[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"academy-blogs-en-1-1-all-using-ai-tools-in-code-development-and-project-testing-all--*":3,"academy-blog-translations-2ivf2r4edncngru":81},{"data":4,"page":80,"perPage":80,"totalItems":80,"totalPages":80},[5],{"alt":6,"collectionId":7,"collectionName":8,"content":9,"cover_image":10,"cover_image_path":11,"created":12,"created_by":13,"expand":14,"id":75,"keywords":76,"locale":49,"published_at":77,"scheduled_at":13,"school_blog":71,"short_description":78,"status":69,"title":6,"updated":79,"updated_by":13,"slug":72,"views":74},"Using AI Tools in Code Development and Project Testing","sclblg987654321","school_blog_translations","\u003Cp data-start=\"58\" data-end=\"339\">Software development today is evolving at a much faster pace, especially with the integration of AI (Artificial Intelligence) into code development and project testing. This advancement allows development and testing processes to be executed more quickly and efficiently. In recent years, AI tools have significantly enhanced the productivity of developers by streamlining workflows and minimizing errors. In this article, we’ll explore AI tools that developers can use to support both coding and project testing—helping you write code faster, reduce bugs, and improve testing effectiveness.\u003C\u002Fp>\u003Ch2>1. Using AI in Code Development\u003C\u002Fh2>\u003Cp data-start=\"166\" data-end=\"648\">Using Artificial Intelligence (AI) in code development is becoming an essential part of modern software development—especially in an era of rapidly evolving technology. AI can help programmers work faster and reduce errors caused by manual coding. AI-powered tools assist developers with auto-completion, recommending appropriate functions, detecting errors, and even generating code from plain text instructions. This improves workflow efficiency and shortens development time.\u003C\u002Fp>\u003Ch4 data-start=\"650\" data-end=\"701\">Key AI Features That Support Code Development:\u003C\u002Fh4>\u003Cul data-start=\"703\" data-end=\"1977\">\u003Cli data-start=\"703\" data-end=\"922\">\u003Cp data-start=\"705\" data-end=\"922\">Auto Completion: AI leverages existing code and IntelliSense to provide real-time code suggestions as developers type. For example, typing \u003Ccode data-start=\"852\" data-end=\"861\">console\u003C\u002Fcode> will prompt the AI to suggest \u003Ccode data-start=\"892\" data-end=\"907\">console.log()\u003C\u002Fcode> automatically.\u003C\u002Fp>\u003C\u002Fli>\u003Cli data-start=\"924\" data-end=\"1190\">\u003Cp data-start=\"926\" data-end=\"1190\">Function Suggestion: When writing functions or working with unfamiliar libraries, AI can recommend functions from related libraries. For example, if you're coding in JavaScript and want to convert JSON to a JavaScript object, AI can suggest \u003Ccode data-start=\"1175\" data-end=\"1189\">JSON.parse()\u003C\u002Fcode>.\u003C\u002Fp>\u003C\u002Fli>\u003Cli data-start=\"1192\" data-end=\"1417\">\u003Cp data-start=\"1194\" data-end=\"1417\">Error Checking: AI uses machine learning to analyze your code and detect possible errors. Tools like DeepCode and GitHub Copilot can scan your codebase and recommend corrections that you may have overlooked.\u003C\u002Fp>\u003C\u002Fli>\u003Cli data-start=\"1419\" data-end=\"1695\">\u003Cp data-start=\"1421\" data-end=\"1695\">Best Practices Recommendation: AI can recommend best coding practices—such as writing flexible, maintainable code—by referencing patterns from various codebases. This includes design patterns, clean code structures, or the most suitable functions for specific tasks.\u003C\u002Fp>\u003C\u002Fli>\u003Cli data-start=\"1697\" data-end=\"1977\">\u003Cp data-start=\"1699\" data-end=\"1977\">Code Generation from Text Commands: Tools like OpenAI Codex or GitHub Copilot can generate full code snippets from plain text prompts. For example, if you write “create a database connection function in Node.js,” the AI will generate the relevant code instantly.