Lucas Dickey’s Post

2023: Software engineers doing all the work. 2024: Generative AI takes over!? Software engineers used to do all the hard work, like writing tons of code and testing it. Now, with generative AI, the AI can write code or even create designs by itself. 92% of engineers now use tools like GitHub Copilot. That’s a huge jump from just 56% last year! And it’s not just the big companies using these tools. Even smaller firms are spending more on AI tech as they grow. Old tools like Google and Stack Overflow? They’re getting left behind. AI is taking their place, especially when information is hard to find. What to do now? Start by integrating these tools into your workflow, upskill your team, and invest in AI-driven solutions. The tech world is evolving fast, and adapting now will keep you ahead of the curve. Want to start building secure and scalable IT solutions then… DM me ‘Innovate’ and let’s connect. #innovation #itsolutions

80% of Software Engineers Could Lose Their Jobs Due to AI? Just came across an eye-opening report from Gartner that says over 80% of software engineers will need to learn new skills, like prompt engineering and retrieval-augmented generation (RAG), to stay relevant in this new AI-driven world. While some might feel anxious about AI taking over, the truth is AI isn’t here to replace us. Instead, it’s transforming the way we work. The tools we use, like GitHub Copilot and Anthropic’s Claude, are already making a huge difference – boosting productivity and even generating code. But here’s the catch – those who don’t adapt might be left behind. This is a wake-up call for all of us to upskill and embrace the change. I’m curious, what do you all think? How do you see AI shaping the future of software development? Are you already working with AI tools? Would love to hear your thoughts! 👇 #AI #SoftwareEngineers #Upskilling #FutureOfTech #SoftwareDevelopment

The hard part about software NEVER was writing code. Yet “AI soothsayers” keep talking about the death of software engineering. There are THREE vested interests here: 1) The AI Investors & Founders They want to succeed. And they are willing to peddle anything for that. 2) The Soothsaying “CEO” Usually a CEO unrelated to AI, but eyes shine bright when seeing the possibility of “cutting costs” by laying off technologists. They talk about how “writing code” will no longer be a tough task. (Well, it never was) 3) The Bad Programmer The wolf in sheep’s clothing. If you’ve been in software engineering long enough, you’d know that more than 80% of them are really bad at their jobs. It’s quite a relief to them when AI makes them supposedly as productive as the rest of the 20%. Yet, the truth is: 1) AI is a tool. An abstraction. It’s like an even higher level DSL. 2) Writing code, laughably, has never been the toughest part of programming. Engineers have always creatively automated boilerplate, snippets, etc. 3) If there is software in whatever form, the people creating it will be called “software engineers” regardless of what tools they use. 4) People who focus on how AI can make yesterday’s problems easier, rather than tomorrow’s problems viable, are not visionaries. — Follow me to elevate your software engineering career in startups. #software #softwareengineering #artificialintelligence #startups #innovation #criticalthinking #growth

Hey LinkedIn fam, Welcome to Day 3 of my series, "Scratch to Stack: My Journey to Tech Sis-dom!" Today? Oh, nothing major—just casually continuing my deep dive into full-stack development like a pro-in-training. No big deal. 😏 I’ve also sprinkled in some AI sessions for good measure (because, why not?), and I’m keeping my DevOps class in check too. Oh, and did I mention? I’ve been invited to collaborate on a new project! 🎉 Yes, *exciting*—I’m buzzing about it too! That’s all the action for now. Stay tuned for more updates. If you have any tips, tricks, or just feel like chat about all things code, hit me up in the DMs or send me an email at [email protected]. Always happy to connect Best, Dein #fullstack #techsis #student #tech #coding #computerscience #AI #DevOps #newproject #selftaught

