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ExternalSoftware Engineering
DEV Community

Most Engineers Use AI. Few Engineer With It.

Most software engineers I know use AI in some form now. Maybe it is for debugging, boilerplate, tests, docs, SQL queries, shell commands, or quick code reviews. Some use it daily. Some use it quietly. Even the skeptical ones have probably pasted a confusing stack trace into a chat window once. So I do not think the interesting question is: “Do engineers use AI?” The better question is: “Has AI changed how they engineer?” Because those are not the same thing. Using AI is easy. Engineering with AI

aiproductivitysoftwareengineering
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ExternalSoftware Engineering
DEV Community

Além da Ditação: Como Extrair Inteligência Real de Conversas a partir de Áudio em Segundos

No ecossistema de dados moderno, o áudio está em todo lugar. Gravamos ligações de suporte ao cliente, reuniões de vendas, sessões de brainstorming, notas de voz e podcasts. No entanto, para muitas empresas, esses milhares de horas de áudio continuam sendo um silo de dados invisível. Por anos, a solução técnica padrão foi simples: Speech-to-Text (STT). Você envia um arquivo de áudio para um engine, e ele cospe uma parede gigante de texto sem pontuação. Mas sejamos honestos: ninguém tem tempo para

aiwebdevpython
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ExternalSoftware Engineering
DEV Community

Chrome Put a 4GB AI Model on Your Computer: What Gemini Nano Means for Privacy

Originally published on MRTD.NET — fast, sourced news on crypto security, cyber & SEO. If you run a recent version of Google Chrome on a desktop, there is a decent chance your browser has quietly downloaded a ~4GB artificial-intelligence model in the background. It is called Gemini Nano, and it is the engine behind Chrome's new built-in AI features. The download is real — Snopes verified it — and it is worth understanding what it is, why it is mostly good, and where the legitimate concern lies.

securityprivacytechnology
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ExternalCybersecurity
Microsoft Security Blog

Crypto Clipper uses Tor and worm-like propagation for persistence and control

Microsoft Threat Intelligence analyzed a cryptocurrency clipper campaign that combines clipboard theft, wallet replacement, Tor-based communications, and worm-like propagation. Beyond stealing cryptocurrency transactions, the malware establishes persistent access and enables follow-on activity through a lightweight backdoor capability. The post Crypto Clipper uses Tor and worm-like propagation for persistence and control appeared first on Microsoft Security Blog.

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ExternalSoftware Engineering
DEV Community

Setting Up the Codehabits MCP Server in Cursor (5 Minutes)

The Codehabits MCP server gives Cursor six tools that read from .codehabits/ in your repo — convention lookup, code validation, domain knowledge, reviewer suggestions, and a feedback loop for updating conventions. Setup takes about five minutes if you already ran codehabits enable. Node.js 20+ .codehabits/meta.json in your repo (from npx @codehabits/cli enable) Cursor with MCP support enabled If you don't have intelligence files yet, run enable first — see the quickstart. From your repository ro

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ExternalSoftware Engineering
DEV Community

The Dilemma of the Modern Programmer: Adapting to a Changing Job Market

The market hasn't gotten easier since I first wrote a version of this. It's gotten stranger — and faster. Becoming, or staying, a software engineer in 2026 can feel daunting, but it's not all doom and gloom. The engineers who are winning right now are the ones who adapted to how the work actually gets done today, not how it got done in 2021. I stay in perpetual job-hunting mode — not because I'm looking to leave anything, but because it keeps my skills sharp and lets me give the veterans I mento

careeraiprogramming
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ExternalSoftware Engineering
DEV Community

Building a Path-First State Engine for TypeScript Apps

I got tired of application state being split across a dozen tiny systems. One store for settings. One object for UI state. One event bus for updates. One validation layer for important values. One undo stack. One pile of helper functions for waiting until something is ready. One separate system for debugging what changed. That works for a while. Then the app gets larger, and state stops being “just values.” It becomes application infrastructure. That is the problem I built OmniTurbo around. Omni

typescriptjavascriptopensource
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