Based in the Holy Land, Tabnine claims to be the originator of the AI coding assistant category. The company has now announced an expanded partnership and integration within the Atlassian platform ...

Tabnine tables AI platform integrations at Atlassian Team ’24

TEL AVIV, Israel, May 01, 2024 (GLOBE NEWSWIRE) — Tabnine, the originators of the AI coding assistant category, today announced an expanded partnership and integration within the Atlassian platform to build and maintain applications faster and with higher quality through AI.Unveiled at the ...

Tabnine and Atlassian Announce New AI Platform Integrations at Team ’24

The integrations, along with Tabnine&#x27;s AI coding assistant, will be available across Jira, Confluence, Bitbucket, and more later this year.

Tabnine and Atlassian reveal new generative AI tools for developers | ZDNET

Tabnine has competitors in GitHub Copilot and Amazon CodeWhisperer. But Weiss asserts that the company affords more control and personalization than rival systems, for example enabling customers to deploy its tools either on-premises or via a virtual private cloud.

Code-generating AI platform Tabnine nabs $25M investment | TechCrunch

That’s why AI is a really important and hot topic for us as we try to find more ways to bring innovation to our clients at a faster pace. Tabnine has boosted developer productivity for CI&amp;T: The company’s developers accept 90% of the tool’s single-line coding suggestions, resulting in ...

Tabnine is an AI assistant that speeds up delivery and keeps your ...

On the surface, the price appears to be almost the same ($20 per Tabnine Enterprise user, $19 per Copilot Business user). However, Copilot Business is only available to companies using GitHub Enterprise, which charges $210 per seat per year. In effect, that’s a barrier for enterprise companies ...

Tabnine Enterprise vs. GitHub Copilot Business • Tabnine Blog

I saw deep TabNine and want to use it as my company-backend but I can&#x27;t get it working even after spending the last 5 hours on it. I installed it…

r/emacs on Reddit: Use TabNine as Company Backend

I use Copilot for its multi-line code generation. It&#x27;s vastly superior. (Sorry Tabnine). Gotta give credit to Tabnine for kicking off this space -- they had a multi-year headstart on Copilot and it was pretty cool when it first launched, but it just doesn&#x27;t come close to Copilot.

Next-generation AI models | Hacker News

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FAQs | Tabnine

TabNine is the all-language autocompleter. It uses machine learning to provide responsive, reliable, and relevant suggestions. company-tabnine provides TabNine completion backend for company-mode. It takes care of TabNine binaries, so installation is easy.

GitHub - TommyX12/company-tabnine: A company-mode backend for ...

Tabnine

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AI-assisted coding is intended to help you as a developer be more productive, write code faster, make fewer mistakes, and have to do less context switching between other windows and your IDE. But is AI-assisted coding a silver bullet, snake oil, or something in between? In this article, we’ll look at the benefits as well as the potential downsides of using AI-assisted coding. We’ll also show a brief demo of using the AI-assisted coding solution to help us write some code in JavaScript and React. Tabnine What is AI-Assisted Coding and How Does It Work? AI-assisted coding is fueled by a machine learning model that is trained on other code. The best of these models are trained on billions of lines of code from respectable open-source projects around the world. Through this training, the model “learns” what characters and lines of code often come after one another. Then, as you write your code, it provides auto-suggest tab completions for you, directly in your IDE. As an extremely simple example, if you type in your IDE, the autocomplete would provide something like to finish your statement. import React from ‘react’; But AI-assisted coding goes much further than that; it also learns from the code write. The model constantly examines how you write your code and what patterns you typically follow. You can also train a more sophisticated model on your team’s code repos so that it better understands how your company writes code, which helps you be more consistent as a team. you What Are the Benefits? So, why would you opt to use an AI-powered coding assistant? Perhaps you’d rather rely on your own brain and a less fancy auto-suggest feature. For starters, AI-assisted coding keeps you in your IDE, reducing the context switching to other windows. If the autocomplete can provide you with the right syntax, you no longer have to do a quick Google search to remember how to use an API that you’re a bit rusty on. Less context switching leads to higher productivity. These machine learning models can also prompt you to write better code, as the code that they’re trained on often follows best practices and well-known design patterns. These nudges can be a teaching opportunity to help make you a better developer. What Are the Potential Downsides? Now, why would you want to use AI-assisted coding? not The biggest concern is privacy. If the machine learning model is being trained not just on public code but also on the code you write, then that means your code is potentially being shared with others who also use the same machine learning model. So, before using an AI-assisted coding solution, you should always look into the product’s privacy statement to understand if or how the product collects or shares data. The second concern is how well the model is trained. As mentioned before, most models are trained on billions of lines of code. But, what if those code repos are no good? You know the old saying: “garbage in, garbage out.” If the model is trained on poor code, then the suggestions you receive will be equally poor. Demo Time So, how helpful is AI-assisted coding in practice? To find out, I did a test drive with Tabnine, a popular solution that supports over 30 programming languages and 21 IDEs. The , for example, has nearly three million downloads. VS Code extension Installing the extension is as simple as clicking the Install button, waiting a few minutes for the model to be initialized, and then restarting VS Code on your machine. Tabnine has a featured prominently on their website which states that the model only runs locally on your machine and that your data is not shared. The cool thing about this setup is that, though your data is not shared with anyone else, the model is still being trained (locally) on your code, so the suggestions get better as you use it. privacy statement Once I had Tabnine installed and ready to go, I began my coding. For this demo, I decided to write a very simple login form in JavaScript and React. The form includes inputs for the username and password as well as a submit button. This UI is simple enough and is something just about every frontend engineer ends up building at some point. Creating the Structure of the Login Form Below is a short screen recording of me writing the JSX for the login form: You’ll notice that some of the suggestions were helpful, and some were not. The import statement worked flawlessly, and the suggestion for the component name to match the filename was helpful. LoginForm When setting up the boilerplate code for the function component and the return statement, I didn’t receive very many helpful suggestions. I then created the two input elements, and that’s where the magic started to happen. After typing , the rest of that line was suggested for me. Knowing that I had a label element for the username and that I was then creating an input element, the AI assistant gave me most of the code for the text input. Afterward, I added the attribute myself. <label id The same thing happened for the password input, which makes sense because a username input is commonly followed by a password input. But this time for the input, the AI assistant included an attribute for me. It’s learning! id Finally, I added the attribute to link the label to the input for each set of elements. As usual, the autocomplete struggled for me on the first usage for the username, but then when I added it for the password, the suggestion was right there. Magic! htmlFor Making the Form Interactive Now that I had the JSX in place, I needed to write the rest of the JavaScript to add the event handlers for the form’s submit event and the two inputs’ change events. Let’s take a look at how that went: You’ll notice a similar pattern in this video. Initially, the suggestions weren’t very helpful. However, as I wrote more code, the suggestions improved as the model picked up on what I was doing. When creating the function, I needed to supply the Event object myself. But after I typed , the model knew I wanted to call . Then, when I needed to add this event handler to the form’s method, the model knew exactly what I wanted to do. handleSubmit e e.pre e.preventDefault(); onSubmit When creating the two change handling functions, I had to create most of the setup for the username using the hook myself. But when I followed the same pattern again for the password, the AI assistant was right by my side and ready with the code I needed. useState This trend seems to be consistent: Do something once on your own, and the model is silently observing and learning. Do that same thing a second time, and the model is ready to help! Conclusion AI-assisted coding was an interesting experience. I’ve only spent a few hours playing around with Tabnine so far, and the value seems tangible. Once you get used to working with the auto-suggestions, I can imagine your productivity skyrocketing. The can certainly attest to that. experience of this engineering team at Cisco The real power seems to lie in automating the tedium of writing the same patterns of code over and over. Why not let an AI assistant help with that? AI-assisted coding solutions are becoming more mainstream, and I think that they’re here to stay. Privacy concerns are real, so be wise in choosing a solution that has a level of telemetry you’re comfortable with. Regardless of your stance, I think any developer who is serious about their productivity should at least give AI-assisted coding solutions a try.