\u003C\u002Fp>\u003C\u002Fli>\u003C\u002Ful>\u003Ch4 data-start=\"1979\" data-end=\"2018\">How to Use AI in Code Development:\u003C\u002Fh4>\u003Cul data-start=\"2020\" data-end=\"2897\">\u003Cli data-start=\"2020\" data-end=\"2293\">\u003Cp data-start=\"2022\" data-end=\"2293\">GitHub Copilot: A tool developed by GitHub in collaboration with OpenAI, Copilot provides AI-powered auto-completions based on your current coding context. For example, when starting to write a \u003Ccode data-start=\"2224\" data-end=\"2229\">for\u003C\u002Fcode> loop, Copilot will immediately suggest the full loop structure.\u003C\u002Fp>\u003C\u002Fli>\u003Cli data-start=\"2295\" data-end=\"2475\">\u003Cp data-start=\"2297\" data-end=\"2475\">DeepCode: An AI tool that uses machine learning to scan your codebase for potential errors. It reviews multiple repositories to detect issues and recommends improvements.\u003C\u002Fp>\u003C\u002Fli>\u003Cli data-start=\"2477\" data-end=\"2709\">\u003Cp data-start=\"2479\" data-end=\"2709\">Tabnine: An AI-based auto-completion tool that provides intelligent code suggestions as you type. For example, if you're writing JavaScript, Tabnine can predict and complete function calls relevant to your current context.\u003C\u002Fp>\u003C\u002Fli>\u003Cli data-start=\"2711\" data-end=\"2897\">\u003Cp data-start=\"2713\" data-end=\"2897\">Kite: An AI tool that provides auto-completion for Python and JavaScript, offering accurate function suggestions and inline documentation to help you write better code.\u003C\u002Fp>\u003C\u002Fli>\u003C\u002Ful>\u003Ch4 data-start=\"2899\" data-end=\"2945\">Benefits of Using AI in Code Development:\u003C\u002Fh4>\u003Cul data-start=\"2947\" data-end=\"3698\">\u003Cli data-start=\"2947\" data-end=\"3158\">\u003Cp data-start=\"2949\" data-end=\"3158\">Faster Code Writing: AI helps speed up the coding process, especially through auto-completion, by suggesting code snippets without the need to type everything manually—saving valuable development time.\u003C\u002Fp>\u003C\u002Fli>\u003Cli data-start=\"3160\" data-end=\"3325\">\u003Cp data-start=\"3162\" data-end=\"3325\">Reduced Code Errors: Tools like GitHub Copilot and DeepCode can identify and suggest fixes for code issues quickly, making your code more reliable.\u003C\u002Fp>\u003C\u002Fli>\u003Cli data-start=\"3327\" data-end=\"3487\">\u003Cp data-start=\"3329\" data-end=\"3487\">Learning from Existing Code: AI can learn from the code you write and suggest optimized patterns based on previously analyzed codebases and use cases.\u003C\u002Fp>\u003C\u002Fli>\u003Cli data-start=\"3489\" data-end=\"3698\">\u003Cp data-start=\"3491\" data-end=\"3698\">Suggesting the Most Efficient Code: AI recommends the best way to structure and optimize your code—for example, through the use of design patterns, clean code organization, and high-efficiency logic.\u003C\u002Fp>\u003C\u002Fli>\u003C\u002Ful>\u003Cfigure class=\"image image_resized\" style=\"width:75%;\">\u003Cimg style=\"aspect-ratio:1920\u002F1920;\" src=\"https:\u002F\u002Fimagedelivery.net\u002Fg5Z0xlCQah-oO61sLqaEUA\u002FTemplate_Blog_2025_05_23_T160634_852_11zon_d2ee0e704c\u002Ftwsme\" alt=\"Benefits of Using AI in Code Development\" width=\"1920\" height=\"1920\">\u003C\u002Ffigure>\u003Ch2>2. Using AI in Project Testing\u003C\u002Fh2>\u003Cp data-start=\"173\" data-end=\"693\">Project testing is a critical step in software development to ensure that applications work as expected and are free of errors. Artificial Intelligence (AI) plays an increasingly important role in enhancing the speed, accuracy, and efficiency of the testing process. AI allows testing to be conducted across multiple levels effectively—reducing human error and accelerating test cycles. Using AI in project testing leads to more precise and faster results without relying solely on time-consuming manual testing.