Alan Felice’s Post

👉Ask ChatGPT: Give the detail attributes of the C# Roselyn compiler? - Part 1 of 2 ChatGPT🤖 The C# Roslyn compiler, also known as the👉 .NET Compiler Platform, is a set of 👉open-source compilers and code analysis APIs for C# and VB.NET. It provides a wealth of features and attributes that make it a powerful tool for developers. Here are the detailed attributes of the C# Roslyn compiler: Key Attributes of the C# Roslyn Compiler Open Source: Roslyn is fully open-source and hosted on 👉GitHub, which allows developers to contribute to its development and use it freely in their projects. Rich API for Code Analysis and Refactoring: Provides APIs that enable deep analysis of C# code, supporting 👉advanced code refactoring, diagnostics, and code generation tools. 👉Compiler as a Service: Exposes the compiler functionality as a service, allowing developers to compile code, perform syntax analysis, and semantic analysis programmatically. 👉Syntax Tree API: Allows access to and manipulation of the syntax tree of a C# program, enabling detailed code analysis and transformations at the syntax level. 👉Semantic Model API: Provides detailed information about the meaning of the code (types, symbols, bindings), which is essential for advanced code analysis and refactoring tools. Incremental Compilation: Supports incremental compilation, which compiles only the parts of the code that have changed, resulting in faster compilation times during development. Workspaces API: Manages collections of documents and projects, providing services for editing, compiling, and analyzing the code within these projects. Diagnostic API: Generates and reports diagnostics (errors, warnings, and suggestions) that can be used for developing custom code analysis tools and IDE features. 👉Code Fix and Refactoring API: Facilitates the creation of code fixes and refactoring tools, enabling automated code transformations and improvements directly within the development environment. --continued--

Will AI take away jobs? It's been 2 years since the launch of ChatGPT. While many have quickly adopted AI and GenAI in their professional lives, this question has been in the minds of a significant workforce, especially software engineers and managers. There are already visible impacts around us, as has been the case with all tech evolutions. Wrote my perspective on this in this blog. Feels good to be back to writing after some time. https://lnkd.in/dsHUfpQa #ArtificialIntelligence #Programming

"The best programmers are lazy programmers." I first heard this in my freshman year of college, and it’s stuck with me ever since. But with the rise of Generative AI, I’m starting to rethink that philosophy. As "lazy programmers," we’ve grown used to grabbing the latest frameworks and publicly available packages to quickly add functionality to our applications. Despite being a great asset, this habit might actually be making us worse programmers—we should be putting in a bit more effort. Here’s why: In my experience, it’s cleaner and easier to maintain code generated by AI from scratch rather than code built around existing packages. This approach avoids versioning issues, eliminates the need for custom modifications, and offers much more flexibility. The challenge is that you need to create a clear specification upfront, and you’ll have to deal with fixing defects in AI-generated code at first. Once that specification is in place, you gain extreme extensibility. When your application is defined in plain language, AI will be able to generate code for any framework, language, or platform—whether it’s iOS, Android, or even something new like wearables or smart glasses. A well-written specification is what will truly allow us to be "lazy" in the long run. By investing a little more time upfront, I believe the lazy programmer in all of us will reap significant benefits down the road. I’d love to hear your thoughts! Rajesh Kandaswamy

"ChatGPT has an extremely broad range of success when it comes to producing functional code—with a success rate ranging from anywhere as poor as 0.66 percent and as good as 89 percent—depending on the difficulty of the task, the programming language, and a number of other factors." A range of 0.66% to 89%. This is why experienced, not novice, developers need to work with the tool, understand its limitations and "teach" it so that it has all the information it needs to approach its potential of being a useful, consistent, productivity tool.

