Collected AI Tools
Estimated Reading Time: 25 minutes Last updated on 13th September 2025
AI tools refer to software applications and platforms that leverage artificial intelligence technologies to perform tasks traditionally requiring human intelligence. These tools encompass a wide range of functionalities, from natural language processing and computer vision to decision-making and predictive analytics. They are increasingly being integrated into various industries such as healthcare, finance, marketing, and manufacturing to enhance efficiency, accuracy, and productivity. AI tools can automate repetitive tasks, provide insights from large datasets, and facilitate personalised user experiences. As they continue to evolve, these tools hold the potential to transform how businesses operate and innovate, making them indispensable assets in the modern technological landscape. However, their adoption also raises important considerations around ethics, privacy, and the future of work.
Here then are some tools that I have encountered so far. While many are online, some offline tools are here too. The upheaval that AI is bringing upon us is akin to the personal computing one from around thirty years ago. Even the mobile revolution within the last ten or fifteen years does not compare so strongly in extent or depth. This episode could change everything for humanity. That is why my own dalliances with AI tooling proceed with a certain amount of impetus.
Aider is an AI pair programming tool that operates within terminal environments, enabling collaboration with Large Language Models (LLMs) to edit code in local Git repositories. It works optimally with GPT-4 and Claude 3.5 Sonnet but can connect to various LLMs. Key features include editing multiple files simultaneously for complex requests, automatic committing of changes with sensible commit messages, support for popular programming languages like Python, JavaScript, TypeScript, PHP, HTML, and CSS, using a map of your entire Git repo to work effectively in larger codebases, adding images and URLs to the chat for additional context, and enabling voice-based coding. Aider has achieved one of the top scores on SWE Bench, a challenging software engineering benchmark. To use Aider, you can install it via pip and run it within your Git repository using the provided command line instructions. Many users have reported improved coding efficiency and tackling complex tasks after adopting this tool.
This pervasive conversational AI chatbot developed by OpenAI was first released on 30 November 2022 and is built on the GPT large language model family. The system can answer questions with follow-ups, explain concepts, summarise content, generate various forms of writing from essays to emails, translate languages, assist with coding tasks and maintain context throughout conversations. Recent enhancements include larger context windows for processing longer inputs, plugin capabilities, web browsing functionality for current information and multi-modal inputs that accept images or documents. However, users should be aware of significant limitations including hallucinations where plausible but incorrect information may be provided, potential gaps in current data unless specifically updated through browsing features, inherent biases from training data and sensitivity to how queries are phrased. People commonly use it for educational purposes, content creation, coding assistance, brainstorming sessions and document processing because it combines flexibility with conversational interaction across multiple capabilities in a single platform.
Developed by Anthropic, this family of large language models serves as AI assistants designed with a focus on being helpful, honest and safe, with ethics and safety being prominent aspects of its design. The system can handle various natural language tasks including writing, summarisation, question answering, coding and document analysis whilst supporting multiple input types such as images and files. Key strengths include multimodal input handling, maintaining context over longer conversations, strong document analysis capabilities, effective coding and reasoning skills, and implementation of Constitutional AI techniques to reduce harmful outputs. However, like other language models, it can produce hallucinations and incorrect information, may be overly cautious in refusing certain requests due to safety constraints, involves cost and speed trade-offs between different model variants, and raises typical data privacy considerations. Recent developments have enhanced its productivity tools for creating office documents and improved memory features for better personalisation. Additionally, Anthropic offers Claude Code, a terminal-based coding tool that provides in-depth codebase awareness and can edit files and run commands, alongside Claude Desktop applications for Mac and Windows that provide a dedicated interface rather than browser-based access.
This open-source Visual Studio Code extension provides an AI assistant that can perform complex software development tasks through an interactive interface, requiring user approval for each action. The tool can create and edit files whilst monitoring for errors, execute terminal commands, browse the internet using screenshot capabilities, and analyse existing codebases to understand project structure. It supports multiple API providers including OpenRouter, Anthropic, OpenAI and others, whilst tracking token usage and costs throughout development sessions. The extension includes features such as workspace snapshots for comparing and restoring previous states, context addition through URLs and file references, and the ability to create custom tools using the Model Context Protocol. With over 50,000 GitHub stars and active development, it offers a human-supervised approach to autonomous coding assistance that integrates directly into the development environment.
