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How Microsoft Evaluates LLMs in Azure AI Foundry: A Practical, End-to-End Playbook

Microsoft’s Azure AI Foundry just released a proper workflow for putting LLMs through their paces. Thinkoffline/online tests,human-in-the-loop checks,automated scoring, and evencustom evaluators—all wired into one system. At the heart of it: the newAzure AI Evaluation SDK. You can run it locally whi.. read more  

How Microsoft Evaluates LLMs in Azure AI Foundry: A Practical, End-to-End Playbook
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Structured Vibe Coding: A Smarter Way to Build AI Agents with GitHub Copilot

A fresh approach calledstructured vibe codingblends human-style team habits with AI workflows. Specs, GitHub Issues, and Copilot now pull agents into the loop like actual teammates. Powered byGitHub Copilot Coding AgentsandAzure AI Foundry, devs can run full AI-driven sprints—spec to PR—right inside.. read more  

Structured Vibe Coding: A Smarter Way to Build AI Agents with GitHub Copilot
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Claude Skills are awesome, maybe a bigger deal than MCP

Anthropic releasedClaude Skills—a lean way to snap specialized instructions and scripts into Claude without bloating the prompt. Each “skill” lives in a folder with Markdown and optional code. Frontmatter tags tell Claude when to load what. No need to cram everything into the context window—Claude g.. read more  

Claude Skills are awesome, maybe a bigger deal than MCP
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OpenAI Needs $400 Billion In The Next 12 Months

OpenAI, Broadcom, NVIDIA, and AMD say they’ll deploy10GWof AI compute by end of 2026. That includes custom chips and slews of 1GW data centers. What they didn’t say: where, when, or how. No sites named. No shovels in dirt. OpenAI alone aims for250GW by 2033—a moonshot that needs$400Bin the next 12 m.. read more  

OpenAI Needs $400 Billion In The Next 12 Months
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How AI can help your DevSecOps pipeline

AI is sliding into DevSecOps and turning security into less of a slog. Tools likeDarktrace PREVENT,CrowdStrike Falcon, andMicrosoft Security Copilotaren't just watching—they're flagging weird behavior, proposing fixes, and unclogging patch pipelines inside CI/CD. The shift:DevSecOps is on its way to.. read more  

How AI can help your DevSecOps pipeline
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How Shopify Handles 30TB of Data Every Minute with a Monolithic Architecture

Shopify handles billions of Black Friday requests on amodular monolith, built with Ruby on Rails and kept in check byPackwerk. Domain boundaries are enforced. Chaos averted. Inside, it blendsHexagonal Architecture, isolatedPods, and real-time Kafka pipes. The system scales without fracturing into mi.. read more  

How Shopify Handles 30TB of Data Every Minute with a Monolithic Architecture
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How I Block All 26 Million Of Your Curl Requests

A developer built a razor-sharp TLS fingerprinting and blocking tool—all in kernel space—witheBPFandXDP. It hooks into incoming packets, scrapes TLS Client Hello messages, and cranks out simplified JA4-style hashes from their cipher suite lists. The fun part? It's running under tight stack limits, s.. read more  

How I Block All 26 Million Of Your Curl Requests
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CVE-2025-49844 - The Redis CVSS 10.0 vulnerability and how we responded

Report URI closed the door on Redis CVE-2025-49844 fast. They rolled out ACL-based command blocks and jumped to Redis8.2.2, now running on a freshRedis Sentinel-based HA setup. To prove the fix stuck, they ran command counter checks and layered in enforced blocking rules—then pushed it all out fleet.. read more  

CVE-2025-49844 - The Redis CVSS 10.0 vulnerability and how we responded
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Migrating to Hetzner - We saved 76% on our cloud bills

DigitalSociety ditched AWS and DigitalOcean. Swapped the comfort of cloud for full control onHetzner, built onTalos Linux. PostgreSQL? Now running onCloudNativePG. Traffic flows throughIngress NGINXwithExternalDNShandling the names. The payoff: monthly costs dropped from $449.50 to under $100. ARM v.. read more  

Migrating to Hetzner - We saved 76% on our cloud bills
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Hosting Remote MCP Server on Azure Container Apps (ACA) using Streamable HTTP transport mechanism

A fresh setup shows how to runModel Context Protocol (MCP) servers over HTTPinsideAzure Container Apps—stateless, serverless, and ready for real-time jobs like live forex conversion. It pipes in a live API fallback, adds caching, and speaksJSON-RPC 2.0overPOST. You can spin it up withBicep templates.. read more  

Hosting Remote MCP Server on Azure Container Apps (ACA) using Streamable HTTP transport mechanism
GPT-5.4 is OpenAI’s latest frontier AI model designed to perform complex professional and technical work more reliably. It combines advances in reasoning, coding, tool use, and long-context understanding into a single system capable of handling multi-step workflows across software environments. The model builds on earlier GPT-5 releases while integrating the strong coding capabilities previously introduced with GPT-5.3-Codex.

One of the defining features of GPT-5.4 is its ability to operate as part of agent-style workflows. The model can interact with tools, APIs, and external systems to complete tasks that extend beyond simple text generation. It also introduces native computer-use capabilities, allowing AI agents to operate applications using keyboard and mouse commands, screenshots, and browser automation frameworks such as Playwright.

GPT-5.4 supports context windows of up to one million tokens, enabling it to process and reason over very large documents, long conversations, or complex project contexts. This makes it suitable for tasks such as analyzing codebases, generating technical documentation, working with large spreadsheets, or coordinating long-running workflows. The model also introduces a feature called tool search, which allows it to dynamically retrieve tool definitions only when needed. This reduces token usage and makes it more efficient to work with large ecosystems of tools, including environments with dozens of APIs or MCP servers.

In addition to improved reasoning and automation capabilities, GPT-5.4 focuses on real-world productivity tasks. It performs better at generating and editing spreadsheets, presentations, and documents, and it is designed to maintain stronger context across longer reasoning processes. The model also improves factual accuracy and reduces hallucinations compared with previous versions.

GPT-5.4 is available across OpenAI’s ecosystem, including ChatGPT, the OpenAI API, and Codex. A higher-performance variant, GPT-5.4 Pro, is also available for users and developers who require maximum performance for complex tasks such as advanced research, large-scale automation, and demanding engineering workflows. Together, these capabilities position GPT-5.4 as a model aimed not just at conversation, but at executing real work across software systems.