Intelligent Engineering with AI for .Net June 19-20, 9-5 EST, remote “Improperly used AI tools can be one of the fastest ways to create a tangle of technical debt. However, those that use AI tools well, develop better and faster (55% according to some studies) than those who don’t” Julias Shaw, CTO, LeanDog This 2 day course will teach your engineers the most modern practices leveraging AI and improving their productivity.  We will also cover the most modern best practices including Test Driven Development, Continuous Integration, Pairing, Code Refactoring, and best practices on how to be effective in a distributed work environment... all improved by using AI! Is it possible to have zero defects? Yes, and this course will share techniques to get you on that path. This course covers Agile Engineering practices like TDD, BDD, Pairing Techniques, and so much more. This hands-on interactive curriculum has been very well received. Artificial Intelligence Topics Covered: Test Driven Development - When working with coding assistants like GitHub Copilot - When working with LLMs such as ChatGPT Refactoring - Using AI to identify code smells Zero Defect Code - Protecting yourself from AI mistakes - Getting AI to test its own code This industry is moving FAST (for example, OpenAI released a new ChatGPT model on Monday May 13th) so we update the specifics of coding assistants and LLMs used frequently. If you are interested in guidance on a specific tool let us know and we can look at incorporating it into your team’s training. If you are interested in a private course contact us!  If you need coaching and/or staffing we would love to talk too!!  For more details and to register go to: https://lnkd.in/e2XhQvvM

I'm using ChatGPT to help me learn CSS. I haven't seen much about Chat's roll as a mentor, but it is vital is closely tied to the nature of software (as I wrote in https://lnkd.in/evFxRQDq. Programming is speaking in a language that is a common ground between one who has a goal and an automaton. Today's AI assists have broadened the language, but it also requires the translation to be vetted by the intermediary of programming languages that the explainer (formerly known as the programmer) and the agent (computer) have a shared understanding of. CSS is an interesting language and takes a while to master. While it may seem arcane, it is well suited to conversation about presentation. CSS's expressive power it rapidly improving. But how do I say that I want to set the background of a row which contains a checkbox for drafts and to set the background color to green. I asked Chat (after telling it I want modern CSS) and it gave me tr:has(> td > .draft-input:checked) { background-color: var(--draft-color);} What is important is that I now know the language and can say it in native CSS. It's a lot faster for me to learn from Chat. This is not because it is intelligent but rather programming languages are about expression and once I understand the concept I can say what I want more effectively than using plain language. It gives me an argot that allows me to have an informed way to express my ideas. Another way of saying this is that the solution to a problem is asking the right question. I can now say what I want directly.

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🚀 New JetBrains Releases: A Leap in AI and IDE Technology! In the fast-paced world of programming, having powerful and intelligent tools is essential for developers. JetBrains has just released its 2024 versions, offering an upgraded AI assistant and new features in IDEs that bring a fresh experience to programmers. 🌟 New Features in JetBrains AI Assistant 🔹 Smarter Code Completion: JetBrains’ advanced AI model provides more accurate and faster code suggestions. This is particularly helpful for developers working with multiple languages. 🔹 Automatic Error Fixing: The new assistant automatically detects and resolves common coding errors, a real lifesaver when you’re racing against time! ⏱️ 🔹 More Advanced Solutions for Code Issues: The assistant can now offer precise recommendations for complex code problems, helping to tackle challenging issues faster. ⚙️ JetBrains IDE Updates 🔸 Performance and Loading Speed Optimization: With improved internal architecture, JetBrains IDEs now load large projects faster. 🔸 Support for New Technologies: The 2024 versions support new tech, like Python 3.12 and Java 21, keeping you up-to-date with the latest advancements. 🔸 New Team Collaboration Tools: Enhanced features for team coding allow simultaneous editing, a game-changer for big projects! 🤖 AI and the Future of Developers The use of AI in JetBrains tools helps us focus more on creativity and solving complex problems. When errors are automatically fixed, we have more time for meaningful tasks. 🌈 Whether you’re a longtime JetBrains user or just starting, be sure to check out the new versions. 💡 Source: https://blog.jetbrains.com

> If you as the developer do not understand the code, do not understand how you got to where you are, do not understand how to solve the problem yourself. Copying and pasting code from a LLM, and being spoon fed the answer, is not going to make you a better programmer. Its going to make you reliant on the robot, and you will never be able to do anything that the robot cant already do. Not to mention his earlier point - when relying on AI systems like #Copilot, you often get spoon fed answers that aren't actually accurate, helpful, complete, or optimized. So you may make the mistake of thinking you're taking the correct action, when really that's one of the worst moves you can make. I'm not arriving at the conclusion that you *shouldn't* use AI. However, use AI judiciously when programming, and take the time to be informed. Similarly to how you shouldn't ever just copy and paste output from #ChatGPT when content writing, you shouldn't do the same with code. Use it as a base to brainstorm, to go out and research, to unblock yourself when stumped - but don't rely on it. It will be to your detriment. https://lnkd.in/gGKX483T #AI #LLM #programming #devcommunity #developers #coding #github #microsoft #deeplearning