Many developers are questioning their future roles as AI and LLMs reshape the tech landscape. Developers who see AI as a threat are discovering how these tools can enhance their capabilities and secure their position in the industry. AI is becoming an invaluable resource for developers, from automating routine tasks to solving complex problems more efficiently.
Developers who are learning how to effectively leverage AI tools are making themselves more valuable by combining human creativity and expertise with AI-powered productivity. Developers can focus on high-level problem-solving and innovation with the help of these tools, which are increasingly in demand.
GitHub Copilot
GitHub Copilot is integrated with your editor and, like Cursor, allows you to choose your preferred AI agent. Additionally, there is a extensions feature that enables the integration of external devtools such as Docker, Sentry, or GitBook into the Copilot chat.
Pros
It features a chatbot within the developer’s environment, which allows for questions, suggestions, debugging, and natural language queries.
GitHub Copilot offers code suggestions that complete lines or complete functions based on comments in your file.
The tool is compatible with popular IDEs like Visual Studio, Neovim, Visual Studio Code, and JetBrains, and supports a variety of programming languages, such as TypeScript, Golang, Python, and JavaScript.
Users can easily cycle through multiple auto-complete suggestions, allowing them to explore different options and select the most suitable recommendation for their code.
Cons
The tool’s ability to generate incorrect or inefficient code can be a challenge, especially for developers who are less experienced and have trouble identifying and rectifying errors.
Advanced features such as GitHub Codespaces access and assigning multiple users or teams for pull request reviews are only available in the paid Team Plan. Individual developers or small teams on free plans are restricted from accessing premium collaboration tools due to this limitation.
GitHub Copilot’s code generation is based on learned patterns, and it could inadvertently produce code segments that are similar or identical, causing code duplication across projects.
It is crucial to maintain test coverage for larger codebases. GitHub Copilot may not have the capability to generate an adequate number of test cases, which may make it harder to identify and debug issues and ensure overall code quality.
Bolt
Bolt is a coding tool that is built on StackBlitz WebContainers and uses AI. It enables you to describe full-stack apps in plain English and generates, runs, and deploys them all within the browser without any need for local tooling.
Pros
The use of natural language input is used to construct frontend components, backend endpoints, and project structure.
A live environment can be used to quickly validate product ideas, spin up MVPs, or teach app architecture.
Using the browser, it handles installs, terminal commands, code editing, and deployments without any need for local setup.
Its built-in support allows you to deploy Netlify, setup Supabase backend, integrate Stripe, and collaborate on GitHub.
Cons
Designed for small apps and demonstrations, but not suitable for large monorepos due to lack of performance and structure.
The Bolt interface is the only place it can operate, without any support for external IDEs like VS Code or JetBrains.
Despite being maturing, there are still occasional prompt misfires or UI quirks that can occur during complex interactions.
AskCodi
AskCodi was included on this list because it is an AI coding assistant that is both practical and reliable and simplifies the coding process. This tool has been useful to me in both speeding up workflows and tackling coding challenges. AskCodi is unique in its versatility and ease of use. It’s not just about producing code; it also helps you learn, debug, and write better code with minimal effort, all while integrating seamlessly into popular development environments.
Pros
By answering coding-related queries using natural language, it makes it easier to understand new concepts or troubleshoot problems.
Visual Studio Code, PyCharm, and IntelliJ IDEA are supported IDEs for direct use within your development environment.
AskCodi is capable of producing code in various programming languages, such as Python, Java, TypeScript, Rust, Ruby, Kotlin, and more.
By analyzing your code and providing suggestions for improvement or fixing it, it helps to avoid mistakes and save time.
Cons
The tool’s use of open-source code for training may restrict its capability to address all use cases or scenarios.
It can be challenging to structure questions effectively, which can lead to inaccurate or incomplete results.
For some users, the monthly subscription that is required for full access to features may be costly.
Replit
Replit is a coding platform that offers AI-powered help and an interactive development environment. I included it in this list because it provides a balance of coding support and learning features that aid developers in writing and comprehending code better.
Pros
Code snippets are broken down with clear explanations and meaningful comments are generated for better documentation
Provides a platform for learning while coding, making it valuable for both new and experienced developers.
Real-time code suggestions expedite the coding process and ensure consistent code quality.
Identifies coding errors and provides guidance for fixing them, improving code accuracy.
Cons
Replit, an online tool, necessitates a steady internet connection, which can be a hindrance in offline situations.
Cursor
Cursor is a code editor that is powerful and has AI features as its core. It’s basically a fork of VS Code that incorporates various LLMs to provide intelligent code completion, debugging assistance, and chat-based help without leaving your editor. The main advantages of it are that it can explain complex code, generate implementations from comments, and refactor existing code through natural language instructions.
Qodo
Qodo is a software tool that focuses on AI Coding and covers the entire SDLC from code generation and automated test authoring to intelligent AI code reviews in the PR. Integrating with VS Code, JetBrains, terminal, and CI pipelines, it combines developer productivity with SOC 2-level enterprise safeguards. The codebase awareness of its agents (Gen, Cover, and Merge) is achieved through RAG-based context indexing.
Pros
Offers tailored suggestions, which include docstrings, exception handling, and best practices, which directly enhance code quality. Aids developers in maintaining code that is cleaner and easier to maintain.
Qodo includes purpose-built agents Gen, Cover, and Merge for generating code and testing, as well as for improving test coverage, PR summaries, risk analysis, and automated code review.
Defines source code or snippets with specific descriptions. Provides insights and sample usage scenarios that enhance code comprehension for both junior and senior developers.
Covering all possible code behaviors ensures thorough testing. Produces test cases and seamlessly applies related modifications to the source code.
Generates accurate and reliable unit tests that save time and effort. Makes testing easier, particularly for large and complex codebases.
Git integration facilitates teamwork by allowing code sharing and reviews. Promotes efficient workflows and high-quality code overall.
Provides support for programming languages such as Python, JavaScript, and TypeScript. Suitable for top-notch IDEs, such as VSCode, WebStorm, IntelliJ IDEA, CLion, PyCharm, and JetBrains.
Cons
A paid plan is necessary to access advanced features like SOC2 compliance and static code analysis in Qodo Merge Pro. This could be a hindrance for smaller teams or individual developers.
Conclusion
As technology develops, AI coding assistants are becoming more important in software development. These AI tools, with their ability to keep learning and improving, have the potential to completely transform the way developers code, aiding them in innovating, collaboration, and writing better-quality code. Developers can easily tackle coding challenges, improve their skills, and create high-quality software in the fast-changing digital world by embracing the power of these tools.