CodeConvert is an AI-driven tool designed to facilitate code conversion across more than 25 programming languages, including commonly used ones such as Python, Java, C++ and JavaScript. The platform features a straightforward interface that enables developers to convert code with a single click, without needing to create an account or provide payment details for basic functionality. Key characteristics of the tool include its AI-powered conversion capabilities, ease of use, and extensive language support. It offers a free version with no registration required, maintaining user privacy by not storing inputs or outputs. For those seeking more advanced features, CodeConvert provides paid options that allow unlimited usage, custom conversion rules, and integration with popular development environments and code repositories. The tool is continually updated to incorporate the latest programming languages and enhancements, serving as a useful asset for developers aiming to optimise their coding workflow.
ComfyUI is an open-source, node-based application for generating images from text prompts. Developed by comfyanonymous and released in January 2023, it has gained significant traction within the AI art community due to its integration with diffusion models like Stable Diffusion. Key features include a visual workflow system, support for multiple diffusion models, saveable workflows in JSON format, and customisable extensions. The software has over 50,000 stars on GitHub and is supported by Nvidia's RTX Remix modding software, as well as the Open Model Initiative. Despite some learning curve and performance challenges, ComfyUI offers flexibility and visual clarity that make it a popular tool for artists and developers interested in AI-generated imagery.
This open-source AI coding assistant provides similar functionality to GitHub Copilot by integrating directly into popular development environments including VS Code and JetBrains IDEs such as IntelliJ, PyCharm and WebStorm. The tool operates as an extension or plugin depending on the chosen editor and offers comprehensive AI-powered assistance through interactive chat functionality, code explanation, function generation, refactoring support and test creation. Users can access these features through side panels for conversation-based interactions or receive inline completions whilst typing, with JetBrains users additionally able to highlight code and access AI assistance through right-click context menus. Although the core functionality remains consistent across different development environments, the user experience adapts to feel more integrated with each specific IDE's interface and workflow patterns.
Built on a fork of Visual Studio Code, this AI-powered integrated development environment developed by Anysphere offers enhanced coding capabilities for Windows, macOS and Linux users. The editor provides agent mode functionality that allows developers to describe changes in natural language and execute modifications across multiple files, whilst its deep codebase indexing system enables natural language queries about project structure and context. Beyond standard autocompletion, it delivers predictive edits and multi-line suggestions, smart refactoring tools and terminal command assistance that converts natural language instructions into shell commands. The platform includes privacy protection through SOC-2 certification and a privacy mode that prevents remote code storage without consent. Although it excels at complex refactoring and offers powerful context-aware editing for small to medium projects, users report a steeper learning curve compared to alternatives like Windsurf, potential performance limitations with very large codebases and concerns about subscription costs and plan restrictions. Whilst Cursor generally provides faster local editing and fluid typing experiences, competing tools may offer more intuitive interfaces for beginners and better handling of deeply interconnected projects, though the choice ultimately depends on individual coding requirements and project complexity.
This AI voice synthesis platform specialises in creating hyperrealistic voice generation for applications such as audiobooks, video narration and voice cloning. The service employs advanced AI models to produce natural, conversational narrations and can create realistic podcast-style content with dual AI co-hosts. Users can replicate voices using just minutes of audio for basic cloning, or achieve professional-grade results with longer recordings of over 30 minutes. The platform caters to developers through comprehensive APIs and SDKs supporting various programming languages including Python and TypeScript for integration into applications and services. However, the platform restricts studio projects to three concurrent works, each supporting up to 500 chapters with individual chapters limited to 400 paragraphs and 5,000 characters per paragraph. The handling of voice data presents potential privacy considerations, particularly regarding voice cloning features, requiring users to carefully examine terms of service and data security policies before proceeding with sensitive audio content.
FauxPilot is an open-source, self-hosted tool designed as an alternative to GitHub Copilot, focusing on AI-assisted code generation while maintaining privacy by running locally. It leverages SalesForce CodeGen models within NVIDIA's Triton Inference Server to offer smart code suggestions. Unlike GitHub Copilot, it does not use OpenAI Codex, potentially reducing licensing issues and copyright risks. Users can customise and train their own AI models with specific code bases, allowing greater control over the output. Additionally, it serves as a research platform for developing and assessing code models aimed at producing more secure code. FauxPilot is suited for developers and organisations prioritising control over their coding tools and safeguarding data privacy and security, requiring specific hardware such as an NVIDIA GPU with Compute Capability of at least 6.0 and adequate VRAM.
