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@kala shared a link, 1 month, 3 weeks ago
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AI as tradecraft: How threat actors operationalize AI

Microsoft observes threat actors operationalizeAIandLLMsacross the cyberattack lifecycle. They accelerate reconnaissance, phishing, malware development, and post‑compromise triage. Actors abusejailbreakingtechniques andGANs. They craft personas, generate look‑alike domains, embed runtime‑adaptive pa.. read more  

AI as tradecraft: How threat actors operationalize AI
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@kala shared a link, 1 month, 3 weeks ago
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The reason big tech is giving away AI agent frameworks

A catalog of majoragent frameworks: LangGraph, CrewAI, Google ADK, AWS Strands, Microsoft Agent Framework, OpenAI Agents SDK, Mastra, Pydantic AI, Agno. Hyperscalers co-design free SDKs (e.g.,Strands,ADK). They tie those SDKs to metered runtimes -Bedrock,Vertex AI. Revenue shifts to inference and de.. read more  

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@kala shared a link, 1 month, 3 weeks ago
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LLMs are getting better at unmasking people online

Researchers at ETH Zurich show LLMs can stitch anonymous bios to public web data and reidentify users across platforms. Fine-tuned models and agent chains parse unstructured text and automate deanonymization in minutes at penny-level inference costs... read more  

LLMs are getting better at unmasking people online
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@devopslinks shared a link, 1 month, 3 weeks ago
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Amazon is back up after outage affecting tens of thousands of shoppers

Amazon faced an outage, affecting tens of thousands of shoppers globally on Thursday afternoon. Downdetector reported a surge in complaints, peaking at 20,000 by 3:49 p.m. ET. The outage involved checkout and pricing errors caused by a software code deployment... read more  

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@devopslinks shared a link, 1 month, 3 weeks ago
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Why Serverless Compute Partners Are Now More Important Than Ever

The note saysAIworkloads are bursty. They spawn parallel tool calls, pull multi‑GB model weights into RAM, and endure long cold starts (e.g.,vLLM,SGLang). Companies wrestle with a fragmentedGPUmarket and poor peakGPU utilization. To hit latency, compliance, and cost targets they adoptmulti‑region/mu.. read more  

Why Serverless Compute Partners Are Now More Important Than Ever
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@devopslinks shared a link, 1 month, 3 weeks ago
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AWS Cost Optimization Best Practices: A Maturity-Based Guide [2026]

The guide maps a five-stagematurity model— fromVisibilitytoFinOps Culture. It prescribes staged actions before commitment purchases. It recommends turning onCost ExplorerandAWS Budgets, enforcingtag policies, runningCompute Optimizer, testingGraviton, and usingCloudBurn/Amazon Qfor pre-deploy estima.. read more  

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@devopslinks shared a link, 1 month, 3 weeks ago
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Draw.io MCP for Diagram Generation: Why It’s Worth Using

Draw.io MCPlinks theModel Context Protocoltodraw.io. It ingests structured input (text,CSV,Mermaid) and emitsdraw.io XML, PNG/SVG, or hosted links. Draw.io MCPruns as anMCP Tool Server, CLI, or Copilot skill. It drafts small graphs (<50 nodes) in seconds and stores diagrams inGitfor diffs andCI/CDau.. read more  

Draw.io MCP for Diagram Generation: Why It’s Worth Using
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@devopslinks shared a link, 1 month, 3 weeks ago
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How I Dropped Our Production Database and Now Pay 10% More for AWS

Planned migration shifts the static site fromGitHub PagestoAWS S3. DNS moves toAWS.Djangostages on a subdomain before the main domain swaps. ATerraformauto-approve ran with no remote state. It destroyed productionRDS,VPC,ECS, and automated snapshots.AWSfound a hidden snapshot and recovered the DB in.. read more  

How I Dropped Our Production Database and Now Pay 10% More for AWS
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@shubham321 shared a post, 1 month, 3 weeks ago
Software engineer, Keploy

What Is QA Automation? Benefits, Tools, Challenges & Future

QA automation is a modern software testing approach that uses automated tools and frameworks to execute test cases efficiently and consistently. Instead of relying solely on manual testing, QA automation enables teams to validate application functionality, performance, and reliability at every stage of the development lifecycle. It plays a crucial role in Agile and DevOps environments, where frequent code changes and faster release cycles demand continuous testing.

One of the biggest advantages of QA automation is speed. Automated tests can run in minutes, allowing teams to detect defects early and provide quick feedback to developers. This leads to improved software quality and reduced risk of critical issues reaching production. Automation also enhances accuracy by eliminating human errors that commonly occur in repetitive manual testing tasks.

qa automation
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@suarezsara shared a post, 1 month, 3 weeks ago

Why SharePoint Application Development Still Powers Enterprise Collaboration in 2026

Learn how businesses use SharePoint for workflow automation, seamless Microsoft 365 integration, and enhanced governance.

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.