Centizen, Inc.’s Post

Are AI assisted developer tools already changing Software Engineering jobs? At work, we’ve adopted GitHub Copilot over the past few months. Feedback has been broadly positive, with one engineer likening it to having a keen junior developer always on hand. However, its impact hasn’t been transformational. On personal projects, I’ve been using Cursor for the last month and found it to be a significant improvement over Copilot in predicting my next steps. For someone like me, a leader who hasn’t coded full-time in nearly a decade, having an IDE that remembers all the basic syntax I've forgotten is a game changer. While iteration is necessary, it accelerates the initial stages, especially when you’re a bit rusty. Over the weekend, I took Replit for a spin, and it was eye-opening. Replit goes beyond being an AI assistant in your IDE; it has an AI agent that can understand relatively sizable requirements, update your codebase, test, iterate on issues and push its changes to github. I had a simple football stats site built & deployed in 40 minutes and added a bunch more features throughout the evening. The pace was insane. That said, it wasn’t without challenges. The AI struggled with some features but it wasn't because of complexity. It was able to add caching and a refresh strategy but struggled adding a dark mode toggle. There were a few things like this where it was quicker for me to write it myself. The initial implementation was slow and poorly architected, but to its credit, once I explained why and outlined a better structure, it adapted quickly. This tool feels perfect for rapid prototyping, but I wouldn’t rely on it yet to create maintainable, production-ready code. A word of caution: Replit’s $25 subscription only includes $25 in AI usage credits, and I burned through $20 of this over the weekend. Sure, it’s still a fraction of the cost of a human developer but you still need to commit plenty of your own time guiding it. The market for AI developer tools is heating up with the rise of #agenticai. According to reports the global market for AI in software development is projected to grow at a compound annual rate of over 20% in the next few years. This is driven by the promise of faster cycles, reduced costs, and tools that increasingly mimic the collaborative experience of working with another developer. The pace of innovation in this space is impressive and is underpinned by the LLM models that power them. If the current trajectory holds, we may soon see agents capable of producing cost-effective and maintainable solutions. Until then, I’ll be sticking with Cursor but keeping an eye on how Replit and others evolve. And for anyone stressing about AI replacing them as software engineers - remember coding is just part of what we do. The experience gained supporting crappy code and working with clients who don't know what they need is hard to replicate with AI. Have you tried these tools? I’d love to hear your thoughts!

Favorite AI Tools of Developers and Tips For Using Them https://lnkd.in/gfTxqiYr Despite being a relative newcomer to the developer tools ecosystem, AI continues to have an increasingly significant impact on how developers are doing their jobs. According to a recent report by Gartner, 75% of enterprise software engineers will be using AI code assistants by 2028, a sizable jump from only 10% of those surveyed in 2023. Developer research firm SlashData recently published an even more bullish survey that revealed 71% of all developers are actively working with AI “in one way or another” and that “59% of developers use AI tools in their development workflows.” “I don’t think AI is going to replace software developers (yet), but I do think software developers that use AI might replace software developers that don’t.” – Shane Thomas, co-founder of Audiofeed While the growth and impact of AI on software development are undeniable, we wanted to get a real-world sense from developers on how they’re personally using AI development tools, so we spoke with a number of software engineers to find out — and also to get their feedback on the pros (and cons) of using AI development tools. Top AI tools: Pair Programming and Code Completion  The largest category of AI tools used by developers I spoke with fall into the AI pair programming and code completion categories, tools which can easily generate code snippets and serve as automated assistants for programmers. GitHub Copilot was mentioned by every developer I spoke with, and seems to be one of the most popular solutions for developers looking for an AI tool. “For me, GitHub Copilot is mainly about increasing my speed,” said Shane Thomas, a veteran software engineer and co-founder of Audiofeed. “[GitHub Copilot] is best when I already know what I want to write and it can just autocomplete those sections for me. It’s not often [completely] right, but it’s directionally correct. It gets me 80% of the way there and I can update the things I know are wrong.” Other developers had similar things to say about Copilot. “I use GitHub Copilot every day,” said Kristian Ranstrom, owner of Rainstorm Technologies and an experienced developer. “It’s built into Visual Studio and Visual Studio Code (and other IDEs) so using it is extremely easy… you can [also] use the GitHub Copilot Chat window to ask it to do something. For example, ‘How do I handle resizing images in an API in C#?’ or ‘Write test cases for this class.’” Bekah Hawrot Weigel, a technical AI advocate at OpenSauced, said that “GitHub Copilot and ChatGPT are the obvious choices for improving efficiency and getting unstuck”, and added that using AI tools “…helps us find the right answers more quickly and connect with the people who have those answers faster.” Thomas also relies on Cursor IDE, which he sees as an enhancement on top of VS Code. “I use this to chat with sections of my code or my code base when I’m not exactly sure wha...

