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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,..

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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  

GPT-5.3-Codex is OpenAI’s advanced agentic coding model, designed to go beyond writing code and operate as a general-purpose collaborator on a computer. It builds on GPT-5.2-Codex by combining stronger coding performance with improved reasoning and professional knowledge, while running about 25% faster. The model is optimized for long-running tasks that involve research, tool use, and complex execution, and it performs at the top of industry benchmarks such as SWE-Bench Pro and Terminal-Bench.

Unlike earlier Codex models that focused primarily on code generation and review, GPT-5.3-Codex can reason, plan, and act across the full software lifecycle. It supports activities such as debugging, deploying, monitoring, writing product requirement documents, creating tests, and analyzing metrics. It can also autonomously build and iterate on complex applications and better interpret underspecified prompts, producing more complete and production-ready results by default.

A defining feature of GPT-5.3-Codex is its interactive, agentic workflow. Users can steer the model while it is working, receive progress updates, and adjust direction without losing context, making it feel more like a teammate than a batch automation tool. The model was even used internally to help debug its own training and deployment processes. GPT-5.3-Codex is available through paid ChatGPT plans in the Codex app, CLI, IDE extension, and web, with API access planned for the future.