Stack Overflow

Developers deserve better! Even with the assistance of GenAI-powered coding tools, devs are still struggling to find answers to their questions without interrupting their workflows or wasting time with repetitive tasks 🔍 So how can organizations and managers meet these challenges and create a better work environment for their engineering teams? Get our recommendations in our 2024 #Developer Survey insights deep dive: https://lnkd.in/ebfFxXad

"It's great to have knowledge, but if you can't find it, it's hard to use." 🎯 We couldn't have said it better ourselves! Our Chief Technology Officer Jody Bailey spoke at #MSBuild about how we're partnering with Elastic on our search capabilities for Stack Overflow for Teams in order to empower developers to find the solutions they need. Watch the full talk here: https://lnkd.in/gkJ4bmhR

🎙️On our latest podcast episode, we sit down with Avthar Sewrathan, AI Lead at Timescale, about adapting developers’ favorite database management system, Postgres, to support a range of new technologies involved in the GenAI ecosystem, especially vector databases. Listen here: https://lnkd.in/e8K2QbTw

JavaScript, Python and SQL are all highly-desired and admired programming languages in our 2024 #Developer Survey, but Rust continues to be the most-admired programming language with an 83% score this year. Read more for a deeper dive on this year’s findings: https://lnkd.in/eU8ZtMjb

New language models get released every day (Gemini-1.5, Gemma, Claude 3, potentially GPT-5 etc. etc.), but one component of LLMs has remained constant over the last few years—the decoder-only transformer architecture. Why should we care? Research on LLMs moves fast. Shockingly, however, the architecture used by most modern LLMs is pretty similar to that of the original GPT model. We just make the model much larger, modify it slightly, and use a more extensive training (and alignment) process. For this reason, the decoder-only transformer architecture is one of the most fundamental/important ideas in AI research, so investing into understanding it deeply is a wise idea. This week, Cameron R. Wolfe, Phd walks us through why the decoder-only transformer architecture is one of the most fundamental ideas in AI research. To learn more: https://lnkd.in/ejaKBfnz

On today’s episode, the podcast team chats with a listener, Geshan Manandhar, who has been working in the world of software engineering for two decades. He started programming in a small village in Kathmandu during the days of dial-up. Since then he’s worked across three continents and today is a senior software engineer at Simply Wall Street. He gives his advice on how developers can change with the times and what it’s like to move into the era of serverless containers. To listen to the full conversation: https://lnkd.in/eJ42DgwE

There’s no arguing that we’re in the midst of an AI boom. New tools, capabilities, and skill sets are emerging, and a massive upskilling wave is underway for both individuals and organizations. It’s easy to get swept up in the enthusiasm around AI right now—positive and negative. AI coding tools can be huge productivity boosters for seasoned programmers who understand what they’re getting and how to evaluate it. They’re also an excellent source of support for novice programmers or those picking up a new language. But they require expert guidance to perform complex programming exercises and have been shown to introduce coding errors and security flaws when not managed carefully. We know from our most recent Developer Survey that only 43% of developers polled say that they trust the accuracy of AI tools. In this article, we’ll delve into the advantages and drawbacks of AI code generation tools, explain why a knowledge community is essential for successfully incorporating AI into your technical workflows, and unpack how AI coding tools combined with a knowledge community can unlock new levels of developer productivity. https://lnkd.in/eqyKNyt8

Thank you to WeAreDevelopers for the opportunity to share Stack Overflow's vision of becoming the Knowledge As A Service engine for the AI stack - the most trusted and accurate knowledge store of technology information that brings together Humans & AI to ensure developers and technologists get their answers to their questions wherever they are in their workflow - in GenAI tools, ChatOps tools or their IDEs. Full video here: https://lnkd.in/emzVUj4F

On today’s episode, the podcast team chats with Ryan Dahl, creator of Node.js and Deno. Ryan explains why he feels the first version of Deno has reached certain limits and what he and his team are doing with Deno 2.0 to scale up the module system and ensure it's a great tool for the modern web. To listen to the full discussion: https://lnkd.in/e4zE9FY3

In collaboration with The National DevOps Conference and Awards, Jody Bailey, CTO at Stack Overflow, shares his view on Generative AI and AI tools with DevOps Online UK. Generative AI has moved beyond the early adopter phase and its hype cycle moment, so questions about its staying power have now been replaced with discussion of how technologists and organizations can and should best harness its efficacy and power. One of the benefits of GenAI tools most frequently touted by advocates is increased productivity and efficiency. However, recent data suggests that how enterprises measure productivity is often murky at best. Despite this, AI tools are here to stay, so it is in the best interest of technologists and companies to understand which tools are being used the most and how AI impacts the overall developer experience. To read more: https://lnkd.in/eEsFfRkW