Large Language Models (LLMs) are a family of generative models that can understand natural language and produce human-like responses. Modern iterations of LLMs have been trained to accomplish various tasks from writing an email, proposing an outline of a paper, and writing code. Naturally, it gave rise to LLM-based tools, especially for developers as early adopters of the copilot-style of doing things. Now, developers can save time with more advanced autocompletion, spend less time hunting through Stack Overflow to debug errors, and stop struggling to remember the right terminal commands — all thanks to LLM-based tools like Copilot, AI-enhanced IDEs, and AI-enhanced Terminal. Retrieval Augmented Generation (RAG) has played a major role in the growth and adoption of LLM-based applications. It allows GenAI applications to gain access to new, up-to-date information not seen during model training, allowing them to counter hallucinations and compose an information-rich response. For coding applications, RAG is used to retrieve additional context for a software application and generate relevant responses. It links the LLM to the user codebase, technical documentation, and online repositories to retrieve updated information regarding the input query. The added information allows the LLM to stay updated with code updates, design patterns, and development standards and prevents it from hallucinating. This is an honest review of 5 AI tools that truly make developers' lives easier, helping them feel more confident and satisfied in their work. Long story short: GitHub Copilot is a go-to solution for trying AI developer tools. Cursor IDE is for an AI-centric approach to code development. Tabnine for a more privacy-oriented approach. Warp for a modern terminal built around AI tools. Replit Agent for handling entire application architectures (more like a junior full-stack developer, not just a code-suggestion tool). So let’s dive in and discuss these popular LLM apps for developers (based purely on experience and without any bias) 🧐 1. Github Copilot Github Copilot is powered by OpenAI Codex and is purpose-built for coding-related tasks. The model is trained on millions of public Github repositories and other codebases available on the internet. Github Copilot is a coding assistant that can help write code, develop algorithms, solve bugs, and simplify pull requests by keeping track of your changes. Copilot also utilizes RAG to access code in your application codebase and use it as context to improve suggestions. While earlier versions of Copilot only considered code in the currently active file, later iterations use neighboring tabs andfill-in-the-middle (FIM) paradigm to create a wider context. The wider context allows the copilot to provide suggestions based on the existing application architecture. 85% of developers felt more confident in their code quality when authoring code with GitHub Copilot The tool was developed to improve the productivity of coding-related tasks and has gained great popularity among developers. A survey posted on Github concluded that 85% of developers felt more confident in their code quality when authoring code with GitHub Copilot. Moreover, it also revealed that code reviews using Github Copilot Chat were 15% faster than manual reviews. Another research study by Github aimed to evaluate productivity using the SPACE framework. Between 60-75% of users reported improved work satisfaction, focus, and stress levels. Moreover, the study also conducted a coding assessment, which copilot users completed in 55% less time than non-users. GitHub offers Copilot integrations with popular IDEs like VS Code and JetBrains. The copilot extensions allow users to generate code by specifying prompts or receive real-time suggestions based on their existing codebase. Users can also train a custom LLM, tailored to their writing style and adopt all best practices, by specifying a few personal repositories and fine-tuning the model. The easy integration and amazing benefits have made copilot the preference of 55% of developers and gained the trust of over 50,000 businesses. So if you or you company still haven’t used it its probably a time to start doing so. Dont expect its going to replace developers or any stuff like this, but it definitely will save you some time 😉 2. Cursor IDE The cursor IDE is an AI-powered code editor integrated with a GPT-backed LLM called the Copilot++. The IDE is filled with amazing features to help developers with everyday tedious tasks. Some of its key features include: Code Generation: Copilot++ predicts entire code blocks based on recent changes and project workflow. Smart Rewrites: The IDE auto-fixes syntax and formatting mistakes as developers code. This saves programmers from frustrating and redundant rewrites. Cursor Prediction: Cursor recognizes developers' work patterns and predicts where the cursor would need to be next. Developers can press the tab button to shift to the predicted location automatically. Each feature improves developers' productivity and enables robust and quality development. Cursor also includes a chatbot that understands the entire codebase as context. Developers can query the bot by referencing the codebase and ask questions about the implementations and suggestions for improvements. The chatbot is integrated with popular models like GPT-4o, GPT-4, and Claude-3.5-Sonnet. It also includes specialized long-context models like GPT-4o-128k for working with lengthy codebases. The AI-powered features boost productivity and have gained the trust of top organizations like