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@laura_garcia shared a post, 5 months, 1 week ago
Software Developer, RELIANOID

🚗🔒 Automotive Cybersecurity: Connected Cars, Connected Risks

Modern vehicles are no longer just machines — they’re connected devices storing data, running AI-driven assistants, and linked to vast supply chains. But with innovation comes new threats: from remote car hacking to ransomware attacks targeting manufacturing lines. Recent incidents — like the cybera..

Blog_Automotive Cybersecurity_relianoid
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@laura_garcia shared a post, 5 months, 1 week ago
Software Developer, RELIANOID

Huge thanks to Design Tech Solutions for publishing an article about RELIANOID! 📰 🤩

They explore how the RELIANOID Load Balancer enhances maritime cybersecurity, helping secure connected vessels, ports, and critical infrastructure. Read the full article here: https://www.relianoid.com/about-us/relianoid-related-articles/ #MaritimeCybersecurity#CyberSecurity#ConnectedShipping#LoadBa..

design tech solutions Article
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@anjali shared a link, 5 months, 1 week ago
Customer Marketing Manager, Last9

7 Observability Solutions for Full-Fidelity Telemetry

A quick guide to how seven leading observability tools support full-fidelity telemetry and the architectural choices behind them.

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@varbear shared a link, 5 months, 1 week ago
FAUN.dev()

We are replacing OOP with something worse

Object-oriented programming didn’t die - it evolved. Now it lives in the guts of infrastructure. Services talk through strict interfaces, crossing process and network lines like pros. Classes and objects? They're nowOpenAPI schemas,Docker containers, andKubernetes clusters- same old encapsulation ga.. read more  

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@varbear shared a link, 5 months, 1 week ago
FAUN.dev()

Why is Zig so Cool?

Zig bringscross-compilationandC interoperabilityto the forefront - no extra setup, no toolchain fuss. It builds across architectures, links with C code like it was born to, and skips headers entirely. Its real flex?Compile-time execution, sharperror handling, and azero-fat runtime. All wrapped in a .. read more  

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@varbear shared a link, 5 months, 1 week ago
FAUN.dev()

How the classic anime 'Ghost in the Shell' predicted the future of cybersecurity 30 years ago

“Ghost in the Shell” turned 30 this week. Still hits hard. Back in 1989, it dropped cyberpunk bombs that would take the real world decades to catch up with: government-grade AI hackers, behavior-based intrusion detection, malware tailored for humans, and remote code attribution that vanishes into th.. read more  

How the classic anime 'Ghost in the Shell' predicted the future of cybersecurity 30 years ago
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@varbear shared a link, 5 months, 1 week ago
FAUN.dev()

Programming Languages in the Age of AI Agents

GitHub Copilot and friends tend to shine in languages with rich static types - think Rust or Scala. Why? The compiler does the heavy lifting. It flags mistakes fast, keeps structure tight, and gives the AI sharper signals to riff on. But drop that agent into a sprawling legacy repo, and cracks show... read more  

Programming Languages in the Age of AI Agents
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@varbear shared a link, 5 months, 1 week ago
FAUN.dev()

The (lazy) Git UI You Didn't Know You Need

Lazygit is a snappy terminal Git UI that’s picking up steam - and for good reason. It streamlines common tasks like staging, rebasing, and patching without dragging you through clunky menus. The interface sticks close to native Git commands but adds just enough structure to reduce context switches a.. read more  

The (lazy) Git UI You Didn't Know You Need
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@varbear shared a link, 5 months, 1 week ago
FAUN.dev()

Your URL Is Your State

Modern frontend apps love to complicate state. But they keep forgetting the URL - shareable, dependency-free, and built for the job. This piece breaks down how a well-structured URL can capture UI state, track history, and make bookmarking effortless. NolocalStorage. No cookies. No bloated global st.. read more  

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@varbear shared a link, 5 months, 1 week ago
FAUN.dev()

How to Benchmark Python Code?

pytest-benchmarknow plugs straight intoCodSpeedfor automatic performance runs in CI - flamegraphs, metrics, and history included. Just toss a decorator on your test and it turns into a benchmark. Want to measure a slice of code more precisely? Use fixtures to zoom in... read more  

How to Benchmark Python Code?
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.