AI-Assisted Coding with Tabnine

CodeComplete CodeComplete is an AI coding assistant by the search engine . Similar to GitHub’s Copilot, you can input a comment on what you need and which language the code should be written in and get the result instantly. However, in contrast to Copilot and most other Code Completion tools, CodeComplete works independently of your coding environment and lets you paste snippets into whatever environment you like most. I like having it always open on my second screen when coding. It works great and has been a true time saver. You.com https://you.com/search?q=code+complete GitHub Copilot GitHub Copilot is a tool that most of us likely know about. Available as an extension for many popular editors, just like with CodeComplete, you can input a comment of what code you’d like to have, and Copilot will create it for you. However, you have to use it as an extension on one of the supported editors. It is still astonishing to see how great Copilot works; it is also an absolute time-saver. https://github.com/features/copilot/ Cogram Cogram, a Berlin-based Startup, is a code generation tool for data scientists and Python programmers using SQL queries and Jupyter Notebooks. With Cogram, you can write queries in  English that the tool then translates into complex SQL queries with joins and grouping. It supports SQLite, PostgreSQL, and MySQL. This is a must-have for all Data Scientists! https://www.cogram.com/ Tabnine Lastly, similar to CodeComplete and Copilot, Tabnine is a whole-line and full-function code completion tool. I found Tabnine’s greatest strength in its auto-completion feature. Available as an extension, Tabnine supports all major IDE’s and significantly more than Copilot. Tabnine’s first version was developed in Rust by Jacob Jackson when he was still a student at the University of Waterloo. https://www.tabnine.com/ Have you ever used one of these tools, and how was your experience using them? Are there any other AI tools you can recommend? Let me know in the comments!

My Top 4 AI Tools for Coding

5 LLM-based Apps for Developers

Writing code is like an artist creating a masterpiece, putting thoughts and feelings into it. We expect developers to enjoy the process of writing and designing , as this careful work results in a digital product that solves real-life problems for users and provides a good experience. Developers focus on the art of writing efficient code, and tools or platforms that make delivering these coding masterpieces easier are highly appreciated by the developer community. code In this information age, the demand for digital products is at its peak, and hence, the tech industry is under immense pressure to release its products and improvements at a massive pace to gain substantial market share. The developers need to live with the continuous demand of releasing products. As depicted in the wagon wheel, developers allocate only 25% of their time to coding, aiming for a flow state akin to artistry. The tech industry grapples with challenges to boost overall developer productivity, and apparently, this was the most shocking discovery for Github CPO Inbal Shani. This article delves into strategies to amplify the impact of that crucial 25%, exploring ways to enhance productivity within the limited coding timeframe. With the advent of code , CodeLlama, Star Coder, etc., the entire tech community is debating and innovating to make the “time to code” for developers more effective, and it is exciting time to observe where the tailwinds of code generation using GenAI is headed towards and how does it impact in faster churn of code. Let’s segment and try to find answers to understand this entire situation better under these broad questions: LLMs like CodeT5 What problem do code-generation tools solve for the developers? Which developer teams are experiencing it as a significant problem? What are the solutions out there, and how do they solve the above-stated problem? What are the possible ways to measure the effectiveness of these tools in the developer lifecycle? 1. What problem do code-generation tools solve for the developers? Within the 25% of “time to code,” almost half of the time of a developer goes into writing the core business logic (which is true art) while the rest of his time gets occupied in either refactoring the code artifacts of his previous work, writing basic scaffoldings, writing database models (if any), basic validation and utility for generic use-cases, etc. Given the amount of time that goes into writing the trivial flows, if these code generation tools can save at least half of the time for companies and developers, then it may enhance the overall developer experience & productivity. One of the latest survey reports of McKinsey reflects the sentiment of the developer community, which strongly resonates that at least 30-35% of their entire code writing, documenting, and refactoring time can be saved with recent code generation Gen AI models and related solutions. 2. What are the possible solutions currently out in the market? With the advent of better LLM models, there are a bunch of companies that are solving the problem of code generation. Some of these solutions are either distributing themselves by building integration with IDEs (VS Code, IntelliJ, etc.) like Codium, Sourcegraph, Tabnine, GitHub Copilot, etc; on the other hand, there are few them who are focused on browser-based code editors like replit. Since all these solutions introduce natural language as the new interface of programming and generating code, the quality of code generated directly depends on the prompt and context provided; currently, the incumbents like have the maximum advantage compared to all new entrants due to plethora of code database it is sitting on and advancement of OpenAI model, new entrant still have an advantage if they closely work with enterprises and handles the security and privacy concerns which have been the key huddle for GitHub Copilot like the incumbent. Recent reports of Accenture look promising for space, and also, with the recent general availability announcement of copilot chat of GitHub, the scope of innovation with these code generation solutions is opening wide. GitHub 3. What kind of developers are adopting such solutions? Among the enterprise side of the code generation tools, GitHub CoPilot ranks #1 among all, with almost 37K enterprises using it in their workflow and having 1.5Mn+ active developers, while developers working in enterprise or startup teams mainly voted that the use of code generation tools is helpful because: Repetitive and redundant code changes with changing user requirements can be accommodated swiftly. Reducing the writing of boilerplate code for rapid prototyping. Efficient collaboration among teams for PR generation, review, and other such use cases. Reduced time to onboard the new developer. If GitHub Copilot is seeing its active adoption among enterprise teams, a large chunk of developers’ traffic is also using these code generation tools to learn new coding skills or learn basic programming fundamentals. This can be seen with the increased use of replit.com in the past few months, with an active volume of ~3-5Mn unique developers visiting these tools monthly [src - similarweb.com]. A recent poll from GitHub also gives a clear picture of the use cases for which developers are mostly adopting these tools. 4. What are the possible ways to measure the effectiveness of these tools in the developer lifecycle? We started this discussion by keeping developer productivity at the center and how these solutions can reduce the “time to code” and help developers ship faster, but in the software industry, it is tough to measure effectiveness and ROI just in terms of time due to it subjective quantification, but there can be other proxy ways which developer teams and engineering leaders can adopt to measure the ROI and effectiveness: Measuring the relative change in DORA metrics, tools like LinearB, Middleware HQ, etc., and other open-source tools like ApacheDevLake KLOC(Line of Code) generated from these tools is going live on production. Relative change in Developer Experience rating. Associating the financial ROI by keeping close observation on man-months needed to solve the problem. Path Ahead By being the tech operator in startups and writing code for so many years, I truly feel there is a bottleneck in the velocity of shipping code faster with increasing software demand, and as time unfolds and the state of code LLMs improves, we may head toward the age of mass code production compared to what we saw after the Industrial Revolution. In the book The Mythical Man-Month, programmer Fred Brooks observed how simply adding resources to a large programming project did not speed up the project—a good deal of the time, it made things worse. It's not yet clear if AI will dramatically help project scheduling and management or reduce the total effort required for a large programming project, but as the coder, what I can vouch for is that “prompt to code” will definitely, in some shape and form see massive adoption in the space of software development.