CTOs - Here's the biggest trap I've seen fast-growing tech startups fall into—one that's now entirely preventable. In the rush to grow the business and add new features, engineering teams cut corners while shipping multiple pull requests daily. While this drives product velocity, it accumulates as technical debt, gradually slowing down your product. Users have zero tolerance for sluggish performance, which ultimately damages both the company's and CTO's reputation. The challenge compounds because performance bottlenecks spread throughout your expanding codebase, with each new code change potentially introducing more slowdown. It's impractical to constantly dedicate resources to chase these issues. Most CTOs resign themselves to planning "an optimization pass" only after it becomes critical—but by then, it's too late for your users. It does not have to be this way. Automated performance optimization is now possible with ai performance engineers like Codeflash Instead of letting slow code pile up over a period of time, Codeflash can continuously optimize your logic, algorithms, library use and just plain mistakes to keep your application at top-speed. By consistently optimizing code, companies such as Pydantic and Langflow achieve exceptional speed, ultimately delighting their users #python #performance #aiagents

💻💻Software engineering is evolving rapidly before our eyes🖥🖥 For decades, we've known software as a set of rules implemented through code. But the future is taking a new direction. Today’s software merges code, data, and models. This shift requires a fresh approach to how we build and think about software. AI isn’t replacing software engineering; it’s transforming it. I don’t want to be left behind as the AI/ML revolution changes everything. That’s why I’ve been adapting, learning, and trying new approaches. Here are three strategies I'm currently following: 1. **Mastering how to control computers remains crucial**: In 2024, this means learning how to write code with the assistance of AI. 2. **Building scalable software solutions is still a top skill**: Knowing how to move from "it works on my machine" to "a million people use this" sets you apart from others. 3. **Objective and critical thinking is invaluable**: Don’t rely on AI to understand how software works. Learn the core principles yourself. What more can we do to stay competitive in the next 10 years?

I opened my company's bank account before I could open a personal one. I have been building a lot of cool projects ever since I was 14, but now that I am 17 and trying to build my first company, nType, which provides AI solutions to businesses, it feels kind of weird facing all of these non-coding related things. In the morning, I am trying to sell my services to companies, and at night, I code. I am the businessperson, the engineer, the salesperson—everything. But the weird thing is that I don't get stressed that much. I face many ups and downs, whether it's a disagreement with a client or an irritating bug. I always think, if I completed the entire 12th grade syllabus in a week before board exams, which was so stressful, I can definitely build a billion dollar company :) In terms of progress, I have started automating a lot of stuff. I am the only person who codes in my company, so it becomes difficult even working with three companies. So, I think automating machine learning development will increase my bandwidth. #buildinpublic #startup

Over 25% of Google’s new code is now generated by AI. A $2T company 💼 is relying on machines to build a quarter of its software. From 2022 to 2024 🚀, software engineering has rapidly evolved. Jensen Huang 🧠 suggests coding could be replaced by simple English commands in the near future. At this pace, "CODING" as we know it might not exist in the next decade. Software development is no longer the same competitive barrier it once was. It's time to rethink 🤔 what’s next for the tech world ! 💡 #GOOGLE #AIRevolution #FutureOfTech #SoftwareEngineering #Innovation #coding #AI #Technology

So, coding is dead now? Really? I’ve been seeing a lot of buzz on LinkedIn lately about how AI is replacing software engineers. Some even claim that soon anyone—grandmas included—will be launching SaaS products. Let’s be real: AI and the maturity of software engineering have made it easier than ever to spin up an MVP. Forms, buttons, and fancy effects? Sure, those are faster to build now. But here’s the thing—that was never the hard part of software engineering. AI won’t replace software engineers. What it will do is highlight just how essential skilled engineers are for building robust, scalable, and user-centered products that solve real problems. Good software engineering isn’t about code alone—it’s about thoughtful design, architecture, and understanding the needs of people. What do you think? Is AI really going to replace us, or will it make good engineers even more indispensable?

Looking Ahead: The Next 10 Years In the next ten years, how we do software engineering will probably change a lot. But the main problems we face – figuring out what customers want, building systems that can handle many users, making sure they work reliably, and keeping them safe – will still be the same. What will be different is how we solve these problems. AI tools will become a regular part of our work, just like using tools like Git and automatic testing are today. The best engineers will be those who can use both their own knowledge and what AI can do to create better software more quickly. This doesn't mean you need to become an AI expert. Instead, focus on learning how to use these tools effectively and knowing when they are the right choice and when you need to rely on your own judgment.