your agent. But real users find paths no generator anticipates, so we also ingest your production conversations and automatically extract test cases from them. Your coverage evolves as your users do.Mock tool platform - Agents call tools. Running simulations against real APIs is slow and flaky. Our mock tool platform lets you define tool schemas, behavior, and return values so simulations exercise tool selection and decision-making without touching production systems.Deterministic, structured test cases - LLMs are stochastic. A CI test that passes "most of the time" is useless. Rather than free-form prompts, our evaluators are defined as structured conditional action trees: explicit conditions that trigger specific responses, with support for fixed messages when word-for-word precision matters. This means the synthetic user behaves consistently across runs - same branching logic, same inputs - so a failure is a real regression, not noise.Cekura also monitors your live agent traffic. The obvious alternative here is a tracing platform like Langfuse or LangSmith - and they're great tools for debugging individual LLM calls. But conversational agents have a different failure mode: the bug isn't in any single turn, it's in how turns relate to each other. Take a verification flow that requires name, date of birth, and phone number before proceeding - if the agent skips asking for DOB and moves on anyway, every individual turn looks fine in isolation. The failure only becomes visible when you evaluate the full session as a unit. Cekura is built around this from the ground up.