Is AI Code Generation An Age of Industrial Revolution for Software Enterprise?

260 Stories To Learn About Team Productivity

Developer Experience (also called “DevEx” or “DX”) has a direct positive correlation with productivity and innovation. Elsewhere, I wrote about how to spot the telltale signs of subpar developer experience. If you want to, you can read that one here. In that post, I suggested . It’s all about doing things that eliminate irritations and frustrations and maximize joy. These were: four ways to improve the developer experience Invest in resources and processes that make life easier, and nurture a sense of ownership. Work toward seamless collaboration to reduce data silos, improve visibility and enable more efficient workflows. Optimize the development environment to reduce friction and automate repetitive tasks. Be conscious about culture to create a supportive, inclusive environment where people feel trusted and appreciated. AI is ready to solve some major DX problems. Teams that get this right can expect to unlock substantial competitive advantages. I want to share how I think that can work. AI for Avoiding Data Silos and Enabling Visibility This category of tools is all about exposing high-quality information in the right places. That’s everything from creating useful, accurate resources to ensuring the right information reaches the right people at the right time. For Creating Resources The first use case for AI is perhaps one of the more obvious use cases – generative AI for creating resources. These kinds of AI can do things like write code documentation for you automatically or summarize meetings so you don’t have to rewatch the whole thing. Pick 1: Meeting summarization with . Otter AI automatically summarizes meetings and captures slides to generate easy-to-digest summaries of meetings. You can connect it to your Google or Microsoft calendar, and it can automatically join and record your meetings on Zoom, Microsoft Teams, and Google Meet. Otter AI Pick 2: for automatic documentation. Almost nobody is buzzing to write docs for their code, so make the most of code-aware LLMs and get them to do it for you. Mintlify For Surfacing What Matters The second use case for AI in this category is for surfacing what matters. As far as I’m aware, there’s only one tool that observes and reflects on everything that happens across the tools you use and surfaces what matters in a bespoke, personalized way. It’s called Stepsize AI, and I’m building it with my team at Stepsize. Pick 3: for surfacing what matters. You can schedule recurring reports bespoke to any team or person. Replace the daily standup, send recurring team updates, request personalized alerts when something you care about happens, or generate ad-hoc reports ahead of meetings. Stepsize AI It deeply understands the context of what your projects and goals are and can even answer questions about what’s happening. Here’s what that looks like: AI for the Development Environment We have to invest in reducing friction in the development environment if we want to boost productivity and satisfaction. AI has come on leaps and bounds in the last year in developing specific niches of the engineering process. For a more extensive list of dev tools CTOs should know about, head here. For Code Implementation Ask any developer, and they'll tell you - coding is often the stage where ideas take form but also where major bottlenecks occur. Too often, teams lose precious hours to syntax errors, library issues, and bugs that just won't squash. This hurdle can feel like a steep climb, causing unnecessary delays and frustration. Furthermore, codebases are living, evolving organisms. Your team's work isn't just about implementing new features, but also about understanding and navigating existing code. Annotating and understanding complex codebases can be a Herculean task, especially if the original author isn't around. AI Pick 4: for code implementation. It offers what feels like the next generation to GitHub Copilot, with code completion, error detection, and more that make each part of the software development process from reading, understanding, and writing code much more efficient. Sourcegraph Cody Honorable mentions: for writing tests, for an established but slightly less-cutting edge tool. Codium AI Tabnine For Code Reviews It's often a time sink because it's easy to get lost in endless lines of code, particularly if you're working on a complex project or a large team. Moreover, non-technical team members often find themselves left out of the loop. When your developers, product managers, and stakeholders aren't on the same page, it can cause confusion and delay decisions. AI Pick 5: to improve code reviews. To optimize the review process, What The Diff is worth your time. It’s an AI assistant designed to provide summaries, review pull requests, and even refactor code, making the entire review process more inclusive and efficient. What the Diff It’s also great for keeping non-technical team members in the loop and works really well with tools like (above) because it helps surface what matters about each pull request. CollabGPT Honorable mention: does something somewhat similar but with a focus on a great code review experience. Planar Deployment and Maintenance Let me guess. Nobody on your team lives for maintenance. But you have to deal with dependencies and migrate code. there were a way to do that hands-free. If only AI Pick 6: for hands-free tech debt management. Right on cue! Grit helps manage code migrations and dependencies, and its radar is designed to spot potential regressions, offering a smoother ride through the deployment and maintenance stage. Grit.io What You Need to Remember… AI for software developers isn't a silver bullet that's going to solve all your DX issues with DX tools overnight. It's a facilitator. It’s about leveraging the power of artificial intelligence to bolster the creative and innovative elements of software development. That's where the real competitive advantage lies. Adapting to an AI-driven Developer Experience (DX) requires more than just selecting the right tools. It's a holistic process that impacts your team's workflows, skillsets, and overall development culture. As leaders, our roles in this transition extend beyond decision-making to driving the necessary change. Firstly, ensure your engineering team is trained and well-equipped to work with AI tools. Next, reevaluate your development workflows. Lastly, and perhaps most importantly, nurture that culture of continuous learning and innovation. The AI landscape is continuously evolving, and to make the most of it, your team should too. Encourage your software engineering teams to stay updated with the latest AI trends, offer regular training, and create a safe space for experimentation. Remember, AI's potential is best unlocked when human creativity and machine intelligence are blended. That’s why I created Stepsize AI, the AI Operational Intelligence Engine that takes all the manual work out of keeping informed about what matters. By integrating with Jira, Slack, GitHub, and more, Stepsize AI deeply understands the context of your projects and goals, providing bespoke, personalized updates for any person or team depending on what matters to them. We believe Stepsize AI is a game-changer. I’d love for you to give it a spin. . Try out Stepsize AI here Also published here

