Joao-Pierre Ruth’s Post

Tackling the Legacy Code Dilemma What we heard a lot lately .... NoCode and AI are transforming the tech landscape at lightning speed. However, the legacy code problem looms large as non-developers dive into these powerful tools without fully understanding the underlying systems. (No offense - I have that problem too.) With only 0.3% of humanity coding, this gap can lead to significant risks in the future, such as maintenance problems and scaling issues. How do we solve this? Our Approach: Visualize & Simplify: Imagine a 3D visualization of your entire workflow, showing you what happens with your data in each step. This offers a clear understanding of processes, making it easier to identify workflow boundaries and address efficiency issues. Paired with a platform to not only visualize but adapt the workflows, you could replace legacy systems one step at a time. This reduces risk and alleviates the fear of touching core processes in a company, ensuring a smooth transition and preventing loss of control. By integrating visualization with NoCode, we are on our way for businesses to innovate confidently, bridging the gap between old and new. Could you agree to that or do you have a different oppinion?

🚀 Exciting Insights from Xebia's Latest GitHub Copilot Survey! Discover how GitHub Copilot is transforming software development! Developers are finding that this #AI tool significantly saves time on basic coding tasks and enhances job satisfaction. But what about code quality? Our survey reveals the real impact of Copilot on productivity and quality. Dive into our findings and see how developers balance these aspects. Read more: https://lnkd.in/gJ_dpuXi #GitHubCopilot #AI #SoftwareDevelopment #Xebia #TechInnovation

Indeed, AI code assistants are going to revolutionize software development by empowering developers, accelerating project timelines, and augmenting productivity. Now, let's move on to the trends and predictions for the future: 1. Hyper-Personalised Development Environments: AI-enabled IDEs will adapt to individual coding styles, offering suggestions of code snippets and structures based on historical developer decisions. This will significantly enhance productivity and decrease cognitive load 2. Natural Language Programming: Plain English coding will become the norm. Advanced AI models will be able to understand complex programming concepts expressed in natural language, enabling developers to describe functionality in plain English and have an AI generate code corresponding to that description. 3. AI-Driven Software Architecture: AI will help design scalable and Efficient system architectures help developers create more robust and maintainable systems. 4. Greater Adoption: AI tools will be integrated into more developers' workflows—like was the case with tools like GitHub Copilot that are in very wide use today. 5. Continual Improvement: As precision and capability continue to grow, AI code assistants themselves will improve over time, further increasing their usefulness to developers. The future for AI-assisted coding is very bright, with a huge potential to make software development accessible, efficient, and innovative in nature. What's your take on these trends?

Here are the nine reasons users and stakeholders have told us why they care about how much GenAI is in their codebase, i.e. GenAI Code Transparency. The most common reason: PE-backed companies, and companies who wish to take on later-stage investment or exit, expect to be diligenced on their GenAI code usage. It's just like they are diligenced on Open Source. And they want to stay ahead of any surprises.

In the Architecture & Technology team, we're taking a deep dive into GenAI with Project AI Impact 🚀 . Our goal? Discover how GenAI tools can boost software development productivity on a team basis. After examining over 30 teams, we’ve uncovered some fascinating findings. 🛠 Here’s how we did it 🛠: ⏩ Leveraged Plandek for automated insights into our engineering performance and productivity. ⏩ Conducted surveys to get a clearer picture of how teams are using GenAI and for which specific activities. ⏩ Applied a blend of analytics and human judgment to extract meaningful conclusions and learn valuable lessons. 💡Starting with an interesting finding💡: In software development teams, there are three activities that are especially considered important across multiple roles: 🔧 Learning new skills 🔧 Writing tests 🔧 Writing code 🎉 A huge thanks to Andreas Folkesson for his dedication and effort in making this project a success!  🎉 Super kudos to Jurijs M. and Tudor Nica; your efforts made this project possible.  🎉 Also, thanks to Will Lytle and Pranav Lakhotia from Plandek for their full support in onboarding more than 30 teams and helping us unlock the true value of Plandek. Keep an 👀 out for more insights!

Insightful study to be involved in, helping to answer the question everyone in the technology world is asking... What's the real impact of GenAI? 🤷♂️ Plandek insights were used to draw meaningful conclusions in this study, by measuring the impact of GenAI across 30 different teams. It raised some important conversations and uncovered fascinating results! We'll be sharing more on this interesting study in the coming weeks... 👀 #GenAI #SoftwareIntelligence #AI #Research #Insights

Next week, the Sonar Team is heading to MS Build 2024! Stop by Expert Meet-Up Spot FP36 where we will provide in-depth demo sessions on how our Clean Code solutions - SonarQube, SonarCloud, and SonarLint - help enhance code quality when using Gen-AI-assisted tools! On May 23, Tom Howlett, Head of Product Management will present a demo: "Produce AI-assisted quality code with speed and confidence"! Whether written by humans or generated by AI, it is imperative that code be checked for quality and security. In this demo, Tom will dive into the world of AI-assisted coding, showing how to produce quality code quickly and confidently with GitHub Copilot and Sonar, as well as practical advice to nurture a Clean Code culture. Full details here: https://lnkd.in/gi-HQs2a #CleanCode #MSBuild2024 #MicrosoftBuild24 #SonarQube #SonarLint #SonarCloud #genAI #AI #LLMs #Microsoft Zeynep Koch Harry Wang Manish Kapur

Over the last year, we've engaged in extensive discussions with developers, engineering leaders, and executives from organizations worth hundreds of billions of dollars about using GenAI in the SDLC.   A common theme emerged: the importance of GenAI Code Transparency – knowing how much code in a codebase originated from a GenAI tool.   In our latest blog post, we explore nine reasons why developers and organizations care about GenAI Code Transparency.    The top reason? Investor-backed companies expect to have to explain their use of GenAI in future technical due diligences—just like they do today for Open Source usage.   Read the full blog post to learn more about each reason and how GenAI Code Transparency can benefit your organization.   Read more here: https://lnkd.in/dyApKkiD

Great insights from Grove Ventures' 'Shift Happens 2024' report! While AI adoption in software development is rising, we haven’t hit the 'hockey stick' growth many expected (myself included). There's still room for tools to mature. My two cents: the challenges in building solid AI-driven tools (not just for SDLC) are (1) AI foundation models are still evolving and costly, (2) cloud GPU costs strain margins, and (3) integrating GenAI while ensuring trust and safety. Enjoy the read! https://lnkd.in/evjwvad9