\u003C\u002Fp>\u003Ch4 data-start=\"695\" data-end=\"740\">Benefits of Using AI in Project Testing:\u003C\u002Fh4>\u003Cul data-start=\"742\" data-end=\"2418\">\u003Cli data-start=\"742\" data-end=\"1113\">\u003Cp data-start=\"744\" data-end=\"1113\">Automated Testing: AI-powered tools like Test.ai and Applitools can automatically test applications and instantly detect issues during execution—eliminating the need for manual testing. AI can simulate various user behaviors, test on different devices and operating systems, check application performance under load, and identify potential crash points.\u003C\u002Fp>\u003C\u002Fli>\u003Cli data-start=\"1115\" data-end=\"1433\">\u003Cp data-start=\"1117\" data-end=\"1433\">UI and UX Testing: AI enables automated testing of User Interface (UI) and User Experience (UX) in various scenarios, eliminating repetitive manual efforts. Tools like Applitools use Visual AI to detect UI changes and ensure the application displays correctly across multiple screens and devices.\u003C\u002Fp>\u003C\u002Fli>\u003Cli data-start=\"1435\" data-end=\"1790\">\u003Cp data-start=\"1437\" data-end=\"1790\">Cross-Platform Testing: AI-powered tools can perform testing across different platforms and browsers efficiently. For example, testing applications on Android, iOS, Windows, Linux, and macOS to verify correct functionality. AI supports cross-browser and cross-device testing, ensuring consistent performance across all user environments.\u003C\u002Fp>\u003C\u002Fli>\u003Cli data-start=\"1792\" data-end=\"2088\">\u003Cp data-start=\"1794\" data-end=\"2088\">Bug Detection: AI helps detect bugs that may be missed during manual testing, especially in conditions that aren’t often tested, such as poor network connections or low-spec devices. AI can analyze hidden issues and detect errors caused by incomplete test coverage or complex scenarios.\u003C\u002Fp>\u003C\u002Fli>\u003Cli data-start=\"2090\" data-end=\"2418\">\u003Cp data-start=\"2092\" data-end=\"2418\">Performance Testing: AI can simulate high user loads and run performance tests under various conditions. Without repeating manual tests, AI enables stress testing, load testing, and scalability testing to evaluate the application's performance under pressure and predict potential issues in real-world use.\u003C\u002Fp>\u003C\u002Fli>\u003C\u002Ful>\u003Ch4 data-start=\"2420\" data-end=\"2458\">Key AI Tools for Project Testing:\u003C\u002Fh4>\u003Cul data-start=\"2460\" data-end=\"3278\">\u003Cli data-start=\"2460\" data-end=\"2683\">\u003Cp data-start=\"2462\" data-end=\"2683\">Test.ai: An AI tool for testing mobile and web apps that performs automated UI testing and detects UI\u002FUX issues that traditional tools might miss. Test.ai can simulate various scenarios without manual testing.\u003C\u002Fp>\u003C\u002Fli>\u003Cli data-start=\"2685\" data-end=\"2845\">\u003Cp data-start=\"2687\" data-end=\"2845\">Applitools: A Visual AI tool that performs visual testing to detect errors in an application's UI across different devices and screen resolutions.\u003C\u002Fp>\u003C\u002Fli>\u003Cli data-start=\"2847\" data-end=\"3086\">\u003Cp data-start=\"2849\" data-end=\"3086\">Selenium + AI Integration: Selenium is a widely used web testing tool that can be enhanced with AI to improve UI testing efficiency. AI can learn user interaction patterns and test application functionality in various situations.\u003C\u002Fp>\u003C\u002Fli>\u003Cli data-start=\"3088\" data-end=\"3278\">\u003Cp data-start=\"3090\" data-end=\"3278\">Katalon Studio: An automation testing tool for API, Web, Mobile, and Desktop applications. It can integrate with AI to detect errors and technical issues during test execution.\u003C\u002Fp>\u003C\u002Fli>\u003C\u002Ful>\u003Ch4 data-start=\"3280\" data-end=\"3331\">How to Get Started with AI in Project Testing:\u003C\u002Fh4>\u003Col data-start=\"3333\" data-end=\"3953\">\u003Cli data-start=\"3333\" data-end=\"3492\">\u003Cp data-start=\"3336\" data-end=\"3492\">Install AI-Powered Testing Tools: Use tools like Test.ai, Applitools, or Katalon Studio and configure them based on your project needs.