Leveraging AI to Enhance the Developer Experience (DX): A Guide

Developed by and released eight years ago, (VS Code) is the widest-used source-code editor. Its great features have made it the number one choice of many who enjoy intelligent code completion, snippet generation, code refactoring, and syntax highlighting. Microsoft Visual Studio Code According to the 2021 , VS Code is the most popular development environment among developers, with 73.1% of respondents using it. Its popularity can be attributed to its wide range of features, including built-in debugging, git integration, and support for multiple programming languages, as well as its active development community. But it’s the array of extensions and plugins available in VS Code that brings me here. Stack Overflow Developer Survey One of the biggest strengths of Visual Studio Code (VS Code) is its extensibility. VS Code allows developers to customize and extend the editor's functionality in so many cool ways. From adding new features and integrating with external tools and services to enhancing the development experience in many ways. And the best part? There are thousands of extensions available in the VS Code ecosystem, touching almost every situation you could think of. Today, I’ll focus on just 3 classes of extensions: productivity, debugging, and language support. Productivity Doing more with less and optimizing for efficiency is a big part of technology, it wouldn’t make sense if the development process were any different. Here are some tools that are likely to boost your output. is a powerful extension for Visual Studio Code that enhances the functionality of Git. It provides a wealth of features that allow developers to easily track code changes, view commit history, and analyse code authorship. Additionally, it allows for efficient collaboration and code review among team members. GitLens is an extension for Visual Studio Code that enables real-time collaborative coding and debugging. It allows multiple developers to simultaneously edit code, debug in real-time, and share their terminal sessions with each other. Live Share enhances collaboration and makes it easier for remote teams to work together seamlessly. Live Share is a powerful extension for Visual Studio Code that makes code formatting easy and consistent. It supports multiple languages and automatically formats code based on a set of rules. Prettier saves developers time and effort, eliminates debates over formatting, and improves code readability and maintainability. Prettier is an extension for Visual Studio Code that simplifies HTML and CSS coding. It allows developers to write code using abbreviations and then expands them into full HTML and CSS code. This saves time and reduces errors while increasing productivity and consistency. Emmet is an AI-powered extension for Visual Studio Code that suggests code as developers write. It uses machine learning to learn from existing code and provides contextual recommendations to improve efficiency and productivity. Copilot can save developers time and enhance the development process by providing more accurate and relevant code suggestions. GitHub Copilot is an extension for Visual Studio Code that captures screenshots of code and converts them to image files. It supports multiple file formats and provides a customizable interface for capturing screenshots. Code Snap makes it easy to share code snippets and improves communication among team members. Code Snap is an AI-powered extension for Visual Studio Code that provides predictive text and code completion suggestions as you type. It learns from your codebase and supports multiple programming languages, allowing developers to write code faster and with fewer errors. TabNine improves efficiency and enhances the development experience. TabNine is an extension for Visual Studio Code that automatically renames paired HTML/XML tags as you type. This saves developers time and reduces errors when working with complex code. Auto Rename Tag enhances productivity and simplifies the development process. Auto Rename Tag is an extension for Visual Studio Code that displays the size of an imported package as you type. It supports multiple package managers and provides real-time feedback on package sizes, allowing developers to optimize their code and minimize file size. Import Cost enhances performance and helps developers avoid unnecessary dependencies. Import Cost is an extension for Visual Studio Code that adds icons to file and folder names, making it easier to identify them at a glance. It supports many different file types and themes, allowing developers to customize their workspace. VSCode-icons improves productivity and adds a touch of personalization to the editor. VSCode-icons is an extension for Visual Studio Code that enables developers to send HTTP requests and view responses directly within the editor. It supports multiple HTTP methods and response formats, making it easy to test and debug APIs. REST Client improves efficiency and simplifies the API testing process. REST Client is an extension for Visual Studio Code that simplifies regular expression (regex) creation. It provides real-time previews of regex matches, highlights errors, and provides detailed explanations of the regex syntax. This extension saves time and increases accuracy when creating complex regex patterns. Regex Previewer Debugging In addition to the built-in debugging extensions available in VS Code, there are also many external debugging extensions that can be installed to extend the debugging capabilities of the editor. But why debug in the code base, you might ask? Debugging involves setting breakpoints in the code and examining its behavior at various points during execution. This approach can be very powerful, as it allows developers to see exactly what is happening in the code and can help us quickly identify and fix bugs. Additionally, debugging in the code base can be done regardless of the browser or other environment in which the code is running, which can be helpful if the problem is not related to the browser itself. Language Support VS Code provides language support for many programming languages out-of-the-box, but there are also many language support extensions available in the VS Code Marketplace that provide additional functionality for specific programming languages. Most mainstream languages have a language support extension that incorporates your usual features like snippets. Conclusion I can’t imagine looking at VS Code's extensibility and choosing any other editor. Hence why its popularity among developers is no surprise. The ability to customize and extend the editor to suit specific needs and workflows is a major advantage that has made VS Code the preferred choice for many. Honestly, it’d be too difficult to explain how much stress some of these tools have saved me. It’s a lot easier to just imagine how difficult life would be if it didn’t exist. From newbs to seasoned pros, we can’t live without these extensions, whether it’s for language-specific helper tools or to aid your debugging. Even just for reducing the share number of keystrokes needed to complete a task, your keys will thank you ;) I’m always looking for more extensions to make my life easier so I’d love to hear your favourite extensions in the comments.

