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@varbear shared a link, 1 week, 3 days ago
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Company as Code

Organisations rely heavily on digital systems, yet manage important organisational data using outdated manual methods despite advanced automation capabilities in other areas. A novel "Company as Code" concept proposes a programmatic representation of the entire organisation, enabling structured, ver.. read more  

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@kaptain shared a link, 1 week, 3 days ago
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How GKE Inference Gateway improved latency for Vertex AI

Vertex AI now plays nice withGKE Inference Gateway, hooking into the Kubernetes Gateway API to manage serious generative AI workloads. What’s new:load-awareandcontent-aware routing. It pulls from Prometheus metrics and leverages KV cache context to keep latency low and throughput high - exactly what.. read more  

How GKE Inference Gateway improved latency for Vertex AI
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How Kubernetes Learned to Resize Pods Without Restarting Them

Kubernetes v1.35 introduces in-place Pod resizing, allowing dynamic adjustments to CPU and memory limits without restarting containers. This feature addresses the operational gap of vertical scaling in Kubernetes by maintaining the same Pod UID and workload identity during resizing. With this breakt.. read more  

How Kubernetes Learned to Resize Pods Without Restarting Them
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@kaptain shared a link, 1 week, 3 days ago
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Why Kubernetes is retiring Ingress NGINX

The Kubernetes Steering Committee is pulling the plug onIngress NGINX- official support ends March 2026. No more updates. No security patches. Gone. Why? It's been coasting on fumes. One or two part-time maintainers couldn't keep up. The tech debt piled up. Now it's a security liability. What's next.. read more  

Why Kubernetes is retiring Ingress NGINX
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@kaptain shared a link, 1 week, 3 days ago
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Introducing Node Readiness Controller

Kubernetes just dropped theNode Readiness Controller- a smarter way to track node health. It slaps taints on nodes based on custom signals, not just the plain old "Ready" status. The goal? Safer pod scheduling that actually reflects what’s going on under the hood. It's powered by theNodeReadinessRul.. read more  

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@kaptain shared a link, 1 week, 3 days ago
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CVE-2026-22039: Kyverno Authorization Bypass

Kyverno - a CNCF policy engine for Kubernetes - just dropped a critical one:CVE-2026-22039. It lets limited-access users jump namespaces by hijacking Kyverno'scluster-wide ServiceAccountthrough crafty use of policy context variable substitution. Think privilege escalation without breaking a sweat. I.. read more  

CVE-2026-22039: Kyverno Authorization Bypass
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@kala shared a link, 1 week, 3 days ago
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Self-Optimizing Football Chatbot Guided by Domain Experts on

Generic LLM judges and static prompts fail to capture domain-specific nuance in football defensive analysis. The architecture for self-optimizing agents built on Databricks Agent Framework allows developers to continuously improve AI quality using MLflow and expert feedback. The agent, such as a DC .. read more  

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@kala shared a link, 1 week, 3 days ago
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Nathan Lambert: Open Models Will Never Catch Up

Open models will be the engine for the next ten years of AI research, according to Nathan Lambert, a research scientist at AI2. He explains that while open models may not catch up with closed ones due to fewer resources, they are still crucial for innovation. Lambert emphasizes the importance of int.. read more  

Nathan Lambert: Open Models Will Never Catch Up
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@kala shared a link, 1 week, 3 days ago
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Generative Pen-trained Transformer

MeetGPenT, an open-source, wall-mounted polargraph pen plotter with a flair for generative art. It blends custom hardware, Marlin firmware, a Flask web UI running on Raspberry Pi, and Gemini-generated drawing prompts. The stack? Machina + LLM. Prompts go in, JSON drawing commands come out. That driv.. read more  

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Towards self-driving codebases

OpenAI spun up a swarm of GPT-5.x agents - thousands of them. Over a week-long sprint, they cranked out runnable browser code and shipped it nonstop. The system hit 1,000 commits an hour across 10 million tool calls. The architecture? A planner-worker stack. Hierarchical. Recursive. Lean on agent ch.. read more  

Towards self-driving codebases
FastMCP is an open-source Python framework designed to simplify the development of Model Context Protocol servers. It allows developers to define MCP components such as tools, resources, and prompts using decorators, and to organize them through a modular architecture built around providers and transforms. Providers determine where components originate, including local code, directories, OpenAPI specifications, or remote MCP servers. Transforms modify components as they flow to clients, enabling namespacing, filtering, versioning, and visibility control.

The framework supports component versioning, per-component authorization, and middleware for cross-cutting concerns such as authentication and logging. It includes a built-in command-line interface for listing, calling, discovering, and installing MCP servers. FastMCP also supports session-scoped state, background task execution, OpenTelemetry tracing, pagination for large component sets, and transport options including stdio and HTTP-based protocols.

FastMCP is intended for developers building agent-compatible backends and structured tool interfaces for large language model systems that implement the Model Context Protocol.