How engineering teams use AI in software development: agentic coding, RAG, MCP and spec-driven development, plus what to look for when hiring AI engineers who can build with these tools.
The Model Context Protocol (MCP) is an open standard created by Anthropic that allows AI agents to connect directly to external tools and execute actions on them. This isn’t about the AI simply “reading” information: with MCP, the agent can create tickets, navigate interfaces, write code, open pull requests, and more. Think of it as…
Artificial intelligence (AI) is knocking technology out of the park, especially regarding machine learning (ML).
Duration: 1h 05m | On demand Ruby on Rails has powered some of the world’s most successful startups and continues to be one of the most productive frameworks for building scalable web applications. In this webinar, Luis Payan], Senior Software Engineer at BEON.tech, breaks down how Ruby on Rails works in practice, step by step,…
Every team building with LLMs hits the same fork in the road eventually: should we use RAG, fine-tune the model, or build an agent? The three options are frequently discussed as if they’re interchangeable, but they solve fundamentally different problems. Picking the wrong one doesn’t just add cost, it creates architectural debt that’s painful to…
AI tools have become a standard part of how software gets built. Code assistants, RAG pipelines, LLM-powered features—they’re everywhere. And as teams integrate AI into software engineering workflows, a quiet problem has been building: most teams aren’t treating AI-assisted development with the same security rigor they’d apply to everything else. A thread on r/devsecops put…
The question most developers are quietly asking isn’t “will AI replace me?” It’s something more practical: what do I need to know to stay valuable as AI in engineering reshapes my role? That’s the right question. And the answer isn’t “learn to use Copilot.” It’s significantly broader than that. According to PwC’s research on GenAI…
Most developers aren’t losing to AI. They’re losing to developers who’ve figured out how to use it well. That’s the real split happening in engineering teams right now. Not “humans vs. AI” — but engineers who’ve integrated AI into their daily routines in a deliberate, disciplined way, and engineers who still treat it as an…
Generative AI is no longer a “nice-to-have” for engineering teams. It’s quickly becoming part of the default toolchain—alongside your IDE, CI/CD, and observability stack. The reason is simple: when used well, generative AI for developers reduces friction across the software development lifecycle and helps teams ship faster without requiring a linear increase in headcount. Adoption…
For many executives, the phrase “vibe coding” lands somewhere between tech slang and Silicon Valley humor. It sounds informal, almost unserious — but the reality behind it is anything but. Coined by AI researcher Andrej Karpathy, vibe coding describes a shift in how software is built: instead of writing code line-by-line, engineers describe intent in…
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