All Hands AI Open Sources OpenHands CodeAct 2.1: A New Software Development Agent to Solve Over 50% of Real Github Issues in SWE-Bench AI Agents in Software Development The use of AI agents in software development has rapidly increased, aiming to boost productivity and automate complex tasks. However, many AI agents struggle to effectively tackle real-world software development challenges, particularly when resolving GitHub issues. These agents often require significant oversight from developers, which undermines their intended purpose. To overcome this, we need an AI solution that adapts to the fast-paced and intricate nature of software engineering. Introducing OpenHands CodeAct 2.1 OpenHands CodeAct 2.1 is a groundbreaking software development agent that has successfully resolved over 50% of real GitHub issues in SWE-Bench, a standard benchmark for evaluating AI tools in software engineering. This agent achieves a 53% resolution rate on SWE-Bench and a 41.7% success rate on SWE-Bench Lite, making it a powerful tool for developers. Key Benefits of OpenHands CodeAct 2.1 Autonomous Issue Resolution: It solves real GitHub issues on actual projects without human intervention. Open Source: Developers can use, modify, and enhance the tool freely, promoting collaboration. High Performance: It significantly reduces the time developers spend on mundane issue resolution. Major Updates Driving Performance The improvements in OpenHands CodeAct 2.1 stem from three key updates: Claude-3.5 Model: Enhanced natural language understanding for better interpretation of developer issues. Function Calling: Increased precision in task execution by calling specific code pieces accurately. Improved Directory Traversal: Smarter navigation through directories to avoid repetitive tasks, enhancing efficiency. Significance of These Improvements A 53% resolution rate means that more than half of the benchmark issues are solved autonomously, demonstrating the tool’s impact on software engineering workflows. This efficiency allows developers to focus on more complex challenges instead of getting bogged down by routine tasks. The open-source nature encourages global collaboration, further enhancing its capabilities. Conclusion OpenHands CodeAct 2.1 represents a significant advancement in AI-driven software development, moving towards fully autonomous coding assistants. Its ability to solve over 50% of real GitHub issues shows its practicality for daily use. The open-source model fosters community involvement and continuous improvement. Whether you want to run OpenHands locally or integrate it through GitHub actions, it offers flexibility for all developers. Stay Connected Check out the details and GitHub for more information. Follow us on Twitter, join our Telegram Channel, and... https://lnkd.in/dbc6EF-6 https://lnkd.in/dbr3VkCn