Figstack is an AI-driven tool aimed at boosting developers' productivity by simplifying the coding process across various programming languages. It provides features such as translating complex code into simple English, converting code between over 70 programming languages, generating comprehensive function documentation, analysing code efficiency with Big O notation, and integrating with GitHub for version control and collaboration. Figstack is available in multiple pricing tiers, with a free plan offering limited credits and paid plans providing more extensive features. Its user-friendly interface makes it suitable for developers of all experience levels, enabling them to concentrate on complex programming tasks by automating routine development aspects, ultimately enhancing efficiency and productivity.
GitHub Copilot is an AI code completion tool developed by GitHub and OpenAI, launched in October 2021. Supported by popular IDEs like Visual Studio Code, JetBrains IDEs, Neovim, and primarily Python, JavaScript, TypeScript, Ruby, and Go, it assists developers with generating real-time suggestions, error correction, documentation assistance, unit testing, code optimization, security features, increased productivity, accelerated learning, better collaboration, and is used by over 77,000 businesses worldwide. Future developments include the integration of a chatbot based on GPT-4 in March 2023 to enhance user interaction through voice commands and more sophisticated conversational capabilities. GitHub Copilot represents significant advancements in software development tools, improving efficiency, reducing repetitive tasks, and enhancing overall code quality.
Google's DeepMind has developed a multimodal AI suite, Google Gemini, capable of processing various formats such as text, images, audio, and video. With an expanded context window of up to 1 million tokens, Gemini excels in understanding complex queries by handling multiple inputs simultaneously. It is designed for seamless integration with Google applications like Gmail and Docs and supports 35 languages. Capabilities include advanced reasoning abilities, image/video processing, custom chatbots (Gems), and features such as "Audio Overviews" that generate spoken summaries from text input. Comparatively, Gemini surpasses models like OpenAI's GPT-4o due to its larger context window and native multimodal capabilities, making it a leading competitor in generative AI applications.
Hugging Face is a leading machine learning platform founded in 2016 by Clément Delangue, Julien Chaumond, and Thomas Wolf. Known for its Transformers library, the company simplifies access to pre-trained models for natural language processing tasks like text classification, summarisation, translation, and question answering. With over 900,000 models and 200,000 datasets available on the Hugging Face Hub, users can share, and experiment with, various machine learning applications. The platform fosters a strong community and offers extensive documentation, tutorials, and an Inference API for both free prototyping and paid production workloads. By democratising access to machine learning tools, Hugging Face continues driving advancements in artificial intelligence technologies.
Ideogram is a user-friendly, text-to-image AI generator that enables users to create visually appealing images from written prompts. The tool caters to various users, including artists, marketers, and content creators, who can generate photorealistic images and artwork quickly and efficiently using deep learning neural networks. Users can input text prompts which the AI translates into corresponding visuals, offering customisation options such as styles and moods. All in all, Ideogram is a versatile tool that facilitates creativity and streamlines the design process across various fields.
Inquisite is a research platform powered by AI technology from Duke University professors, designed for efficient information gathering and document generation. Its proprietary engine searches, reads, ranks sources, and synthesises data into coherent reports or presentations while providing citations. Collaborative tools facilitate group projects. Applicable across academia, business analysis, and content creation sectors, Inquisite offers a free tier with additional features in paid plans. By reducing time spent on manual searches, it aims to improve research efficiency while ensuring credible information.
Meta's Llama (Large Language Model Meta AI) is a series of advanced open-source language models developed by Meta, designed to facilitate various natural language processing tasks and promote accessibility in the AI community. The Llama models include variants like 3.1 and 3.2, featuring configurations ranging from 8 billion to 405 billion parameters and support for extended context lengths of up to 128K tokens. They can process both text and visual inputs, enabling applications in chatbots, content creation, data analysis, education, and more. Trained on over 15 trillion tokens from diverse sources, these models provide developers with powerful tools to innovate across various applications while ensuring safety through features like Llama Guard and Prompt Guard. Accessibility is emphasised through open-source availability under certain licensing constraints and partnerships with cloud providers for broader accessibility. The Llama models represent a significant advancement in open-source AI technology, offering flexibility, multimodal capabilities, and community engagement.