Samsung, OpenAI, and Midjourney. Moreover, Cursor IDE is a fork of the popular VS Code IDE and has a similar intuitive UI and configurations. It also allows VS Code users to migrate their extensions, settings, and keybindings easily. There is a constant twitter (X) battle which one Copilot or Cursor is better, and both sides have strong opinion. For example, Andrej Karpathy recently became a fan of the second one. 3. Tabnine Tabnine is an AI coding assistant similar to GitHub Copilot. It is built upon Tabnines proprietary LLM and offers automated code completions and explanations. The assistant also includes a chat option, allowing developers to explain requirements in natural language and generate code snippets. Users can use the Tabnine Protected Chat model or an external LLM like Mistral or GPT-4o. Moreover, Tabnine boasts unique features that distinguish it from Github Copilot. One of its primary features is the focus on data privacy and IP protection. Tabnine's protected model is trained exclusively on licensed code, and unlike Copilot, Tabnine is also transparent about data used for training and can share it with customers under an NDA. Lastly, Tabnine can connect with any Git-based repository, supports every major IDE, and provides cloud environments with GDPR and SOC-2 compliance. Tabnine’s productivity features and focus on data security have gained massive popularity and more than 1 Million monthly users use the tool, but definetly less popular than the previous two. 4. Warp Warp is a terminal for CLI (Command Line Interface) tasks. It provides an IDE-like interface with flexible cursor movement and multi-line edit support. It also has smart command completion that recognizes what the developer is typing and offers suggestions for time-saving. The most interesting feature of the Warp is Warp AI. The terminal is integrated with ChatGPT, and developers can chat with the LLM and ask for terminal command suggestions, for example, the command to start a docker container. Users can explain their desired action in natural language, and the LLM will suggest the appropriate command for it. Warp also introduces Agent Mode, which allows users to navigate the terminal entirely in natural language. Users can explain their desired action in language one-by-one, and warp will execute the relevant command, use the output to guide the user, and correct itself in case of an error. Moreover, Warp AI also understands errors displayed on the terminal and can offer explanations and resolutions. In terms of data privacy, Warp has a no-retention policy. Any commands or chats generated by the user are not used for training and are not retained either by Warp or OpenAI. Overall, the Warp is a massive upgrade over the conventional terminal and provides various intuitive features and benefits. 5. Replit Agent Replit Agent has been making waves recently, particularly on Twitter (X) and in tech circles. Many developers are buzzing about how it’s not just another coding assistant like GitHub Copilot, but more of a virtual full-stack developer. What makes it stand out is its ability to handle entire application architectures. Whether it's setting up environments, writing code, or deploying apps, Replit Agent takes on a role similar to that of a junior software engineer, not just a code-suggestion tool. The agent is designed to work with the Replit platform and is built directly into the Replit IDE. It is not just a code generator but understands the users requirements and builds the entire infrastructure required to deploy an application. It offers a natural language interface where users can describe their requirements and have the Replit agent spin up a fully functioning product. Users can choose to add new functionality to the application using prompts like “Add a search bar on the top”. The agent also understands the product requirements and asks follow up questions for clarity on advanced functionalities. It is strongly integrated with the Replit platform and suggests deployment options, including reserved VMs, autoscaling, and static sites. Replit agent is currently only available via a limited early access program and is proclaimed as an experimental product so must be used with caution. But even though it is prone to some limitations, like handling more complex or backend-heavy applications, it’s a big step towards an AI-driven development trend. LLM applications aim to improve productivity by automating several corporate and development-related tasks. They improve the developer's work experience and productivity and allow them to deliver quality products in a short time. Large Language Models (LLMs) are a family of generative models that can understand natural language and produce human-like responses. Modern iterations of LLMs have been trained to accomplish various tasks from writing an email, proposing an outline of a paper, and writing code. Naturally, it gave rise to LLM-based tools, especially for developers as early adopters of the copilot-style of doing things. Now, developers can save time with more advanced autocompletion, spend less time hunting through Stack Overflow to debug errors, and stop struggling to remember the right terminal commands — all thanks to LLM-based tools like Copilot, AI-enhanced IDEs, and AI-enhanced Terminal. Large Language Models (LLMs) Retrieval Augmented Generation (RAG) has played a major role in the growth and adoption of LLM-based applications. It allows GenAI applications to gain access to new, up-to-date information not seen during model training, allowing them to counter hallucinations and