10 Powerful AI Tools to Supercharge Your Development Workflow AI is rapidly transforming the software development landscape, empowering developers to be more efficient and productive. Here are 10 incredible AI tools that can take your coding game to the next level: 1- Tabnine (Code Completion): This AI assistant predicts your next line of code, suggesting snippets, functions, and even entire classes, saving you time and keystrokes across various languages (especially JavaScript and Python). 2- Amazon CodeWhisperer (Code Generation & Security): Working directly in your IDE, CodeWhisperer generates code based on your existing code and comments. It also scans for vulnerabilities, identifying potential security issues and suggesting fixes. 3- Stepsize (AI-powered Debugging): Struggling with bugs? Stepsize uses AI to pinpoint and fix bugs in your code, analyzing new and existing code, reviews, and even production issues. It also helps identify the root cause, saving you hours of debugging frustration. 4- Cody (Advanced Code Assistant): This comprehensive AI assistant provides code completion, refactoring suggestions, and real-time error detection. It integrates seamlessly with popular IDEs, making it a one-stop shop for enhanced development. 5- Codium (Test-Writing Assistant): Let Codium take the burden off writing unit tests. Analyze your code, and Codium intelligently suggests relevant tests, reducing manual effort and ensuring better code coverage. 6- Copilot (Code Generation by GitHub & OpenAI): This powerful tool by GitHub and OpenAI leverages natural language to generate code, translate languages, and write different kinds of creative content based on your instructions. (Limited availability at the moment) 7- Kite (Context-aware Code Completion): Kite analyzes your code and surrounding context to offer highly relevant code completions, documentation, and API references, keeping you focused and in the flow state. 8- DeepCode (Static Code Analysis): DeepCode leverages AI for static code analysis, identifying potential security vulnerabilities, code smells, and bugs. It integrates with popular CI/CD pipelines for automated code reviews. 9- Mullvad VPN (Privacy-focused Development): While not strictly an AI tool, a secure development environment is crucial. Mullvad VPN offers a great option for developers who prioritize privacy and data security. 10- GitHub Copilot Labs (Experimenting with the Future): Stay on the cutting edge with GitHub Copilot Labs, where you can experiment with new features and functionalities being developed for the popular Copilot tool. These are just a few of the many AI tools available to developers today. What are your favorite AI tools that boost your development workflow? Share your experience in the comments! #AI #DeveloperTools #Programming #MachineLearning

𝗧𝗵𝗲 𝗘𝘃𝗼𝗹𝘂𝘁𝗶𝗼𝗻 𝗼𝗳 𝗔𝗜-𝗣𝗼𝘄𝗲𝗿𝗲𝗱 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁: 𝗔𝘀𝘀𝗲𝘀𝘀𝗶𝗻𝗴 𝘁𝗵𝗲 𝗚𝗶𝘁𝗛𝘂𝗯 𝗖𝗼𝗽𝗶𝗹𝗼𝘁’𝘀 𝗙𝗿𝗲𝗲 𝗧𝗶𝗲𝗿 GitHub's move to offer Copilot for free to Visual Studio Code users marks a pivotal moment in software development, significantly enhancing access to advanced tools and potentially transforming workflows for developers of all skill levels. The free tier of GitHub now offers features previously exclusive to paid subscribers. The core offerings include: 𝗖𝗼𝗿𝗲 𝗙𝗲𝗮𝘁𝘂𝗿𝗲𝘀 1. Intelligent Code Generation: Copilot automates repetitive coding tasks, boosting developer productivity. 2. Comprehensive Language Integration: It supports popular languages like Python, JavaScript, and Java, ensuring versatility across environments. 3. Contextual Intelligence: Copilot provides tailored suggestions by understanding project structures. 4. Tier-Specific Parameters: The free edition offers essential features, while advanced options like team collaboration remain exclusive to paid plans. 𝗜𝗺𝗽𝗮𝗰𝘁 𝗼𝗻 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗲𝗿 𝗣𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝘃𝗶𝘁𝘆 Feedback indicates significant improvements in efficiency, enabling developers to tackle higher-level problems and design issues. However, concerns remain about its impact on skill development and potential over-reliance on automation. 𝗜𝗻𝗱𝘂𝘀𝘁𝗿𝘆 𝗜𝗺𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻𝘀 GitHub’s strategic move could catalyze several industry-wide transformations: 1. Learning Acceleration: AI tools could help new developers acquire skills faster by shortening the learning curve. 2. Empowering Small Teams: Advanced tools could enable smaller teams to compete with larger organizations, fostering innovation. 3. Role Evolution: Routine tasks may be automated, allowing developers to focus on strategic and creative projects. 4. Standardization: AI-suggested code could improve quality and consistency across the industry. 𝗙𝘂𝘁𝘂𝗿𝗲 𝗢𝘂𝘁𝗹𝗼𝗼𝗸 The long-term impact of GitHub’s free tier remains uncertain. Its success will depend on achieving a balance between utilizing AI for efficiency and preserving the key skills that define developers. This initiative underscores the need for thoughtful integration of AI into the development process to maximize benefits while mitigating potential challenges. The evolution of software development continues, with GitHub Copilot serving as a compelling example. As the industry advances, it must carefully assess both opportunities and challenges to shape the future direction of software development practices. AI is already transforming the way we write code, and this is just the beginning. What do you think? Are tools like Copilot the future of software development, or should we be cautious about what we might lose in the process? Share your thoughts in the comments! #AI #GitHubCopilot #SoftwareDevelopment #Innovation #Coding #Technology #AIProgramming #DeveloperTools