LLaVA, an open-source multimodal AI model developed through a collaboration between researchers from the University of Wisconsin-Madison, Microsoft Research, and Columbia University, uses a transformer architecture to integrate language and visual understanding capabilities. This advanced system can process queries involving both images and text simultaneously, enabling users to discuss image content. Trained on a relatively small dataset compared to other models, LLaVA demonstrates impressive performance in various benchmarks, particularly those requiring deep visual understanding and instruction-following. The model utilizes the CLIP (Contrastive Language–Image Pre-training) visual encoder for processing images, allowing it to bridge the gap between text and images effectively. LLaVA has undergone several iterations, with recent developments focusing on improving vision-language connectors and data tailored for academic tasks. This open-source alternative to established models like OpenAI's GPT-4 is a valuable tool for various applications due to its ability to seamlessly integrate language and vision.
This open-source enhanced ChatGPT clone provides comprehensive artificial intelligence conversation capabilities across multiple platforms and models. The platform supports integration with numerous AI providers including Anthropic Claude, OpenAI, Azure OpenAI, Google, AWS Bedrock and various custom endpoints without requiring proxy configurations. Key functionality includes a secure code interpreter for multiple programming languages, customisable agents and tools integration through the Model Context Protocol, web search capabilities with content re-ranking, and generative user interface features supporting React, HTML and Mermaid diagram creation. The system offers multimodal interactions allowing users to upload and analyse images whilst chatting with files, supports over 30 languages, and includes advanced conversation management through presets, branching and sharing capabilities. Additional features encompass speech-to-text and text-to-speech functionality, comprehensive import and export options for conversations, multi-user authentication with OAuth2 and LDAP support, and flexible deployment options for both local and cloud environments. The project maintains active community development with regular updates and welcomes contributions for translations and feature enhancements.
LightLLM is a Python-based Large Language Model (LLM) inference and serving framework designed for high performance and scalability. It features efficient GPU utilization through tri-process asynchronous collaboration, efficient handling of requests with large length disparities using Nopad attention operations, dynamic batch scheduling, and faster inference and reduced GPU memory usage through FlashAttention integration. Additionally, it offers multi-GPU token parallelism, optimised GPU memory management via Token Attention, high-performance Router for system throughput optimization, and an Int8KV Cache for increased token capacity (Llama models only). LightLLM is based on open-source implementations like FasterTransformer, TGI, vLLM, and FlashAttention. It's lightweight and scalable, making it suitable for deploying and serving large language models efficiently. Benchmarks show competitive performance with other frameworks on various platforms. The use of OpenAI Triton for kernel implementation and its relatively compact codebase make it easier for developers to optimise the framework. Instructions to launch and evaluate LightLLM's performance are provided in its documentation.
LM Studio is a desktop application that enables users to run large language models locally on their computers without needing technical expertise or coding skills. It offers a user-friendly interface for discovering, downloading, and interacting with various pre-trained models from open-source repositories such as Hugging Face. Key features include offline operation for enhanced data privacy, a built-in chat interface, and a document chat functionality that allows interaction with local documents using Retrieval Augmented Generation. It also supports an OpenAI-compatible local server. The application facilitates model discovery through a Discover page and supports various model architectures. Designed to make language models accessible for personal experimentation while preserving data sovereignty, LM Studio is free for personal use but requires a business licence for commercial applications. Though the application itself is not open-source, it aids in the distribution and use of available AI models.
Swiss-based Proton AG launched this privacy-focused AI chatbot as an alternative to mainstream AI assistants that prioritise user data protection. The service employs end-to-end encryption for all conversations, ensuring that only users can access their chat history, whilst Proton itself cannot view interactions or maintain server logs. Built on open-source language models including Mistral's Nemo and OLMO 2 32B, the platform operates exclusively within European data centres in Germany and Norway, adhering to strict GDPR privacy regulations. The service offers three access tiers ranging from limited guest usage to a premium subscription that provides unlimited conversations, file upload capabilities and advanced reasoning features. Key functionality includes document analysis, email drafting, coding assistance and optional web search through privacy-friendly engines, with a Ghost Mode feature that automatically deletes conversations upon closing. Though user feedback suggests the performance may not match established AI models like OpenAI's offerings, early adopters appreciate the genuine commitment to privacy and data security, particularly for handling sensitive legal, medical or personal information where confidentiality remains paramount.
Microsoft 365 Copilot is an AI-integrated productivity tool within Microsoft Office Suite that uses advanced capabilities like GPT and DALL-E for task assistance across various applications, including Word, Excel, and PowerPoint. The user-friendly interface allows interaction via voice commands or chat interfaces, enhancing the experience while automating routine tasks to save time. Copilot is available on multiple platforms such as Windows and Microsoft Edge for versatility in various work environments. It aims to boost productivity by providing intelligent suggestions, allowing users to focus on more strategic aspects of their jobs. The integration within familiar applications simplifies usage and access to AI capabilities. In conclusion, Copilot is a valuable addition to the modern workplace that empowers individuals with enhanced capabilities and streamlined workflows.
