Artificial intelligence (genAI, LLM, vision agents, etc.) is no longer a futuristic dream - it's here, transforming industries with breathtaking speed and versatility. 🚀 From automating mundane tasks to generating complex code, AI is reshaping modern software development. But the question on everyone’s mind is buzzing louder than ever: Can AI replace seasoned software and test engineers? 🤔 Spoiler alert: it’s not as simple as you might think. We explain in our blog article (https://lnkd.in/eXUhEvhR) the reasons. Join the conversation! Leave your views in the comments. #ArtificialIntelligence #SoftwareDevelopment #TechTrends #Innovation #AI

AI in software engineering is often framed as a threat or a miracle cure. At Ximedes, we take a more practical and thoughtful approach. In a recent conversation, our CEO, Joris Portegies Zwart, shared how AI tools like Claude are already changing daily engineering work and why the real risk isn’t bad code, but rather too much code. When speed turns engineers into passive reviewers, creativity and ownership are the first things lost. We talk about how to use AI without letting it take over the craft, why engineers must stay in the driver’s seat, and why AI can’t replace ambition, intent, or the “why” behind good software. Read the full conversation here: https://lnkd.in/eGXRNtv7 #Ximedes #Fintech #SoftwareEngineering #AI

The compelling metaphor of 'code is clay' from Hacker News sparks a vital conversation about the future of software development and user experience. It suggests that our digital tools should not be rigid, static constructs, but rather adaptable, moldable entities that evolve alongside our needs. At IrisGo, this philosophy is at the core of our approach to personal AI. We believe that for AI to truly serve knowledge workers, it must move beyond predefined functionalities and become genuinely context-aware. This means an AI that observes and learns locally, understanding your unique preferences and workflows, and proactively shaping your digital environment to enhance your productivity. Our on-device AI empowers software to behave like clay, constantly being refined and reshaped by your interaction and context. It’s about building systems that don't just react to commands, but anticipate needs and seamlessly integrate into your personal operating rhythm. This ensures your AI assistant truly serves you, becoming an unobtrusive extension of your intellect rather than a generic tool. We invite you to consider: how much more productive could you be if your software genuinely adapted to you, rather than you constantly adapting to it? We are building that future, one where your AI understands you deeply. #PersonalAI #ContextAwareAI #AIProductivity

The Lesson:- When tech giants treat your obsession as a feature, specialization wins. ElevenLabs proved that in AI, the best product isn't always the biggest model—it's the most thoughtfully designed system. Voice quality obsession + developer experience + platform economics + data moats = a sustainable AI business that scales like software, not like compute. Building with voice AI? What design decision made the biggest impact for you? #VoiceAI #ElevenLabs #ProductDesign #AIStartups #DeveloperTools #PlatformStrategy #TechLeadership

Great insights on how AI is reshaping software engineering, from automation to intelligent decision-making across development teams. #CloudDestinations #AI #Software #Automation

Six hours. No code. One working AI system. A recent Forbes piece captured something many of us are starting to feel: the centre of gravity is shifting from “writing software” to “orchestrating systems”. What used to need a squad of engineers can now be prototyped by one person in a single flight – if they deeply understand the workflow and can translate it into clear steps an AI can execute. That doesn’t make engineering obsolete. It changes where the leverage is: • Less time wiring APIs and infrastructure. • More time designing workflows, data flows, and guardrails. • More focus on evaluation and iteration, not implementation. For data scientists and builders, the question is no longer “Can I code this?” but “Can I design a reliable system that compounds my expertise?” The real moat won’t be the model or the tool. It will be who owns the workflows, the feedback loops, and the courage to ship a v1 in six hours.

Google has released a comprehensive Prompt Engineering Guide focused on real-world AI applications. The guide covers: Industry-relevant use cases and examples Step-by-step strategies for effective prompt development Advanced prompting frameworks for developers, including Chain of Thought, ReAct, and Tree of Thought Best practices for creating more accurate, efficient, and reliable prompts This resource is especially valuable for professionals aiming to enhance the quality, speed, and consistency of their AI-driven workflows. #PromptEngineering #ArtificialIntelligence #GenerativeAI #AIWorkflows #AIProductivity

AI hasn’t changed how systems behave in production — it’s changed how fast I get there. In my day-to-day backend work, tools like Antigravity have become part of the development loop. Not to replace decision-making, but to reduce friction where it doesn’t add value. Boilerplate, query drafts, edge-case prompts — that’s where AI helps most. From using AI (and Antigravity in particular) in real development work, a few things stand out: • Antigravity is effective for quick context switching and first-pass solutions • It accelerates repetitive backend tasks without touching core architecture • Blind trust is risky; every suggestion still needs engineering judgment • The biggest win is reclaimed time for performance, reliability, and design AI tools don’t understand production consequences — developers do. Used intentionally, they make good engineers faster, not careless ones. Curious to hear—how are you integrating AI tools like Antigravity into your workflow? #backenddevelopment #softwareengineering #aiindev #antigravity #productivity

AI is becoming a powerful co-pilot in full-stack development, but knowing when to trust it and when to challenge it is what separates good code from great engineering. In Arjun V D's latest blog, he explores how developers can use AI effectively without giving up engineering judgment, from writing cleaner code to making better architectural decisions. If you’re using AI in your daily workflow and still want to think like an engineer, this one’s for you👉 Read the full blog: https://lnkd.in/gJYHreRe #FullStackDevelopment #AIinEngineering #SoftwareCraftsmanship #EngineeringJudgement #DeveloperExperience #CubetInsights #TechBlog

AI has become an everyday part of how we write code now. It helps us move faster, explore options quickly, and reduce a lot of repetitive effort. But speed alone doesn’t make better software.   While working on this piece at Cubet, I kept coming back to one question: are we becoming better engineers, or just faster coders?   In the blog, I’ve shared how I think about using AI in full-stack development without handing over responsibility for engineering decisions, and why human intuition remains a critical part of the stack.   Check out my full Blog: https://lnkd.in/gzmFxujq