Exploring AI-Enhanced Development Tools -The New Frontier in Programming    GitHub, the worlds largest source code host, has introduced the GitHub Copilot Workspace, enhancing its existing tools by allowing programmers to manage their projects entirely in natural language. This launch is part of a broader trend in AI-powered developer tools that aim to increase productivity and reduce errors.     Key players in this field include:  Codeium: Known for its advanced autocomplete feature, Codeium tailors code suggestions to fit individual project needs.  Replit GhostWriter: This feature in Replit's online editor helps complete code in real-time.  Amazon CodeWhisperer: It offers real-time coding suggestions using a vast database of code, focusing on speed and security.  CodePal & Cody by Sourcegraph: These tools range from generating code from text (CodePal) to automated code reviews (Cody).  Tabnine & MutableAI: Tabnine provides cross-platform code completions, while MutableAI transforms designs into functional websites.  AskCodi & AI2sql: AskCodi assists with coding by providing insights and auto-tests, whereas AI2sql converts natural language into SQL.    These AI tools are redefining standards in programming environments.     Are you utilizing any AI tools in your development projects? Let’s explore how AI is reshaping our workflows and capabilities.    At Audley Consulting Group, we specialize in developing AI solutions that augment productivity, efficiency, and quality across various operational facets. Link to read more: https://lnkd.in/eqdAxSNi   #AI #programming #GitHub #developer_tools #technology #innovation #codeium #tabnine #mutableai #askcodi #codewhisperer #gov #govai 

🚀 Low-Code/No-Code: Is It a Threat or an Opportunity for Developers? 🤔💻 In recent years, Low-Code/No-Code platforms have been revolutionizing the way apps, websites, and workflows are built. 🌍 These platforms allow non-developers to create solutions without writing a single line of code — sounds like a game-changer, right? But here’s the burning question: Does this spell trouble for developers, or is it a golden opportunity? 💥 The Threat: 1. Job Displacement – With drag-and-drop functionality, even non-technical people can create websites, apps, and automations with minimal coding knowledge. This might reduce the demand for developers in certain industries. 🤖 2. Automation Overload – As businesses automate more tasks, entry-level development roles might shrink, leading to less demand for traditional coding jobs. 🚫 🔥 The Opportunity: On the other hand, Low-Code/No-Code isn’t here to replace developers — it’s here to empower us. Here's how: 1. Faster Development – Developers can speed up delivery by using these platforms for the less complex, time-consuming parts of projects. This means faster prototypes, quicker testing, and more time to focus on innovative coding! ⚡ 2. Broader Skill Set – As a developer, knowing how to leverage Low-Code/No-Code platforms can set you apart in the job market. Upskilling in these tools gives you a competitive edge. 🔑 3. Collaboration – Low-Code/No-Code tools help bridge the gap between developers and business stakeholders. Now, you can collaborate more effectively by letting business teams handle the less technical aspects while you focus on the core logic. 🧩 4. Innovation – These tools enable developers to experiment and build creative prototypes in a fraction of the time it would traditionally take. 🚀 Let your imagination run wild! 💡 How Developers Can Benefit: Automate Repetitive Tasks – Focus on more challenging, high-value work while automating basic workflows. 🛠️ Build MVPs Quickly – Get your ideas into the market faster with rapid prototyping. 🏃♂️💨 Improve Efficiency – Optimize development processes and improve team productivity. 📈 Expand Your Service Offering – As Low-Code/No-Code platforms continue to grow, developers can add new services for clients, like automation consulting, workflow integrations, or customized Low-Code solutions. 🌟 🌟 The Verdict? It’s not a matter of Threat vs. Opportunity, but rather how developers can adapt and leverage these tools to stay ahead. So, developers, it’s time to embrace the future and explore how you can benefit from these game-changing platforms. 🙌 What are your thoughts on Low-Code/No-Code? 💬 Let’s discuss below!👇 #LowCodeNoCode #TechInnovation #FutureOfWork #DeveloperCommunity #NoCodeRevolution #WebDevelopment #Automation #TechTrends #SoftwareDevelopment #CodingLife #DeveloperOpportunities #SkillsOfTheFuture #GrowthMindset

