KlausHaeuptle

104 posts

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KlausHaeuptle

KlausHaeuptle

@KHaeuptle

Author, Software Engineer, Community Lead. https://t.co/TargvxtNSR Newsletter: https://t.co/EXzWkeVZMA…

Katılım Ekim 2019
26 Takip Edilen135 Takipçiler
Ethan Mollick
Ethan Mollick@emollick·
As I see more and more data, it is becoming clear the first productivity gains that will be widely realized from AI is in programming. Look at this from Amazon: 4,500 developer years saved on a project!
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Andy Jassy@ajassy

One of the most tedious (but critical tasks) for software development teams is updating foundational software. It’s not new feature work, and it doesn’t feel like you’re moving the experience forward. As a result, this work is either dreaded or put off for more exciting work—or both. Amazon Q, our GenAI assistant for software development, is trying to bring some light to this heaviness. We have a new code transformation capability, and here’s what we found when we integrated it into our internal systems and applied it to our needed Java upgrades: - The average time to upgrade an application to Java 17 plummeted from what’s typically 50 developer-days to just a few hours. We estimate this has saved us the equivalent of 4,500 developer-years of work (yes, that number is crazy but, real). - In under six months, we've been able to upgrade more than 50% of our production Java systems to modernized Java versions at a fraction of the usual time and effort. And, our developers shipped 79% of the auto-generated code reviews without any additional changes. - The benefits go beyond how much effort we’ve saved developers. The upgrades have enhanced security and reduced infrastructure costs, providing an estimated $260M in annualized efficiency gains. This is a great example of how large-scale enterprises can gain significant efficiencies in foundational software hygiene work by leveraging Amazon Q. It’s been a game changer for us, and not only do our Amazon teams plan to use this transformation capability more, but our Q team plans to add more transformations for developers to leverage.

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Allie K. Miller
Allie K. Miller@alliekmiller·
🚀 Amazon's AI assistant, Amazon Q, has saved the company $260M and 4,500 developer-years of work by drastically cutting down software upgrade times. Average app upgrade to Java 17 used to take 50 dev days. Now takes just a few hours. @ajassy confirmed that devs shipped 79% of AI-generated code reviews without changes. More here: finance.yahoo.com/news/amazon-ce…
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Matt Johansen
Matt Johansen@mattjay·
Andy Jassy sharing major payoffs of genAI initiatives in their engineering efforts. Security engineers at Amazon in the comments agreeing from first hand experience. Major productivity boost? Or 4,500 dev years worth of layoffs on the horizon?
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sarah guo
sarah guo@saranormous·
Andy Jassy, CEO of Amazon:
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Andy Jassy
Andy Jassy@ajassy·
One of the most tedious (but critical tasks) for software development teams is updating foundational software. It’s not new feature work, and it doesn’t feel like you’re moving the experience forward. As a result, this work is either dreaded or put off for more exciting work—or both. Amazon Q, our GenAI assistant for software development, is trying to bring some light to this heaviness. We have a new code transformation capability, and here’s what we found when we integrated it into our internal systems and applied it to our needed Java upgrades: - The average time to upgrade an application to Java 17 plummeted from what’s typically 50 developer-days to just a few hours. We estimate this has saved us the equivalent of 4,500 developer-years of work (yes, that number is crazy but, real). - In under six months, we've been able to upgrade more than 50% of our production Java systems to modernized Java versions at a fraction of the usual time and effort. And, our developers shipped 79% of the auto-generated code reviews without any additional changes. - The benefits go beyond how much effort we’ve saved developers. The upgrades have enhanced security and reduced infrastructure costs, providing an estimated $260M in annualized efficiency gains. This is a great example of how large-scale enterprises can gain significant efficiencies in foundational software hygiene work by leveraging Amazon Q. It’s been a game changer for us, and not only do our Amazon teams plan to use this transformation capability more, but our Q team plans to add more transformations for developers to leverage.
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KlausHaeuptle
KlausHaeuptle@KHaeuptle·
Writing readable, maintainable and testable code matters! I just got my physical copy of the German Translation of Clean SAPUI5. We wrote the book to help developers utilize the concept of clean code in their SAPUI5 / JavaScript projects. rheinwerk-verlag.de/clean-sapui5-l…
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KlausHaeuptle
KlausHaeuptle@KHaeuptle·
With the recent newsletter edition on the importance of Developer Experience the Software Engineering Ecosystem newsletter jumped to more than 1000 subscribers. Thanks to everyone who contributed to reaching this milestone by spreading the word..
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KlausHaeuptle
KlausHaeuptle@KHaeuptle·
Unveiling the secrets of effective decision-making strategies in #OpenSource Risk Management and Sustainability for building systems that can last decades! Dive into our enlightening interview with Sebastian Wolf from SAP's Open Source Program Office. open.substack.com/pub/ecosystem4…
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KlausHaeuptle
KlausHaeuptle@KHaeuptle·
Jörg-Michael Grassau the master mind behind ABAP cleaner, just wrote the best blog so far about the tool which can help you to automate many of the Clean ABAP rules! The blog also contains the links to the recent sessions about the tool. blog.sap-press.com/how-to-clean-y… #SAP #CleanABAP
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