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Manus AI Launches ‘Wide Research,’ Pitting 100-Agent Swarms Against ‘Deep Research‘ from Google and OpenAI

Manus just droppedWide Research—a swarm of 100+ AI agents, each spun up as a Turing-complete VM. They don’t follow orders. They solve massive tasks in parallel, straight from natural language prompts. Forget rigid chains of command. These agents don’t play roles—they run jobs. No hierarchies. No br.. read more  

Manus AI Launches ‘Wide Research,’ Pitting 100-Agent Swarms Against ‘Deep Research‘ from Google and OpenAI
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Cursor AI Code Editor Fixed Flaw Allowing Attackers to Run Commands via Prompt Injection

XM Cyber dropped a practical guide for rolling outContinuous Threat Exposure Management (CTEM)with its platform—geared for those eyeing 2025 readiness. It dives into wiring up real-time exposure visibility, validating actual risk, and tightening up remediation across complex enterprise setups. Why .. read more  

Cursor AI Code Editor Fixed Flaw Allowing Attackers to Run Commands via Prompt Injection
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GPT-5 is here

GPT-5 tightens reasoning and lands cleaner hits inmath,science,finance, andlaw. It outpaces GPT-4—not just wider, but deeper... read more  

GPT-5 is here
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Anthropic says OpenAI engineers using Claude Code ahead of GPT-5 launch

Anthropic just shut the door on OpenAI, yanking access to theClaude Code APIafter spotting ChatGPT engineers poking around—likely prepping forGPT-5. Claude Codeisn’t just an internal toy. It’s a serious coding co-pilot, used in the wild by devs who want answers without babysitting a model. Market .. read more  

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Blue‑Green Deployment in 1 diagram and 195 words

Blue-Green deployment runs two matching environments so you can flip traffic with zero downtime—and yank it back fast if something breaks. Kubernetes + IstioandSpinnakerhandle the heavy lifting. They steer traffic between versions and keep infra lean... read more  

Blue‑Green Deployment in 1 diagram and 195 words
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Perplexity is using stealth, undeclared crawlers to evade website no-crawl directives

Perplexity AI’s stealth crawling behavior includes modifying user agents and source ASNs to avoid website blocks, highlighting the importance of transparent bot behavior... read more  

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Project Ire autonomously identifies malware at scale

Microsoft just droppedProject Ire, an autonomous AI that tears through software like a experienced reverse engineer. It decompiles, analyzes, classifies malware—all on its own. Under the hood: LLMs, decompilers, and a tool-use API running the show. On public Windows driver datasets, it scored0.98 p.. read more  

Project Ire autonomously identifies malware at scale
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Writing an internal Terraform provider from A to Z

Typeform rolled their ownTerraform providerto wrangle runtime data through an internal API. Built with HashiCorp’sGo SDK, the official scaffolding framework, and wired up withacceptance testsfor full lifecycle muscle. They skipped the publicTerraform Registryentirely. Instead, they shipped provider.. read more  

Writing an internal Terraform provider from A to Z
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Introducing Approvals in Pulumi ESC

Pulumi ESC just leveled up withApprovals—structured reviews for environment config changes, straight from Console, CLI, SDK, or VS Code. Think pull requests, but for your infra settings. No more YOLO updates. Teams can now lock down config changes with required sign-offs. More control. Cleaner logs.. read more  

Introducing Approvals in Pulumi ESC
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🚨 Azure Service Health Built-In Policy (Preview) – Now Available! 

Microsoft just droppedAzure Service Health Built-In Policy(Preview). It lets teams push Service Health alerts across every Azure subscription—automatically—using Azure Policy. No more piecemeal setup. It folds in AMBA lessons, supports custom rules and action groups, and locks in alert coverage at .. read more  

🚨 Azure Service Health Built-In Policy (Preview) – Now Available! 
Grafana Tempo is a distributed tracing backend built for massive scale and low operational overhead. Unlike traditional tracing systems that depend on complex databases, Tempo uses object storage—such as S3, GCS, or Azure Blob Storage—to store trace data, making it highly cost-effective and resilient. Tempo is part of the Grafana observability stack and integrates natively with Grafana, Prometheus, and Loki, enabling unified visualization and correlation across metrics, logs, and traces.

Technically, Tempo supports ingestion from major tracing protocols including Jaeger, Zipkin, OpenCensus, and OpenTelemetry, ensuring easy interoperability. It features TraceQL, a domain-specific query language for traces inspired by PromQL and LogQL, allowing developers to perform targeted searches and complex trace-based analytics. The newer TraceQL Metrics capability even lets users derive metrics directly from trace data, bridging the gap between tracing and performance analysis.

Tempo’s Traces Drilldown UI further enhances usability by providing intuitive, queryless analysis of latency, errors, and performance bottlenecks. Combined with the tempo-cli and tempo-vulture tools, it delivers a full suite for trace collection, verification, and debugging.

Built in Go and following OpenTelemetry standards, Grafana Tempo is ideal for organizations seeking scalable, vendor-neutral distributed tracing to power observability at cloud scale.