Why investing in junior engineers is key to future success

“The New Engineering Hybrid — Hardware Brains & Software Hands.” > Ten years ago, hardware engineers barely coded. Today, the best ones write Python for testing, C++ for controls, and train AI models on their own data. The future belongs to hybrid engineers — people who can design, code, and ship. The question: are companies ready to hire them? 💬 “Do you think ‘hybrid engineers’ will replace specialists in the next 5 years?” #Engineering #AI #Automation #iHire #Hiring

“The New Engineering Hybrid — Hardware Brains & Software Hands.” > Ten years ago, hardware engineers barely coded. Today, the best ones write Python for testing, C++ for controls, and train AI models on their own data. The future belongs to hybrid engineers — people who can design, code, and ship. The question: are companies ready to hire them? 💬 “Do you think ‘hybrid engineers’ will replace specialists in the next 5 years?” #Hiring #Engineering #AI #Automation #iHire

Software Engineering is not Computer Science! Most companies still treat software engineers like they’re computer scientists — testing syntax, memorization, and theory. But software engineering isn’t about proofs. It’s about systems. It’s architecture, feedback loops, and measurable velocity. It’s the discipline of building code that works, scales, and improves with every iteration. In this short video, I explain why confusing software engineering with computer science is one of the biggest bottlenecks in the modern tech industry — and how the AI-First engineering model redefines what it means to “build software.” #SoftwareEngineering #AIFirst #Velocity #EngineeringLeadership #LinkedInLearning

Great insight from Synopsys Inc CEO Sassine Ghazi on the rise of AI and how its reshaping the field of engineering.

I asked the CEO of Synopsys Inc about the future of AI and software engineering. Here is what Sassine Ghazi said: 1. Optimize the whole stack Don’t just code. Engineer the whole stack. Understand how silicon, software, systems, and AI work interdependently. Your level of expertise will pay dividends when others hit their limits. 2. AI cuts toil, not engineers AI is already designing chips, testing code, and writing documentation. As AI advances, the demand for complex systems grows faster than the talent pool. By 2030, the tech market will face a shortage of over 1 𝗺𝗶𝗹𝗹𝗶𝗼𝗻 𝗲𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝘀. 3. Go deep in one domain, not wide in ten Most students chase new frameworks instead of mastering one field deeply. Depth creates insight, and insight creates innovation. The best engineers can even explain the physics behind their code. The future belongs to those who understand deeper, not code faster. ♻️ Repost to help others understand the future of AI and engineering.

⚠️ Stop trying to hire "10x engineers." That entire concept is broken. It celebrates the "lone genius"—the brilliant coder who also happens to be a knowledge-hoarding, team-blocking bottleneck. The math has changed. 1 engineer writing code 10x faster = a 10x gain. 1 engineer who unblocks 5 teammates (making them 2x better) = a 10x gain. In the AI era, the first skill is being commoditized. The second one is priceless. This is the "Force Multiplier." This is the engineer who understands that their job isn't just to write code, but to increase the velocity of the entire team. Their "hard skills" aren't just algorithms. They are: Mastering the (ego-free) Pull Request Writing documentation that prevents future meetings Translating technical debt into business risk These are the most valuable, real-world skills in 2025. We wrote the playbook on how to find, hire, and build them. The full article is in the first comment. #TechTalent #EngineeringLeadership #FutureOfWork #TeamCulture #TechX

We’re not watching the death of software engineering; we’re witnessing its evolution. Those who survive today’s shift won’t just adapt to AI; they’ll redefine what it means to be an engineer. Because in the end, engineers build, the tools just change.

Excited to share insights from the OpenInfra (Gerrit) Summit Europe 2025! At Qualcomm, my session on SRE/DevOps Engineering delved into key aspects: - **Scaling Code Review for 15,000+ Engineers:** - Utilizing Gerrit to support extensive engineering teams, facilitating seamless CI/CD integration and handling petabyte-scale data effectively. - **Performance Tuning:** - Enhanced performance by transitioning to Java 21, adopting ZGC for JVM to reduce GC pause times (<0.2 ms), and optimizing memory usage for large-scale deployments, addressing JVM crashes. - **Storage & Ops Innovations:** - Improved service efficiency through Run Deck automation, mitigating NFS bottlenecks, and enhancing user experience by preventing primary abuse. - **AI-Powered Code Reviews:** - Integration of QGenie, Qualcomm's AI platform, automated code review feedback, processing over 200,000 feedback requests across 600 repositories. Utilizing large language models for enhanced reviews in various programming languages. - **Zero-Downtime Upgrades:** - Seamless upgrades of Gerrit platforms (3.9 → 3.10) achieved through multi-primary setups and robust testing frameworks, ensuring zero downtime. - **Challenges & Future Roadmap:** - Future focus on cache management, replication stability, containerizing primaries, and scaling Kubernetes replicas globally. 🔗 Watch the full session [here](https://lnkd.in/ghwRGsTP). #Gerrit #DevOps #SRE #AI #OpenInfra #Qualcomm #CodeReview #Engineering

Is AI going to take software engineering jobs? Or is it too dumb to do so? There are people posting extremes of these two scenarios. Though one thing is for sure that it's changing the software dev landscape in real-time. So rather than dismissing it or losing your temper over it isn't going to help. The pragmatic thing is to embrace, understand and go deeper into it everyday. #ktalks