Mistral is a sophisticated AI platform developed by a French startup that offers open-weight, customisable models like Mistral 7B and Mixtral 8x7B for various applications across industries. The platform boasts exceptional speed, efficiency, and top-tier reasoning capabilities in multiple languages. It supports serverless APIs, public clouds (such as Azure and Amazon Bedrock), and on-premise setups, ensuring flexibility for users. Mistral recently introduced the Pixtral Large Model with 124 billion parameters, excelling at both text and image processing, making it suitable for complex tasks like document question answering and chart analysis. The platform's Le Chat interface has been updated with web search capabilities, a collaborative "Canvas" tool, and advanced document/image understanding features to enhance user productivity. Mistral provides flexibility through various deployment options and community support while catering to developers, businesses, and researchers with high-performance models. However, it may come with an initial setup complexity and learning curve, as well as potential cost considerations for smaller users. The platform's combination of high performance, flexibility, and community-driven support makes it appealing to both startups and established enterprises.
NotebookLM, developed by Google, is an advanced AI-driven note-taking and research tool that uploads, summarises, and interacts with documents in various formats. It provides a platform for organizing notes, extracting key information through Q&A sessions, creating outlines, generating study guides or FAQs, and producing audio summaries. Notable benefits include time efficiency, enhanced productivity, and improved information retention. Designed for students, educators, and professionals alike, this innovative technology streamlines research processes and adapts to individual needs.
This productivity tool harnesses GPT technology to transform lengthy content into organised notes and study materials. The platform processes various formats including PDFs, videos, articles, presentations and images, converting them into concise summaries, mind maps and presentations with visual outputs that include slide decks, podcasts and infographics. For YouTube content specifically, it extracts transcripts, segments material, answers questions and creates summaries while supporting batch processing and translation capabilities. However, users should be aware that the tool may disproportionately emphasise certain points and potentially misinterpret nuanced discussions, whilst privacy considerations around GDPR compliance remain unclear and warrant careful investigation, particularly for EU users.
This AI-powered learning tool helps users study through personalised questions and concise explanations, utilising active recall and spaced repetition techniques. The platform allows unlimited document uploads across various formats including PDFs and images, providing verified answers with detailed citations for fact-checking purposes. It maintains user privacy and security whilst offering context-aware search functionality that becomes increasingly personalised over time by learning from stored notes. However, the free tier has limitations with higher functionality requiring subscription payments, and being a newer platform, it may lack the integrations and community support found in more established alternatives.
Ollama is an open-source tool designed for running large language models (LLMs) locally on personal devices, catering to developers, researchers, and businesses seeking enhanced control over their AI applications while addressing privacy concerns. Key features include local execution of various LLMs, ensuring data security by keeping sensitive information on the user's machine, model customisation, extensive library access, a user-friendly interface with command line functionality, and seamless integration with programming languages and frameworks. Ollama is versatile, applicable in numerous scenarios such as chatbots, summarisation tools, creative writing aids, and more. It offers significant advantages through its robust solution for local AI model execution, focusing on providing a user-friendly environment for managing large language models.
Perplexity AI is an innovative search engine powered by artificial intelligence (AI) that offers conversational search capabilities, multimodal content generation, user-centric design, and real-time information through a natural language interface. Founded by Aravind Srinivas and his team, the platform aims to prioritize users over advertisers, providing a comprehensive search experience. Perplexity AI uses large language models (LLMs) to interpret queries contextually and generates answers in a conversational format with citations and suggestions for further refinement. It can also create various types of content like text, images, and simple code by integrating multiple LLMs and image generation models. The platform is designed to be intuitive and user-friendly, with features such as swiping to delete threads and voice-based interaction on mobile devices. Perplexity AI indexes the web daily, allowing it to provide up-to-date information. Users can create a free account for additional features like sharing collections and customising preferences. The platform supports search threads and offers a Focus feature for direct searches across various categories.
Privy is an AI-powered coding assistant focused on enhancing developer productivity while maintaining a strong emphasis on privacy and security. It is open-source and self-hosted, granting users control over code and data. Privy supports multiple programming languages and integrates with popular IDEs such as Visual Studio Code. It offers features like AI-driven code completion, generation, and in-editor chat assistance. Additional capabilities include code explanation, documentation generation, unit test creation, and bug detection. Compatible with various AI models like DeepSeek Coder, CodeLlama, and Mistral, users can tailor the tool according to their hardware and preferences. Designed for both individual developers and teams, Privy serves as a comprehensive alternative to proprietary AI coding assistants by promoting open-source principles and user data control.