compose an information-rich response. Retrieval Augmented Generation (RAG) For coding applications, RAG is used to retrieve additional context for a software application and generate relevant responses. It links the LLM to the user codebase, technical documentation, and online repositories to retrieve updated information regarding the input query. The added information allows the LLM to stay updated with code updates, design patterns, and development standards and prevents it from hallucinating. This is an honest review of 5 AI tools that truly make developers' lives easier, helping them feel more confident and satisfied in their work. honest Long story short: GitHub Copilot is a go-to solution for trying AI developer tools. Cursor IDE is for an AI-centric approach to code development. Tabnine for a more privacy-oriented approach. Warp for a modern terminal built around AI tools. Replit Agent for handling entire application architectures (more like a junior full-stack developer, not just a code-suggestion tool). GitHub Copilot is a go-to solution for trying AI developer tools. GitHub Copilot Cursor IDE is for an AI-centric approach to code development. Cursor IDE Tabnine for a more privacy-oriented approach. Tabnine Warp for a modern terminal built around AI tools. Warp Replit Agent for handling entire application architectures (more like a junior full-stack developer, not just a code-suggestion tool). Replit Agent So let’s dive in and discuss these popular LLM apps for developers (based purely on experience and without any bias) 🧐 So let’s dive in and discuss these popular LLM apps for developers (based purely on experience and without any bias) 🧐 1. Github Copilot 1. Github Copilot Github Copilot is powered by OpenAI Codex and is purpose-built for coding-related tasks. The model is trained on millions of public Github repositories and other codebases available on the internet. Github Copilot is a coding assistant that can help write code, develop algorithms, solve bugs, and simplify pull requests by keeping track of your changes. Github Copilot Github Copilot Github Copilot OpenAI Codex OpenAI Codex OpenAI Codex Copilot also utilizes RAG to access code in your application codebase and use it as context to improve suggestions. While earlier versions of Copilot only considered code in the currently active file, later iterations use neighboring tabs and fill-in-the-middle (FIM) paradigm to create a wider context. The wider context allows the copilot to provide suggestions based on the existing application architecture. fill-in-the-middle fill-in-the-middle 85% of developers felt more confident in their code quality when authoring code with GitHub Copilot 85% of developers felt more confident in their code quality when authoring code with GitHub Copilot The tool was developed to improve the productivity of coding-related tasks and has gained great popularity among developers. A survey posted on Github concluded that 85% of developers felt more confident in their code quality when authoring code with GitHub Copilot. Moreover, it also revealed that code reviews using Github Copilot Chat were 15% faster than manual reviews. Another research study by Github aimed to evaluate productivity using the SPACE framework. Between 60-75% of users reported improved work satisfaction, focus, and stress levels. Moreover, the study also conducted a coding assessment, which copilot users completed in 55% less time than non-users. survey survey survey research study research study research study GitHub offers Copilot integrations with popular IDEs like VS Code and JetBrains. The copilot extensions allow users to generate code by specifying prompts or receive real-time suggestions based on their existing codebase. Users can also train a custom LLM, tailored to their writing style and adopt all best practices, by specifying a few personal repositories and fine-tuning the model. The easy integration and amazing benefits have made copilot the preference of 55% of developers and gained the trust of over 50,000 businesses. So if you or you company still haven’t used it its probably a time to start doing so. 55% 55% 55% Dont expect its going to replace developers or any stuff like this, but it definitely will save you some time 😉 2. Cursor IDE 2. Cursor IDE The cursor IDE is an AI-powered code editor integrated with a GPT-backed LLM called the Copilot++. The IDE is filled with amazing features to help developers with everyday tedious tasks. Some of its key features include: cursor IDE cursor IDE cursor IDE Code Generation: Copilot++ predicts entire code blocks based on recent changes and project workflow. Smart Rewrites: The IDE auto-fixes syntax and formatting mistakes as developers code. This saves programmers from frustrating and redundant rewrites. Cursor Prediction: Cursor recognizes developers' work patterns and predicts where the cursor would need to be next. Developers can press the tab button to shift to the predicted location automatically. Code Generation: Copilot++ predicts entire code blocks based on recent changes and project workflow. Code Generation: Smart Rewrites: The IDE auto-fixes syntax and formatting mistakes as developers code. This saves programmers from frustrating and redundant rewrites. Smart Rewrites: Cursor Prediction: Cursor recognizes developers' work patterns and predicts where the cursor would need to be next. Developers can press the tab button to shift to the predicted location automatically. Cursor Prediction: Each feature improves developers' productivity and enables robust and quality development. Cursor also