\u003C\u002Fp>\u003C\u002Fli>\u003Cli data-start=\"3494\" data-end=\"3634\">\u003Cp data-start=\"3497\" data-end=\"3634\">Define Test Scenarios: Choose specific scenarios or conditions to test, such as UI testing, API testing, or performance testing.\u003C\u002Fp>\u003C\u002Fli>\u003Cli data-start=\"3636\" data-end=\"3794\">\u003Cp data-start=\"3639\" data-end=\"3794\">Configure AI Settings for Testing: Set up tools to test across different browsers, devices, and environments to simulate diverse usage conditions.\u003C\u002Fp>\u003C\u002Fli>\u003Cli data-start=\"3796\" data-end=\"3953\">\u003Cp data-start=\"3799\" data-end=\"3953\">Start Testing: Allow the AI-powered tools to execute automated tests and analyze the results to detect issues and potential errors in the system.\u003C\u002Fp>\u003C\u002Fli>\u003C\u002Fol>\u003Ch2>3. AI Tools for Code Development and Project Testing\u003C\u002Fh2>\u003Cp data-start=\"221\" data-end=\"521\">AI-powered tools for code development and project testing help increase speed, accuracy, and overall efficiency in modern software development. By leveraging AI, developers can accelerate project workflows, reduce errors, and create a more structured and seamless development and testing process. Today, we’ll cover some of the most popular AI tools that support project development and testing, allowing you to work more effectively without spending excessive time on manual tasks.\u003C\u002Fp>\u003Cfigure class=\"image image_resized\" style=\"width:75%;\">\u003Cimg style=\"aspect-ratio:1920\u002F1920;\" src=\"https:\u002F\u002Fimagedelivery.net\u002Fg5Z0xlCQah-oO61sLqaEUA\u002FTemplate_Blog_2025_05_23_T160714_182_11zon_87a47c9ee8\u002Ftwsme\" alt=\"AI Tools for Code Development and Project Testing\" width=\"1920\" height=\"1920\">\u003C\u002Ffigure>\u003Ch4 data-start=\"719\" data-end=\"766\">1. GitHub Copilot – AI Tool for Coding\u003C\u002Fh4>\u003Cp data-start=\"768\" data-end=\"1029\">GitHub Copilot is an AI tool that provides code suggestions and completions for developers in Visual Studio Code and other supported editors. It learns from code written by developers around the world and recommends relevant functions to assist programmers.\u003C\u002Fp>\u003Cp data-start=\"1031\" data-end=\"1066\">Key Features of GitHub Copilot:\u003C\u002Fp>\u003Cul data-start=\"1068\" data-end=\"1453\">\u003Cli data-start=\"1068\" data-end=\"1262\">\u003Cp data-start=\"1070\" data-end=\"1262\">Auto code suggestions: The AI suggests code as you type, without needing to type everything manually. For example, typing \u003Ccode data-start=\"1196\" data-end=\"1209\">console.log\u003C\u002Fcode> will prompt Copilot to complete the command for you.\u003C\u002Fp>\u003C\u002Fli>\u003Cli data-start=\"1264\" data-end=\"1453\">\u003Cp data-start=\"1266\" data-end=\"1453\">AI-generated code from descriptions: You can type a natural language instruction like “create a function to connect to a database,” and GitHub Copilot will generate the relevant code.\u003C\u002Fp>\u003C\u002Fli>\u003C\u002Ful>\u003Cp data-start=\"1455\" data-end=\"1632\">GitHub Copilot helps programmers—especially beginners—write code faster and more effectively, even if they are not yet familiar with certain functions or programming structures.\u003C\u002Fp>\u003Ch4 data-start=\"1639\" data-end=\"1686\">2. Test.ai – AI Tool for UI\u002FUX Testing\u003C\u002Fh4>\u003Cp data-start=\"1688\" data-end=\"1897\">Test.ai uses AI to test the UI and UX of mobile and web applications. It automates the testing of visual components without the need for manual intervention, making the process more accurate and efficient.\u003C\u002Fp>\u003Cp data-start=\"1899\" data-end=\"1927\">Key Features of Test.ai:\u003C\u002Fp>\u003Cul data-start=\"1929\" data-end=\"2259\">\u003Cli data-start=\"1929\" data-end=\"2024\">\u003Cp data-start=\"1931\" data-end=\"2024\">Automated visual testing: Detects UI rendering issues automatically and reports problems.