VS Code Extensions Every Developer Should Know

Introduction How many times have you heard the word "AI" in 2023? There is a probability that you must have heard it too many times, especially with the popularity of ChatGPT. AI, which is an acronym for Artificial Intelligence, is a fast-growing phenomenon in today's world. According to statistics, . From education and health to entertainment and business, AI is reshaping our environment and our way of life. the global AI market is valued at over $136 billion and is projected to increase by over 13x over the next seven years At the same time, it is opening up new possibilities and posing new risks to the continued growth, welfare, and survival of mankind. In the modern world, AI is a rapidly expanding phenomenon. Statistics show that the global AI market is already worth over and is expected to grow by more than 13 times over the following seven years. $136 billion AI’s Basic Working Principle… Artificial intelligence is basically the capacity of a digital computer or computer-controlled robot to carry out actions frequently performed by intelligent individuals. Systems and tools that are built with AI can recognize, combine, and deduce information from a variety of data sources, including audio, photos, videos, text, and more, and they can also learn from this information. They can learn from prior experiences, generalize, use reasoning, find meaning, and adapt to new circumstances, which helps them become more intelligent. AI Tools Across 11 Different Sectors in the Modern World Most industries throughout the world—if not all—use AI tools and technology in some capacity. Although it mostly has some beneficial effects, there is concern that given how quickly AI is expanding and improving, and it may have the ability to eliminate many occupations. How accurate is that? But first, let's examine some of the well-known industries that have begun making major use of AI to make this determination. 1. Finance There are powerful AI tools that are used by a variety of financial organizations and even individuals in the areas of financial planning and analysis, assessing credit risk, fraud detection, trading, and investments, optimizing insurance claims processing, sales, and customer services, and digitizing historical files and documents, amongst other applications in the field of finance. Some of the tools include: A virtual assistant tool in the Bank of America mobile app that assists users with a variety of banking operations like checking balances, paying bills, and sending money, as well as balance reconciliation. Capital One also has a similar virtual assistant called  Eno, which notifies users of suspected fraud, price increases, or payment reminders. Erica: Enova uses AI technology to aid users have access to credit facilities and helps financial institutions to solve the challenges surrounding borrowers’ assessment through the provision of sound financial analytics. : Enova An AI-powered platform using data points to provide financial institutions with the data to conduct assessments on borrowers with little or no credit information : Zest : A technology that makes use of artificial intelligence to accurately process financial records like pay stubs, tax returns, and other related ones at a faster speed. Ocrolus provides a predictive model that helps financial institutions solve issues surrounding marketing, wealth management, fraudulent credit card transactions, underwriting, and business growth. : DataRobot an identity verification system that uses ML and AI to analyze and verify applicants’ data to ensure that the KYC details are accurate. : Socure 2. Blockchain Several techniques, including strengthening data security and privacy, improving data quality and trust, optimizing data processing and storage, creating data insights and value, integrating data across platforms and domains, etc., are employed by AI to reinvent and optimize the blockchain sector. Some instances include: - using AI and formal verification to authenticate the security of a blockchain, smart contracts, and web3 dApps. CertiK - which certifies and verifies valuable pieces of art and NFTs on the blockchain using AI. Verisart - which leverages AI to allow quicker transactions, more scalability, and less energy use. Matrix AI - employing artificial intelligence to examine cryptocurrency market movements and offer market insights for individual investors. Token Metrics - which employs AI to build a decentralized network of AI services that can communicate with one another and trade value on the blockchain. SingularityNET 3. Transport AI is revolutionizing transportation and supplying driving assistance. Some of the tools include: This company uses AI to power its autonomous vehicles and taxis for urban transportation. : Waymo Rapid Flow Technologies uses traffic management to deliver adaptive traffic signal control systems that lower congestion and pollution. This is done by analyzing traffic patterns, predicting traffic flow, and optimizing traffic lights using data and algorithms. : Rapid Flow Technologies Using AI, Uber apps are designed to find compatible drivers and passengers, calculate prices and arrival times, and offer safety features. These enhance passenger transportation services by personalizing travel options, streamlining pricing and scheduling, and enhancing customer satisfaction. : Uber Clear uses AI to build biometric identification verification services that let users use their faces or eyes as boarding credentials in airports.  This expedites airport security and boarding procedures in the aviation industry. : Clear With AI, Volocopter has been able to build its drone Taxis which will safely traverse the airspace, avoid obstructions, and land at designated places within a busy urban city. It offers a faster transportation system through congested streets by flying in the lower airspace with zero-emission. : Volocopter 4. Data Analysis One of the key industries using AI and machine learning is data analysis, which does so in a variety of ways, such as by analyzing unstructured data, producing data insights, streamlining data processing, integrating data across platforms and domains, and others. A few of the numerous AI tools that are used in data analysis include: A software program that forecasts data performance using artificial intelligence and suggests subjects based on prediction scores. : Tableau An AI tool designed by Microsoft for Data Analytics, Data Visualization, and Business Intelligence : Power BI A platform to analyze user data and offer insights and recommendations : Research AI An open-source tool to build customized data pipelines, workflow, and solutions for a range of data analysis task : KNIME An AI tool for analyzing