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@idjuric660 shared a post, 10 months, 2 weeks ago
Technical Content Writer, Mailtrap

How to Send Emails in Cursor with Mailtrap MCP Server

If you want to send emails in Cursor, you won’t be able to do it since it doesn’t have built-in sending functionality. But don’t worry—I’ve got you covered! In this article, I’ll show you how to integrate Cursor withMailtrap MCPand start sending emails with simple prompts—whether you’re on Windows o..

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@anjali shared a link, 10 months, 2 weeks ago
Customer Marketing Manager, Last9

PostgreSQL Performance: Faster Queries and Better Throughput

Understand how PostgreSQL performance works, from MVCC to query planning, and how to optimize for better throughput and latency.

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@alberthiltonn shared a post, 10 months, 2 weeks ago

Top 12 Angular Best Practices that you need to consider in 2026

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Find out the top 12 Angular best practices to follow in 2026 for building robust and scalable web apps.

Top Angular Best Practices
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@idjuric660 shared a post, 10 months, 2 weeks ago
Technical Content Writer, Mailtrap

Improve Email Deliverability: Here’s How & Best Practices to Follow

Hitting the inbox is paramount, no matter how big or small a sender you are. If not… - Your marketing campaigns go unseen. - Your transactional emails fail to reach their destination. - Your efforts translate into lost revenue and damaged sender reputation. At Mailtrap, we help you improve deliverab..

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@laura_garcia shared a post, 10 months, 2 weeks ago
Software Developer, RELIANOID

Understanding Botnets & How to Defend Against Them

Botnets remain one of the biggest cybersecurity threats, enabling large-scale DDoS attacks, credential theft, and malware distribution. These networks of compromised devices operate silently, controlled by cybercriminals to exploit vulnerabilities. - How do botnets work? Infect devices via phishing,..

Blog2 Botnets Network Attacks RELIANOID protected
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@faun shared a link, 10 months, 2 weeks ago
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Scaling Netflix's threat detection pipelines without streaming

Netflix’s “Psycho Pattern” stitched togetherSpark, Kafka, and Airflowinto a relentless micro-batch pipeline. It tracked high watermarks for near-real-time threat detection—fast enough, sharp enough. Then came the Flink switch. Lower latency? Sure. But it missed the mark. Signal quality stayed flat... read more  

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@faun shared a link, 10 months, 2 weeks ago
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GitHub Copilot crosses 20M all-time users

GitHub Copilot just crossed20 million users. Five million joined last quarter alone. Enterprise usage? Up75%quarter-over-quarter. It’s now in the hands of90% of the Fortune 100, according to Microsoft. Here’s the kicker: Copilot’s AI coding biz is now bigger than all of GitHub’s revenue when Micros.. read more  

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@faun shared a link, 10 months, 2 weeks ago
FAUN.dev()

The many, many, many JavaScript runtimes of the last decade

JavaScript runtimes aren’t just multiplying—they’re splintering. Big engines likeV8,JavaScriptCore,QuickJS,Hermes, andSpiderMonkeynow sit at the core of purpose-built runtimes everywhere: cloud, edge, mobile, IoT, even smart TVs. Platforms likeCloudflare Workers,Deno Deploy,Bun,LLRT, andNativeScrip.. read more  

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@faun shared a link, 10 months, 2 weeks ago
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My Functional Programming Awakening: Patterns I'd Been Using All Along

A dev takes functional programming from Python class to JavaScript land—with surprising wins. The usual suspects show up:closures,function composition, and some spicyparser combinators. But the real magic? Swapping out side-effect soup forpure functions,Result-based error handling, andhigher-order f.. read more  

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@faun shared a link, 10 months, 2 weeks ago
FAUN.dev()

So you want to parse a PDF?

Out of 3,977 real-world PDFs, 0.5% broke during xref pointer parsing. Not a huge number—unless you're the one parsing them. The top culprit? Junk data before the start pointer. Classic. Other file weirdness: broken xref tables, bad object offsets, and inconsistent xref chains... read more  

Vertex AI is Google Cloud’s end-to-end machine learning and generative AI platform, designed to help teams build, deploy, and operate AI systems reliably at scale. It unifies data preparation, model training, evaluation, deployment, and monitoring into a single managed environment, reducing operational complexity while supporting advanced AI workloads.

Vertex AI supports both custom models and foundation models, including Google’s Gemini model family. It enables organizations to fine-tune models, run large-scale inference, orchestrate agentic workflows, and integrate AI into production systems with strong security, governance, and observability controls.

The platform includes tools for AutoML, custom training with TensorFlow and PyTorch, managed pipelines, feature stores, vector search, and online and batch prediction. For generative AI use cases, Vertex AI provides APIs for text, image, code, multimodal generation, embeddings, and agent-based systems, including support for Model Context Protocol (MCP) integrations.

Built for enterprise environments, Vertex AI integrates deeply with Google Cloud services such as BigQuery, Cloud Storage, IAM, and VPC, enabling secure data access and compliance. It is widely used across industries like finance, healthcare, retail, and science for applications ranging from recommendation systems and forecasting to autonomous research agents and AI-powered products.