\u003C\u002Fp>\u003C\u002Fli>\u003Cli data-start=\"2026\" data-end=\"2159\">\u003Cp data-start=\"2028\" data-end=\"2159\">Learning capability: Uses machine learning to study user behavior and prioritize important UI elements that might cause errors.\u003C\u002Fp>\u003C\u002Fli>\u003Cli data-start=\"2161\" data-end=\"2259\">\u003Cp data-start=\"2163\" data-end=\"2259\">Cross-platform support: Supports testing for both Android and iOS apps in various scenarios.\u003C\u002Fp>\u003C\u002Fli>\u003C\u002Ful>\u003Cp data-start=\"2261\" data-end=\"2343\">Test.ai enables smooth and effective UI\u002FUX testing while minimizing manual errors.\u003C\u002Fp>\u003Ch4 data-start=\"2350\" data-end=\"2423\">3. Selenium with AI Integration – Automated Testing Tool with AI\u003C\u002Fh4>\u003Cp data-start=\"2425\" data-end=\"2597\">Selenium is a popular tool for web application testing. With AI integration, Selenium can conduct thorough UI and functionality tests without relying on manual testing.\u003C\u002Fp>\u003Cp data-start=\"2599\" data-end=\"2640\">Key Features of AI-Enhanced Selenium:\u003C\u002Fp>\u003Cul data-start=\"2642\" data-end=\"2983\">\u003Cli data-start=\"2642\" data-end=\"2777\">\u003Cp data-start=\"2644\" data-end=\"2777\">Cross-browser testing: Ensures your application works across different browsers using AI to evaluate performance and consistency.\u003C\u002Fp>\u003C\u002Fli>\u003Cli data-start=\"2779\" data-end=\"2888\">\u003Cp data-start=\"2781\" data-end=\"2888\">AI-powered test scripts: Generates and refines test scripts automatically to handle multiple scenarios.\u003C\u002Fp>\u003C\u002Fli>\u003Cli data-start=\"2890\" data-end=\"2983\">\u003Cp data-start=\"2892\" data-end=\"2983\">User behavior learning: AI studies user interactions to create relevant test scenarios.\u003C\u002Fp>\u003C\u002Fli>\u003C\u002Ful>\u003Ch4 data-start=\"2990\" data-end=\"3050\">4. Katalon Studio – AI Tool for Web and App Testing\u003C\u002Fh4>\u003Cp data-start=\"3052\" data-end=\"3231\">Katalon Studio is a tool for testing both web and mobile applications without complex setup. With AI features, it efficiently tests APIs, web interfaces, and mobile platforms.\u003C\u002Fp>\u003Cp data-start=\"3233\" data-end=\"3268\">Key Features of Katalon Studio:\u003C\u002Fp>\u003Cul data-start=\"3270\" data-end=\"3615\">\u003Cli data-start=\"3270\" data-end=\"3406\">\u003Cp data-start=\"3272\" data-end=\"3406\">API and web testing: Supports API, web, and mobile testing, with AI assisting in identifying code issues and performance problems.\u003C\u002Fp>\u003C\u002Fli>\u003Cli data-start=\"3408\" data-end=\"3526\">\u003Cp data-start=\"3410\" data-end=\"3526\">Automated test generation: Automatically creates and runs tests for projects that undergo frequent code changes.\u003C\u002Fp>\u003C\u002Fli>\u003Cli data-start=\"3528\" data-end=\"3615\">\u003Cp data-start=\"3530\" data-end=\"3615\">Community support: Has an active community to help with usage and best practices.\u003C\u002Fp>\u003C\u002Fli>\u003C\u002Ful>\u003Ch4 data-start=\"3622\" data-end=\"3672\">5. Applitools – AI-Powered Visual Testing\u003C\u002Fh4>\u003Cp data-start=\"3674\" data-end=\"3824\">Applitools is an AI tool for visual testing that checks whether an application’s UI renders correctly across various environments and devices.\u003C\u002Fp>\u003Cp data-start=\"3826\" data-end=\"3857\">Key Features of Applitools:\u003C\u002Fp>\u003Cul data-start=\"3859\" data-end=\"4228\">\u003Cli data-start=\"3859\" data-end=\"3971\">\u003Cp data-start=\"3861\" data-end=\"3971\">Visual AI: Uses AI to detect UI changes and verify visual correctness across screen sizes and resolutions.\u003C\u002Fp>\u003C\u002Fli>\u003Cli data-start=\"3973\" data-end=\"4100\">\u003Cp data-start=\"3975\" data-end=\"4100\">Cross-device testing: Supports testing across a wide range of devices and operating systems, including multiple browsers.\u003C\u002Fp>\u003C\u002Fli>\u003Cli data-start=\"4102\" data-end=\"4228\">\u003Cp data-start=\"4104\" data-end=\"4228\">Result snapshot recording: Stores visual snapshots of each test to help identify UI regressions and visual bugs quickly.