and indexing a huge volume of data in real-time : Splunk 5. Software Engineering The coding and design industry is being reinvented and optimized by AI in several ways. Currently, programmers can generate, edit, optimize, check, and transform codes with the use of artificial intelligence (AI). Some of the AI tools available at their disposal include: A tool called , which can create code in common development environments, is , which is based on the GPT-3 standard. GitHub Copilot powered by the OpenAI Codex model A program called ** **utilizes artificial intelligence to examine code and identify flaws that would prevent it from running. Embold This tool is an app that provides programmers with comprehensive facilities to build, edit, and test codes and applications. Examples of popular IDEs include VS code, Eclipse, IntelliJ IDEA, PyCharm, Xcode, Android studio, NetBeans, Atom, Sublime Text, and Vim. The integrated development environment (IDE): An auto-completion tool that can be integrated into IDEs to improve productivity. This tool employs deep learning algorithms to predict the rest of the code a programmer is typing. : Deep TabNine : This AI-powered coding assistant using natural language, can generate codes, complete the function of the codes, and generate the summary of a function. CodeT5 Other AI tools that aid programmers include Google Bard, ChatGPT, AskCodi, Mutable, IBM Watson Code Assistant, Code-LMS, WPCode, and Amazon CrowdWhisperer. 6. Entertainment Although technically speaking, humans make up the majority of the characters, artists, and actors in the entertainment industry, artificial intelligence (AI) has begun to play crucial roles in the sector and is used in significant areas like generating, analyzing, optimizing, moderating, and personalizing realistic content for their audiences by using data and algorithms. Some platforms for entertainment that use AI are: aids artists in writing the lyrics of a song. It can write songs in over 100 languages. Lyrical Labs offers video analytics and insights across a variety of platforms, including YouTube, Facebook, Instagram, and TikTok. Tubular Labs is an AI-powered platform using machine learning algorithms to match licensed music with visual content. SyncFloor This is an AI video creation tool that can convert text data to video content. Lumen5: Other global organizations that inculcated AI into their products are Netflix__,__ which uses AI to adapt its streaming quality and bandwidth use to the customers' devices and networks; YouTube, which employs AI to search and eliminate content that breaks its community standards; and Spotify which utilizes AI for curating customized podcasts and playlists for its subscribers depending on their listening patterns. 7. Manufacturing This industry makes use of AI in several areas, including boosting predictive maintenance, streamlining manufacturing procedures, automating production duties, fostering production innovation, and more. The following are some instances of production platforms using AI in their operations: offers AI-based visual inspection solutions for a range of industries, including textiles, electronics, and the automobile. Landing AI for a variety of industries, including energy, mining, and transportation. Uptake leverages AI to offer predictive maintenance solutions. Uptake __c__an give solutions for the optimization of processes in a variety of industries, including the chemical, steel, and cement industries, by utilizing AI. __ m __ Petuu offers robotic picking solutions for a range of industries, including e-commerce, shipping, and the food industry. Covariant For generative design solutions across a range of industries, including architecture, engineering, and construction, leverages artificial intelligence (AI). Autodesk 8. Gaming AI may be used to create intelligent, human-like NPCs that communicate with players, forecast player behavior to improve game design and testing, provide lifelike images and audio, improve gameplay, and increase immersion, among other things. By using data and algorithms, it is also utilized to create, analyze, optimize, moderate, and personalize realistic material for their games. Several instances include: AI is used by to deliver statistics and insights for games across a range of platforms, including PC, mobile, and console. Unity AI is used by to recommend the best times to release mobile games as well as their prices and marketing techniques. Google Play In multiplayer games, employs AI to detect cheaters and block them. Steam 9. Healthcare AI activities in the healthcare industry are increasing by the day. Using systems like Natural Language Processing, Machine Learning, and deep learning algorithms, its impact is greatly felt, especially in domains such as; illness detection and patient care improvement, forecasting and epidemic prevention, medication discovery and development, personalizing and optimizing therapies, and much more. Some notable instances of AI in healthcare  include: The use of AI by to help oncologists diagnose and treat cancer. IBM Watson Health AI-powered tool to track and predict infectious disease outbreaks globally. BlueDot tool used to organize searches across billions of chemicals for possible drugs to speed up drug development. Atomwise Provision of individualized treatment plans by to provide patients with chronic diseases. Wellframe The Future In the years and decades to come, AI will become the centrepiece of innovation in the world, ushering in growth and influencing the world in ways that pave the way for enormous possibilities as well as threats to humanity's progress, prosperity, and the very existence. Possible outcomes may include: More individuals and businesses making use of AI's capabilities and applications as it becomes more widely available and democratized. It is expected that its interaction and synergy with other technologies like cloud computing, 5G, IoT, blockchain, and quantum computing will birth new realities. Advancement to the point where it can generate its content, goods, and services without human intervention. This advancement may accelerate to the level where it will be able to learn from its own experiences and those of other AIs, leading to novel kinds of intelligence and cooperation. A greater influence, transformation, and disruption across many fields and businesses. In conclusion, the development of AI has an inevitable future. It all comes down to how researchers plan, build, implement, and regulate AI systems. How well we adjust to the new opportunities and threats that AI presents will tell how deeply AI will twist our realities. To create the kind of future we want for artificial intelligence, we must be proactive, collaborative, and inclusive.