15+ Artificial Intelligence AI Tools For Developers (2024) https://lnkd.in/dQd-Fbtp GitHub Copilot GitHub Copilot is a cutting-edge AI-powered coding assistant that helps developers produce high-quality code more efficiently. It uses OpenAI’s Codex language model to offer valuable suggestions, complete lines of code, write comments, and aid in debugging and security checks. Amazon CodeWhisperer Amazon’s CodeWhisperer is a machine-learning-driven code generator that provides real-time coding recommendations within various IDEs. It enhances code quality by suggesting snippets to full functions and automating repetitive tasks, thus improving efficiency and security for developers. Notion AI The AI assistant Notion offers valuable support in various writing-related tasks, including creativity, revision, and summary. It accelerates writing tasks such as emails, job descriptions, and blog posts, providing efficient and customizable AI-generated content. Stepsize AI Stepsize AI is a collaboration tool designed to optimize team productivity by integrating with platforms like Slack, Jira, and GitHub. It offers a centralized summary of activities, instant answers to queries, and robust data privacy controls for streamlined updates and communication. Mintlify Mintlify is a time-saving tool that auto-generates code documentation directly in your favorite code editor. It creates well-structured, context-aware descriptions for functions, excelling in generating precise documentation for complex functions and increasing efficiency and accuracy for developers and teams. Pieces for Developers Pieces for Developers is an AI-powered snippet manager that streamlines code production, enrichment, and distribution across the development process. It produces code tailored to specific repositories, extracts code from screenshots, and adds inline comments, saving time and effort for developers. LangChain The LangChain framework simplifies working with language models for niche uses like document analysis, chatbots, and code analysis. It equips programmers with the tools to efficiently utilize language models and create cutting-edge software for various purposes. YOU You.com offers an AI-powered search engine and suite of applications with useful AI-powered capabilities, including AI writing assistance, AI-generated photos, code mode AI chat, and study mode chat for personalized search experiences and creative support. AgentGPT AgentGPT facilitates the development and distribution of user-created autonomous AI agents to achieve specific objectives. It provides a potent instrument for building individualized AI agents tailored to various purposes. Jam Jam.dev offers a user-friendly platform for enhanced bug reporting and integrates AI debugging helpers to evaluate bug reports, find correlations, and offer solutions. It simplifies bug reporting and analysis, enhancing development processes acros...

Headstart, an AI-native software development company, accelerates software development timelines by up to 100x, leveraging Claude's AI capabilities to transform the industry. 🚀 Unprecedented Speed: Headstart slashes development times from months to weeks, achieving 10-100x faster results. 💻 AI-Generated Code: 90-97% of client code is written by Claude, allowing engineers to focus on high-level problem solving. 🏥 Enterprise Security: Headstart ensures data privacy for clients in sensitive industries like healthcare and finance while using Claude. 📈 Game-Changing Efficiency: By quoting clients 10x faster timelines, Headstart disrupts traditional billing with a flat-fee model. 🤖 AI-Native Development: Headstart is a company that uses AI to automate the majority of coding tasks, enabling companies to implement AI effectively in their development processes. 🌍 Looking Ahead: Founder Nicole Hedley envisions a future where AI handles coding while humans focus on creativity and innovation. #AI #SoftwareDevelopment #Claude 🎯 Why Claude?: Its intuitive interface and ability to handle large codebases make it the default tool for Headstart. 🛠️ Revolutionizing Expectations: Headstart consistently delivers complex projects in a fraction of the time, giving clients a competitive edge. 🌍 Pushing Boundaries: AI-native development shifts the focus from manual coding to strategic thinking, revolutionizing software engineering. ♻️ Repost if you enjoyed this post, and follow me César Beltrán Miralles for more curated content about generative AI! Headstart Cuts Software Development Time by 100x with Claude AI https://lnkd.in/gYzMhc27