\u003C\u002Fp>\u003C\u002Fli>\u003C\u002Ful>\u003Chr>\u003Ch2>Summary\u003C\u002Fh2>\u003Cp data-start=\"75\" data-end=\"468\">Using AI tools for code development and project testing has become a game-changing technology in today’s software industry. These tools enhance speed, accuracy, and efficiency throughout the development process. Popular AI tools simplify project workflows and improve quality—especially for beginner programmers looking for powerful tools to aid in development and testing. AI-powered development and testing bring smoothness and structure to your workflow, reducing complexity and enabling developers to build high-quality code quickly and reliably.\u003C\u002Fp>\u003Cp> \u003C\u002Fp>\u003Cp data-start=\"1888\" data-end=\"2187\">If you're looking for a programming course in Bangkok that helps you master AI tools for development and testing,\u003Cbr>Enroll with Superdev School today!\u003Cbr>We offer both one-on-one and online courses, personalized to fit your learning style and goals.\u003Cbr>👉 Enroll now at \u003Ca target=\"_blank\" rel=\"noopener noreferrer\" href=\"https:\u002F\u002Fwww.facebook.com\u002Fsuperdev.school.th?locale=th_TH\">Superdev School\u003C\u002Fa>\u003C\u002Fp>","ai_1_q6co8049s5.webp","https:\u002F\u002Ftwsme-r2.tumwebsme.com\u002Fsclblg987654321\u002Fp2ey6egnzxkmhor\u002Fai_1_q6co8049s5.webp","2026-03-04 08:49:27.449Z","",{"keywords":15,"locale":43,"school_blog":53},[16,23,28,33,38],{"collectionId":17,"collectionName":18,"created":19,"created_by":13,"id":20,"name":21,"updated":22,"updated_by":13},"sclkey987654321","school_keywords","2026-03-04 08:49:26.033Z","xlf3yxdmg3un5cu","tools for testing projects","2026-04-10 16:14:05.508Z",{"collectionId":17,"collectionName":18,"created":24,"created_by":13,"id":25,"name":26,"updated":27,"updated_by":13},"2026-03-04 08:49:26.594Z","535q7zowr949rtj","AI in programming","2026-04-10 16:14:05.717Z",{"collectionId":17,"collectionName":18,"created":29,"created_by":13,"id":30,"name":31,"updated":32,"updated_by":13},"2026-03-04 08:49:26.809Z","7dumzy90ve7sqia","project testing","2026-04-10 16:14:05.888Z",{"collectionId":17,"collectionName":18,"created":34,"created_by":13,"id":35,"name":36,"updated":37,"updated_by":13},"2026-03-04 08:47:50.231Z","x49fmx5msruz70w","code development","2026-04-10 16:13:35.075Z",{"collectionId":17,"collectionName":18,"created":39,"created_by":13,"id":40,"name":41,"updated":42,"updated_by":13},"2026-03-04 08:49:27.117Z","nwhkwkveoaezbby","AI tools","2026-04-10 16:14:06.020Z",{"code":44,"collectionId":45,"collectionName":46,"created":47,"flag":48,"id":49,"is_default":50,"label":51,"updated":52},"en","pbc_1989393366","locales","2026-01-22 11:00:02.726Z","twemoji:flag-united-states","qv9c1llfov2d88z",false,"English","2026-04-10 15:42:46.825Z",{"category":54,"collectionId":55,"collectionName":56,"created":13,"expand":57,"id":71,"slug":72,"updated":73,"views":74},"spm4l1k5bgmhmmt","pbc_2105096300","school_blogs",{"category":58},{"blogIds":59,"collectionId":60,"collectionName":61,"created":62,"created_by":13,"id":54,"image":63,"image_alt":13,"image_path":64,"label":65,"name":66,"priority":67,"publish_at":68,"scheduled_at":13,"status":69,"updated":70,"updated_by":13},[],"sclcatblg987654321","school_category_blogs","2026-03-04 08:31:18.590Z","50hyjr6os45_ayazwr5gq7.png","https:\u002F\u002Ftwsme-r2.tumwebsme.com\u002Fsclcatblg987654321\u002Fspm4l1k5bgmhmmt\u002F50hyjr6os45_ayazwr5gq7.png",{"en":66,"th":66},"Knowledge",0,"2026-03-18 02:25:41.222Z","published","2026-04-25 02:32:14.497Z","2ivf2r4edncngru","using-ai-tools-in-code-development-and-project-testing","2026-05-12 01:28:55.046Z",232,"p2ey6egnzxkmhor",[20,25,30,35,40],"2025-06-06 02:23:31.666Z","Learn how to leverage AI tools in code development and project testing to enhance programming speed and efficiency—while streamlining project testing processes.","2026-04-22 07:10:22.869Z",1,{"th":72,"en":72}]