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Let's learn about via these 84 free stories. They are ordered by most time reading created on HackerNoon. Visit the to find the most read stories about any technology. Vscode /Learn Repo 1. Compiling CUDA File in VS Code [A How-To Guide] Trying to compile a .cu file is not supported in the VS Code natively. This can be a issue if you want to compile and debug  (atleast the CPU part of the file as kernel debugging is not supported in VS Code at the moment). 2. VS Code Extensions with a Bright 2022 This story has a list of VS Code Extensions that has great potential and will possibly do well in the coming year. If you use vs code you should read this. 3. Install and Configure Git on Amazon Lightsail, and Deploy Your Website in Minutes! (Freebie Inside) We break down how to easily deploy your new website on Amazon Lightsail in less than 5 minutes. Get your code up and running and get back to doing what you want 4. Why Taking Good Notes is Critical For Developers Why taking good notes is critical for a software developers? 5. How to Compile C/C++ Code in VS Code (Windows) How to Compile C/C++ Code in VS Code (Windows): To compile C/C++ code we need GCC/G++ to compile the code but Windows doesn't have a terminal. 6. No More Mistakes With VSCode Expand-And-Collapse Options I recently had a large amount of data to refactor out of HTML and into JSON. The details about how I achieved this is a whole different article. What I want to document for myself (and maybe others will find it useful, even if it's only a refresher) are the various code expand and collapse options. 7. Writing Google Apps Script Code Locally in VSCode An easy Set-Up guide to writing google apps script locally with VS code with clasp. 8. 5 Best VS Code Extensions for Refactoring that Every Dev Should Know If you’re looking at ways to clean up our code, reduce complexity and improve functionality - these refactoring extensions will help you move faster. 9. How I Cloned a Simple VSCode Using Tauri and ReactJS How I built a simple code editor like VScode using Tauri and Reactjs 10. Visual Studio Code vs Sublime Text: Which Editor Should You Choose? We have given the benefits of Visual Studio Code and Sublime Text in this article. Compare both code editors based on some factors and choose the better option. 11. 15 VSCode Extensions to Boost your Productivity in React In this article, I will share the VSCode extensions I used for react development and productivity. 12. Como instalar VS Code en Ubuntu 18.04.1 LTS Dentro de nuestra travesia para aprender a desarrollar aplicaciones descentralizadas para Hyperledger blockchain encontraremos un IDE recomendado; VS Code. 13. 5 Best VS Code Extensions to Help Organise Your Code in 2021 Use these 6 VS Code extensions that help devs get organised and work effectively. 14. 10 Best Python IDEs & Code Editors: 2020 Edition Since its advent in 1991, Python has been the choice of coders due to its simple features that include ease of understanding and readability of code but not limited to just that. There have been lots of changes in the codebase over time due to the contribution from developers worldwide. Simple syntax and faster execution make Python a favorable language among programmers. It is used widely to create websites and primarily in big data operations. To make the task of running Python programs easier, many IDEs have been developed for programmers. These environments are equally suitable for beginners and advanced coders with a variety of in-built extensions, libraries, and plugins to ease the task of program execution. Let's walk you through these six IDEs that can ease your work with Python: 15. Indent-Rainbow Tool for Making Your Code More Readable The article discusses the importance for using indent-rainbow to give some color to your code in HTML 16. Easily Formatting Markdown Files in VS Code This VS Code extension helps you when writing markdown to format your text, create lists, and create and modify tables with ease. 17. How To Set Up Vue Linting in VS Code I'm a gopher by nature, so I expect consistent styling and linting in my codebases. More importantly, though, I don't like to think about styling. I like to type haphazardly and then have my editor apply styling automatically on save (ctrl+s, cmd+s). 18. What is Next.JS and How to Debug it Next.JS allows the developers to create Server-side, Client-side or Static websites. Unlike the other frameworks, the rendering in Next JS is per page. That means, the "about" page can be static, while the "home" page can be server-side. 19. 6 Best Chrome & VS Code Extensions For Developers Extensions can make our life as a developer a little easier. Here are 6 of the best Chrome and VSCode extensions for Developers. 20. My Coding Workflow: How I'm Working From Different Places As A Software Engineer Coding is not an easy process, especially if you have to be super focused to do it relatively fast and without bugs. Keeping the focus on coding only is quite a difficult challenge, but this story is more about how to make the ultimate setup to code from anywhere with the internet and browser! 21. The Search-and-Replace Regex with VS Code This is a feature I use with some frequency, but not frequently enough that I remember the pattern when I need it. Therefore, I am writing this article as my own reference to a useful tool with VS Code. 22. How to Learn All VSCode Shortcuts on Mac, Linux and Windows Do you feel intimidated when you see other programmers quickly navigate through hundreds of lines of code, make blazing fast edits or open multiple tabs during development and hardly touch their mouse or touch-pad ? 23. Kill Technical Debt Before it Kills Your Project 24. Top 10 VS Code Extensions to Boost Productivity A curated list of my top ten VS Code extensions that will supercharge your productivity and make you more effective as a developer. 25. Mobile App Debugging Explained on 3 Levels of Difficulty Mobile debugging across different levels of experience. 26. Top 5 VS Code Extensions to Boost Your Coding Productivity Today I prepared for you my pick of relatively new, interesting extensions from the VS Code marketplace that have recently been growing in popularity. 27. Transitioning From VSCode to NeoVim As a DevOps engineer, I recently reached a significant milestone: I switched code editors for the fifth time in my career. 28. How to See Which Branch Your Teammates are on in VS Code In VS Code, open up the team tab by clicking on the GitLive icon on the activity bar. Locate the teammate you are interested in and click the arrow 29. Cloud Collaboration Tools for Engineering Teams It's a story about how I set up a development environment in five minutes 30. A Step-by-Step Introduction to CSS Preprocessors with VS Code It is fun to build cool and good looking pages when you know CSS like the back of your hand. But when you have a few hundred lines of code, this is exactly when things begin to get complicated and messy. This is where CSS preprocessors come to play, helping you to manage and improve the maintainability of your code. 31. Get Notified When There are Commits to Pull in VS Code With the help of GitLive’s new pull reminders, you can now pull sooner, reduce the chances of conflicts, and merge faster! 32. How to Add Custom Shortcuts and Code Snippets to VS Code In this article, we'll learn how to create custom VS Code shortcuts and code snippets. 33. How to Configure Useful User Snippets in VSCode for Golang In this article, I'll show how we can configure some useful user snippets in VSCode to make our life easier. 34. 3 Awesome Themes for Visual Studio Code More than 2,600,000 people use VS Code every month, up by over 160% in the last year. 35. Code Faster: 12 VS Code Shortcuts Here are 12 VS code shortcuts to help code faster. 36. Useful Tools To Make Working on HTML and CSS Easier Programmers and Developers are lazy people, they always want to make their jobs easy. They do not want manual and repetitive tasks. They want to automate tasks. 37. A New Hope for ML Experimentation A quick guide introducing the DVC VS Code extension by Iterative.ai, helping ML Engineers and Data scientists perform better experimentation 38. Top 5 VS Code Extensions for Remote Working A list of the best VS code extensions. 39. It Isn't Just GitLens: 6 Cool VS Code Extensions to Supercharge Git Yes, I know, we should all be terminal ninjas, memorising every git command yadda yadda. Or, like the caveman, we could put two sticks together (or in this case 40. 12 Best Vscode Extensions to Boost Your Productivity in 2022 This article is about some useful VScode Extensions that you can use to increase your productivity and save some time while programming in 2022. 41. 5 Best Plugins For Dev Teams Looking to Level Up Productivity 🔥🔥🔥 Best VS Code Plugins and JetBrains extensions for dev team. Boost developer productivity with GitLive, Tabnine, Stepsize, EditorConfig and Better Comments. 42. What Is Remote Pair Programming? COVID-19 may have forced us all into working remotely, but that doesn't mean we can't still pair program! The VS Code Live Share extension is here to help. 43. The Best IDEs and Code Editors for Learning Pyton In this post, we compare the best Python IDEs and Code Editors. 44. The Best Software for Dev Teams to Review as They Welcome 2022: A 2021 Highlight Reel How would I sum up 2021? 45. Debug your AWS Lambda in Production in just 5 steps By using AWS Lambda Debugger VS Code Extension, you can debug your serverless applications natively with their permissions. 