#AI can make individual developers faster, but scaling a team requires more than giving everyone a coding agent. Gant Laborde and Brandon Mathis discuss why the next phase of AI powered development depends on building the right team structures, with people focused on product vision, system reliability, and long term architecture. The goal is not just producing more code. It is creating engineering systems that help teams move faster while still building software that can scale.

Countless AI communities and groups are being created lately, but this one genuinely caught my attention. Came across this initiative shared by Akhil Naidu, and the idea behind it felt interesting. The focus on practical AI adoption, engineering discussions, and learning from people who are actively building with AI felt valuable. As someone exploring and working with AI in software development, I think conversations like these add a different perspective, especially when many are still trying to make sense of AI through YouTube videos, blogs, and the constant stream of new tools appearing every week. I'm looking forward to joining the discussions and seeing how the community evolves. If you're interested in AI, software engineering, or figuring out how AI fits into real-world development, you might find it worth checking out. https://lnkd.in/gc3JM-AA

Shipping software has never been just about writing code. Someone still has to read it. Review it. Debug it. Extend it. Refactor it. Maintain it. That's why clean code matters even more in the AI era. The better your naming, architecture, and code organization, the better AI can understand your codebase and the more useful its suggestions become. AI is becoming an incredible coding partner. But it still can't replace engineering judgment. Clean code isn't old-fashioned. It's what makes AI-assisted development actually work. What's one clean code principle you never compromise on? #AI #SoftwareEngineering #CleanCode #Programming #Developer #Coding #SoftwareDevelopment #Tech #ArtificialIntelligence #CodeQuality #Architecture #Engineering #DevLife #ProgrammingTips

The best engineers aren't always the ones writing the most code. They're the ones solving the right problems. Productivity isn't measured by commits, pull requests, or hours logged. It's measured by the value you create, the complexity you eliminate, and the impact your work has on users and the business. As AI takes over repetitive coding tasks, engineering excellence will be defined less by output and more by judgment, architecture, collaboration, and decision-making. The future belongs to engineers who think beyond the code. #SoftwareEngineering #DeveloperProductivity #EngineeringLeadership #AIInTech #TechInnovation #Coding #DigitalTransformation #SoftwareDevelopment #EngineeringCulture #FutureOfWork

There was a time when software engineers built frameworks that empowered other developers to build faster, better, and more efficiently. Today, with the rise of AI, the focus has shifted. We're building AI agents that don't just accelerate development—they perform the work themselves. It makes me wonder: Have we simply evolved from building frameworks to building intelligent workers? Or are we slowly losing the habit of solving problems through deep engineering and brainstorming because AI now fills that gap? I'm genuinely curious about where this shift takes us. Is this the next natural evolution of software engineering, or does it risk diminishing the craftsmanship that once defined it? Thoughts..??

🤖 Coding isn’t disappearing — but the skills behind great software are changing In this Signals episode by devmio, Michael Dowden talks with Nir Kaufman about how AI is reshaping software development and why developers need more than technical expertise. ✨ clearer communication 🧠 stronger context management ⚙️ smarter prompt engineering 👉 Listen to “The End of Coding as We Know It”: https://lnkd.in/d2ZySEKX #webinale #AI #SoftwareDevelopment #PromptEngineering #DeveloperSkills

AI is transforming software development—but at what cost? We're proud to support the launch of Dark Code—a timely new book exploring one of the most important conversations in modern software engineering. Can we truly trust code that even experienced engineers struggle to fully understand? Dark Code: The Software Architect's Guide to Travelling at the Speed of AI examines the growing challenge of explainability in AI-assisted software development and explores why the future of engineering may depend less on generating code—and more on understanding it. Launching 1 July 2026, this thought-provoking book offers valuable insights for software architects, technology leaders, developers, and organisations navigating the AI era. As a PR agency, we're proud to support projects that spark meaningful conversations around innovation, technology, and the future of work. #ArtificialIntelligence #SoftwareEngineering #Leadership #DigitalTransformation #Innovation #Technology #ThoughtLeadership #AI #DarkCode

I'm genuinely amazed by how powerful Claude Code has become. It feels like having a team of invisible engineering teammates collaborating with you as you build an application. Vibe coding is quickly becoming a game-changer for software engineers. It enables faster prototyping, accelerates development, helps with debugging, and reduces the time spent on repetitive tasks—allowing developers to focus more on architecture, problem-solving, and delivering business value. That said, it's important to use AI responsibly. Advantages: ✅ Faster development and prototyping ✅ Better debugging and code suggestions ✅ Reduced repetitive coding tasks ✅ Increased productivity and faster learning Disadvantages: ⚠️ AI-generated code still requires careful review and testing. ⚠️ Overreliance on AI can weaken problem-solving and debugging skills over time. ⚠️ Security, performance, and maintainability should never be assumed without validation. ⚠️ Understanding the code remains more important than simply generating it. AI isn't replacing software engineers—it’s empowering those who know how to leverage it effectively. The engineers who combine strong fundamentals with AI-assisted development will likely have a significant advantage in the years ahead. What are your thoughts on vibe coding? Has it become part of your daily development workflow? #ClaudeCode #AI #ArtificialIntelligence #VibeCoding #SoftwareEngineering #SoftwareDeveloper #Programming #Coding #DeveloperTools #Productivity #FullStackDeveloper #WebDevelopment #Innovation #Tech #FutureOfWork

From Code Consumer to Code Creator AI has changed the way we build software but it hasn't changed the need for great engineers. The real competitive advantage is no longer writing more code. It's understanding problems, designing scalable solutions, collaborating effectively with AI and creating business value. The future belongs to professionals who don't just generate code—they create impact.

We are managing for a bottleneck that no longer exists. For the last decade, software engineering processes—Agile, heavy design docs, multi-week sprint planning—were built around one fundamental constraint: coding bandwidth was the most expensive part of the pipeline. That constraint is gone. As Fiona Fung highlighted in Anthropic's recent breakdown of AI-native engineering, AI code generation has completely shifted the bottleneck. Writing the code is now the cheap part. Throughput has skyrocketed. So what happens when the pipeline flows faster? The downstream systems choke. The new bottlenecks are verification, security review, and cross-functional alignment. If your engineering org is still spending hours in pre-planning meetings instead of prototyping directly in PRs, you aren't being rigorous. You are carrying forward legacy processes that quietly stopped working a year ago. The role of product and engineering leadership right now isn't just about deploying AI tools to write code faster. It’s about ruthlessly defragging the organization. It's about shifting verification left, flattening team structures, and explicitly giving your teams permission to kill processes that were designed for a pre-AI world. Don’t just scale your code generation. Scale your verification. #AI #EngineeringManagement #ProductManagement #PlatformEngineering #TechLeadership https://lnkd.in/gbUFKnWN