PromptHub is a platform designed for teams working with large language models (LLMs), offering a comprehensive solution for prompt management. It centralises the organisation, versioning, testing, and deployment of prompts, providing both community sharing and enterprise-grade collaboration features. This platform serves prompt engineers, ML engineers, software developers, and product managers, with support for public prompt sharing and private team workspaces. Pricing plans range from free to custom enterprise solutions, varying in feature availability and limits.
Refraction is an AI-powered tool that aids developers in optimising their software development by offering an extensive range of features across numerous programming languages. It supports 56 languages, including Python, Java, JavaScript and C++, providing capabilities like AI-driven code generation, automatic unit test creation, code refactoring, and inline documentation. Integrated with Visual Studio Code, it allows users to generate code snippets, create unit tests, refactor existing code, automatically document code, add debugging statements, and convert code between different languages. The tool aims to reduce the time spent on repetitive tasks, empowering developers to dedicate more attention to intricate programming challenges. It is available in both free and paid versions, catering to individual developers and teams striving for greater coding efficiency.
Tabby is an open-source, self-hosted AI coding assistant designed to enhance developer productivity with real-time code suggestions and autocompletion for various programming languages. It provides a self-hosted solution that allows developers to maintain control over their code and data, offering an alternative to proprietary tools. Tabby seamlessly integrates with popular development environments such as Visual Studio Code, Vim/Neovim, and JetBrains IDEs and is compatible with major coding large language models, enabling the combination of preferred models. It emphasises end-to-end optimisation for efficient code completion while ensuring privacy and security by eliminating the need for external database management systems or cloud services. Driven by a community-focused approach, it engages users through various platforms, making it a flexible, secure, and efficient coding assistant for individual developers and teams.
Tabnine is an AI-powered code completion assistant intended to boost developers' productivity. Its key features include real-time intelligent code suggestions, support for over 80 programming languages and frameworks including JavaScript, Python, Java, and C++, and integration with major IDEs like VS Code, Eclipse, and JetBrains products. It offers context-aware completions relevant to the current project and coding context, can translate natural language queries into code snippets, and prioritises security with SOC-2 compliance and options for local adaptability. Tabnine provides three pricing tiers: a free Starter tier with basic completions, a Pro tier with advanced features and an Enterprise tier with custom pricing tailored for large organisations focusing on enhanced security and customisation. In summary, Tabnine seeks to expedite software development, ensure code consistency, and aid in code reviews while upholding privacy and security.
TLDR This is an AI-powered summarisation tool designed to help users quickly digest lengthy articles, documents, and other text-based content by condensing key points into concise summaries using advanced natural language processing algorithms. Users can customise the length of their summaries, making it adaptable for various needs, and access it as a web application or browser extension to simplify information gathering from favourite websites. The tool's applications include academic research, professional efficiency enhancement, and staying informed about current topics. In short, TLDR This offers automatic summarisation capabilities and API access for developers.
This AI-powered integrated development environment was formerly known as Codeium and focuses on maintaining developer workflow by reducing tool switching through intelligent context awareness across entire codebases rather than simple autocomplete functionality. The platform features Cascade, an agentic layer that understands project structure and provides relevant suggestions for multi-file tasks, alongside integrated live previews for web applications that allow developers to see changes without running separate instances. The editor supports Mac, Windows and Linux systems whilst incorporating automatic lint error fixing and deep project indexing for enhanced code suggestions. The platform has gained significant adoption with over one million users and numerous enterprise customers, positioning itself as more comprehensive than basic AI coding assistants by offering project-wide modifications and debugging capabilities. However, users should remain cautious about AI-generated code quality, potential performance impacts on large projects, and the risk of over-dependence leading to reduced manual coding skills development.
Launched in 2021, You.com is an AI-driven search engine and productivity platform that focuses on user customisation, privacy, and advanced capabilities. It offers a free tier for basic features and a Pro subscription with unlimited queries and extra features. The platform caters to knowledge workers, content creators, and general users by providing personalised AI-powered search results and interactive experiences. Despite competition, its emphasis on customisation sets it apart in the market, potentially leading to future developments that enhance productivity across various sectors.