includes a chatbot that understands the entire codebase as context. Developers can query the bot by referencing the codebase and ask questions about the implementations and suggestions for improvements. The chatbot is integrated with popular models like GPT-4o, GPT-4, and Claude-3.5-Sonnet. It also includes specialized long-context models like GPT-4o-128k for working with lengthy codebases. The AI-powered features boost productivity and have gained the trust of top organizations like Samsung, OpenAI, and Midjourney. popular models popular models popular models Moreover, Cursor IDE is a fork of the popular VS Code IDE and has a similar intuitive UI and configurations. It also allows VS Code users to migrate their extensions, settings, and keybindings easily. migrate migrate migrate There is a constant twitter (X) battle which one Copilot or Cursor is better, and both sides have strong opinion. For example, Andrej Karpathy recently became a fan of the second one. 3. Tabnine 3. Tabnine Tabnine is an AI coding assistant similar to GitHub Copilot. It is built upon Tabnines proprietary LLM and offers automated code completions and explanations. The assistant also includes a chat option, allowing developers to explain requirements in natural language and generate code snippets. Users can use the Tabnine Protected Chat model or an external LLM like Mistral or GPT-4o. Tabnine Tabnine Tabnine Protected Chat model Protected Chat model Protected Chat model Moreover, Tabnine boasts unique features that distinguish it from Github Copilot. One of its primary features is the focus on data privacy and IP protection. Tabnine's protected model is trained exclusively on licensed code , and unlike Copilot, Tabnine is also transparent about data used for training and can share it with customers under an NDA. Lastly, Tabnine can connect with any Git-based repository, supports every major IDE, and provides cloud environments with GDPR and SOC-2 compliance . licensed code licensed code licensed code GDPR and SOC-2 compliance GDPR and SOC-2 compliance GDPR and SOC-2 compliance Tabnine’s productivity features and focus on data security have gained massive popularity and more than 1 Million monthly users use the tool, but definetly less popular than the previous two. 1 Million 1 Million 1 Million 4. Warp 4. Warp Warp is a terminal for CLI (Command Line Interface) tasks. It provides an IDE-like interface with flexible cursor movement and multi-line edit support. It also has smart command completion that recognizes what the developer is typing and offers suggestions for time-saving. Warp Warp The most interesting feature of the Warp is Warp AI. The terminal is integrated with ChatGPT, and developers can chat with the LLM and ask for terminal command suggestions, for example, the command to start a docker container. Users can explain their desired action in natural language, and the LLM will suggest the appropriate command for it. Warp also introduces Agent Mode, which allows users to navigate the terminal entirely in natural language. Users can explain their desired action in language one-by-one, and warp will execute the relevant command, use the output to guide the user, and correct itself in case of an error. Moreover, Warp AI also understands errors displayed on the terminal and can offer explanations and resolutions. Warp AI . Warp AI Warp AI Agent Mode , Agent Mode Agent Mode In terms of data privacy, Warp has a no-retention policy. Any commands or chats generated by the user are not used for training and are not retained either by Warp or OpenAI. Overall, the Warp is a massive upgrade over the conventional terminal and provides various intuitive features and benefits. 5. Replit Agent 5. Replit Agent Replit Agent has been making waves recently, particularly on Twitter (X) and in tech circles. Many developers are buzzing about how it’s not just another coding assistant like GitHub Copilot, but more of a virtual full-stack developer. What makes it stand out is its ability to handle entire application architectures. Whether it's setting up environments, writing code, or deploying apps, Replit Agent takes on a role similar to that of a junior software engineer, not just a code-suggestion tool. Replit Agent Replit Agent Replit Agent The agent is designed to work with the Replit platform and is built directly into the Replit IDE. It is not just a code generator but understands the users requirements and builds the entire infrastructure required to deploy an application. It offers a natural language interface where users can describe their requirements and have the Replit agent spin up a fully functioning product. Users can choose to add new functionality to the application using prompts like “Add a search bar on the top”. The agent also understands the product requirements and asks follow up questions for clarity on advanced functionalities. Replit IDE . Replit IDE Replit IDE It is strongly integrated with the Replit platform and suggests deployment options, including reserved VMs, autoscaling, and static sites. Replit agent is currently only available via a limited early access program and is proclaimed as an experimental product so must be used with caution. But even though it is prone to some limitations, like handling more complex or backend-heavy applications, it’s a big step towards an AI-driven development trend. LLM applications aim to improve productivity by automating several corporate and development-related tasks. They improve the developer's work experience and productivity and allow them to deliver quality products in a short time.
