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!
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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
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!
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This episode of DOS Won’t Hunt saw Matt Bishop, principal architect at Bitwarden; Artem Kroupenev, vice president of strategy at Augury; Matias Madou, Secure Code Warrior’s CTO and co-founder; and Joel Carusone, senior vice president of data and AI at NinjaOne, come together. They discussed the use of AI in software development, its benefits and risks, and how developers want AI to be implemented in the cycle.
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✨ Crash Course on GenAI for software development 13th June 2024 ✨ Check the attached post about the seminar, get inspired and register yourself for this fantastic event hosted by Sami Köykkä, Marko Taipale and Lasse Girs, Solita's iron-clad GenAI professionals. #solita #impactthatlasts #genai #softwaredevelopment
Crash Course on GenAI for software development
solita.fi
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🌟 Dive into the Future of Software Development! 🌟 The past 2 days, our strategy meeting, held amid the scenic whine mountains and castles of Bingen, ignited a dynamic discussion on the AI-software development nexus. 💻 From automated testing to intelligent algorithms, AI is reshaping our coding landscape, boosting efficiency and elevating quality. 🚀 Embracing AI means pioneering new innovations and architecting the future of software. We are prepared as we embrace AI as our ally, empowering us to break new ground and pioneer innovations. 🔮 Stay tuned as we harness AI's potential to revolutionize our projects! #AI #SoftwareDev #Innovation
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As #AI tools revolutionize coding, some wonder—are we leaning too heavily on automation? 🧐🤖 This thought-provoking article from InformationWeek explores benefits and risks for AI in software development. Watch the full interview featuring our SVP of Data and AI Joel Carusone here: https://bit.ly/41ilFKe
Have We Gone Too Far With AI in Software Development?
informationweek.com
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Exciting News from Anthropic! Anthropic has just released an incredible new feature for Claude, transforming it into more than just a task assistant. Claude can now write and debug code, simplifying the entire process for developers. In the video below, you’ll see how Claude builds a website and fixes bugs—done in just a few prompts! But this is just the beginning. Anthropic aims to enable end-to-end task completion in a single prompt in the near future. What are your thoughts on these groundbreaking features and their potential impact on the world and the future of software development? #AI #MachineLearning #SoftwareDevelopment #Claude #Anthropic #Automation #FutureOfTech #OpenAI #GenerativeAI
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"We only got 5 out of 30 tasks done in half the project time (6 weeks). And those aren't even the hard ones. Everything takes too long. We have to clean up to get anything done." "You want to fix code now? The project is already behind. Stay pragmatic!" *Deadline arrives* Tasks done: 10/30 Average time to change a label on a button: 3-4 weeks Productivity multiplier: somewhere around 0.05 "Ok, next quarter we have to plan better. 15 tasks only this time - much more realistic. NO time for cleanup so we REALLY stay on track" ---- ai generated image for good measure:
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At GitHub I spent the last 1.5 years successfully implementing generative AI features into production for both customers and internal teams. Yet, I've noticed that while industry expectations for GenAI are high, many ideas struggle to get anywhere beyond a proof of concept. I would like to connect with others who have attempted to build GenAI systems to discuss shared challenges. What obstacles have you faced in implementing GenAI effectively?