46. Triple Your Results With These Top 8 VSCode Extensions We all use some VS Code extensions for our day to day development and are always on a hunt for more useful extensions. Here is a list of mine and how I use them: 47.  A Few Words on VS Code Go has hard opinions about how you should style and format your code. The big upside of this is that you don't need to spend hours setting up tools like ESLint, Prettier, JSLint, etc. That said, in order to take advantage of the styling and listing tools available in the toolchain, you need a dev environment that makes them easy to use. 48. Reduce Context Switching with these 7 VS Code Extensions Extensions that help you stay in the editor reduce context switching and help you reach the state of flow. 49. Fixing ChatGPT's Limitations for Coding Quickfix AI is an extension for VS Code that provides you instant solutions for errors in your code within your code editor using AI. 50. VS Code: What if I Need to Replace Something with $? In a previous article about VS Code, Search-and-Replace using RegEx, I had a question that prompted me to create this article so that I can remember what I did ... 51. The Ensuing Battle Between Python vs. .Net Continues C# and Python are two of the most popular languages with C# being widely used in business applications, while Python is more flexible and easier to learn. 52. VS Code Tutorial: How To Set Up A React.js Project With Next.js Express.js framework provides inbuild APIs which are very useful to build fast and scalable applications efficiently with React.js. 53. Setting up a Debugging Environment for Azure Functions 2.x using VS Code Overview 54. Introductory Guide to Debug Node.js Apps with Built-in or VS Code Debugger If you ask me on which task I've spent most of my time as a software developer, it would probably be bug fixing. Working with JavaScript apps, I've used console.log when debugging surely more than I should have. Learning how to become efficient at finding bugs in programs is a very important skill that can save you a lot of time. Debuggers help you with that task by providing tools to analyze your programs and run control execution flow. 55. I Built a VSCode Extension: ngrok for VSCode Over the Easter weekend, a four day weekend characterised by lockdowns all over the world, I decided to use the extra time I had at home to start a new project and learn a new skill. By the end of the weekend I was proud to release my first VSCode extension: ngrok for VSCode. 56. Real-Time GraphQL API Exploration with GraphQuill As software engineers, we use tools built by other devs dozens of times a day. Personally, I use over 15 VS Code extensions. Until my team and I set out to build GraphQuill, I didn’t have the slightest clue about the process of developing and publishing an extension. It’s been a fun and worthwhile experience working within the VS Code extension space, so when my team and I got together to discuss releasing GraphQuill, I insisted we include a behind the scenes look at the development process and what challenged/excited us throughout. 57. How To use Google Colab with VS Code Google Colab and VS Code are popular editor tools. Learn how you can use Google Colab with VS Code and take advantage of a full-fledged code editor. 58. How To Make Correct Line Endings Ever had the problem where you submit a pull request and the diff is waaaaay bigger than it should be? The code looks identical but GitHub is telling you that it's all different! This is typically due to a difference in line endings. Unix systems (Linux and Mac) default to the LF (line feed) character for line breaks. Windows on the other hand is "special" and defaults to CR/LF (carriage return AND line feed). 59. Shifting Containers Left: On the Quest for Reproducible Development Environments Photo by Casey Horner on Unsplash 60. Quick Guide to Install Node, Yarn, Git and VSCode on Linux, Mac, and Windows How to install Node, Yarn, Git and VSCode on Linux, Mac and Windows, a simple and easy guide to follow. 61. 10 VSCode Extensions To Make Your Life Easier I’ve been using VSCode for almost 2 years now and I like it so much. I’m sure that you like it too. Extensions are a core part of VSCode that adds extra functionality to the editor. I’ve installed about +40 extensions and here is my top 10 list. 62. Reduce Your Eye Fatigue With These Top 6 Fonts for Easier Programming in 2021 In this article, I'm going to share the best fonts you can use specifically for coding. Let's take a look! 63. How To Become A VSCode Girl - From A VSCode Girl I didn’t coin the term “VSCode girl” but I’m here to teach you how to become one. It’s a lifestyle, a mindset, not a stereotype. 64. 5 VSCode Quick Tips to Boost Your HTML Writing When I started writing HTML and CSS documents, I found out that one of the best ways to practice building websites was cloning some of them. I spent a lot of time dealing with monstrous HTML documents with tags full of texts and links, which sometimes was not the most exciting experience. Since then, I've managed to look for some time-savers that could improve my efficiency inside VSCode, and here are some that I found: Selecting blocks of text 65. How to Write Clean, Well Maintained Code Using a Static Analyzer and PMD A static analyzer can reduce the possibility of bugs, such as when you accidentally overwrite a variable with another value. 66. How to Configure VS Code for Java in 2022 VS Code is Java-ready! Learn which extensions to use and how to configure it to start coding Java in a modern IDE. 67. VS Code Extensions to Power Up Your JavaScript Development Important VS Code Extensions for JavaScript Developers. 68. 12 Visual Studio Code Shortcuts For Faster Coding There are some great tools and extensions that might help your coding experience enjoyable in the VS Code. That is great and all but there might be a chance you are missing out on some great shortcuts that VS code offers. That is why this article is here to help you with some of the most useful shortcuts for faster coding. 69. 7 VS Code Extensions for Frontend Developers As a developer, you’re always looking for cutting-edge tools, tricks, and extensions.  Here are 7 tools that'll improve your productivity and efficiency. 70. 5 Copy and Pasting Tips For Every Developer to Know Work Smarter, Not Harder. 71. Effective Coding Workflow: My VS Code Setup There are a lot of Code Editors, some are free and some are paid. Among all of them my favorite Code Editor is Visual Studio Code. It's free and has amazing features. I'm using it from the beginning of my web development journey. 72. Best IDEs for .NET Development The .NET Core platform makes it possible for businesses to develop applications for just about any platform—from Windows, macOS, Linux, and even mobile operating systems. This isn’t just a time saver, but a means to cut back on your budget. You will be able to develop across all platforms, and you won't have to hire developers for each ecosystem. Instead, you can hire one developer or a team of .NET developers to make it all happen. 73. Embedded Development: 5 Tools to Try in 2021 Advantages and Disadvantages: 5 Embedded Development Tools, Compared. 74. Become More Productive As A Developer With These Amazing VS Code Extensions How can developers be extra productive? You’re a developer or you manage a team of developers, higher productivity can get you extra things done through ... 75. 7 Must Use Tools For Newbie Web Developers During my journey of learning web development I came across this different technology and stuffs which are often used during web development or writing code and 76. Set up CSS stylelint on Visual Studio Code [Tutorial] While you’re coding it’s of great importance to know what does each line of our code and which elements are being affected by it but it is also important to follow good practices, and over time this can benefit us. 77. How to Create an Extension Pack for VSCode & Code Server This guide outlines and explains the process for creating an extension pack for VS Code & Code Server before publishing it on GitHub release using Travis CI. 78. Github Codespaces Vs. Gitpod: Choosing the Best Online Code Editor Gitpod and Github Codespaces are VS code-based online editors, with attached Linux env servers, which of them is best for you? 79. How You Can Set Up Remote Development Workflow With VS Code in Your Browser In this guide, I will be walking through VS Code-Server setup with DigitalOcean, as well as tweaks I have used to create a clean, simple workflow. 80. 4 Tips on How to Refactor Code in Visual Studio Code This article looks at how you can refactor your code using Visual Studio Code (VS Code) and Visual Studio Code plugins. 81. How to Run and Debug C / C++ Code via VSCode By the end of this short guide, you’d be able to run, debug, and get IntelliSense for C/C++ files in VSCode 82. Introducing Github1s: A Browser-Based VSCode Project Viewer Github1s is a hot new open source project that allows you to browse Github repositories in a VSCode-like UI right in your browser. 83. Free Tools That Will Help You Grow As A Front-End Developer In 2021 You only need this post to become a Front-end Developer because this post has nearly unlimited amount of every type of resources covering everything you.... 84. Introduction to Code-workshop-kit: a Tool for Remote Code Workshops I created a tool for people that teach code, called code-workshop-kit. It makes remote workshops interactive and allows for experiences similar to those in a classroom, and better. Thank you for checking out the 84 most read stories about Vscode on HackerNoon. to find the most read stories about any technology. Visit the /Learn Repo

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