With the ever-evolving world of AI, it’s easy to get overwhelmed. We've curated a list of tools we find really exciting, and hope you adopt a few of these tools into your own workflows to enhance your productivity. Whether it’s finding the next AI-powered IDE, test suite, or debugger, we’ve got you covered. 1. Gemini CLI Around a week ago, Google released Gemini CLI, their take on an open-source CLI AI Assistant. In addition to providing great integration with one of the best overall models, the Gemini CLI has a very generous free tier with 1,000 requests per day, claiming the best free tier in the industry. It’s definitely worth checking out, especially if you have a large codebase and need the 1,000,000 token context window provided with Gemini 2.5 Pro. Gemini CLI best overall models very 2. Stagewise Stagewise is an open-source VS Code extension that lets you change UI with english. You would highlight a specific UI component, and then prompt with what you want to change. This gives you a visual vibe coding experience, making quick iterations simple and powerful. For an in-depth review of stagewise, check out our article on it. Stagewise our article 3. Augment Code Augment Code is a great AI development tool praised for its context-awareness. It’s one of the most autonomous development tools we’ve seen so far, with remote agents that run independently in containers. Early users credit Augment Code for excelling with large codebases, and it integrates with GitHub, Jira, Confluence directly in the IDE of your choice. For a more detailed overview, check out our more in depth blog. Augment Code in depth blog 4. Mabl Mabl is an AI-native test platform for web, mobile, and performance testing. Mabl offers a full stack testing suite, with visual regression, cross-browser testing, API testing, and more. If you're building apps with AI features or apps using APIs (chatbots, image generation, checkout flows), Mabl is worth checking out. Mabl visual regression 5. Termineer – CLI-Based Dev Agent I’ve personally really loved working with Claude Code, but I’ve been missing a few things, and Termineer fills a lot of those gaps. First, Claude Code is tightly integrated with Anthropic models, whereas Termineer is model agnostic, allowing you to use the different strengths of various models when you need them. Also, Termineer doesn’t require the setup requirements tied to Claude Code. Termineer doesn’t need a CLAUDE.md file, special directory structuring, or custom config files. Termineer 6. Context7/mcp All too often, LLMs use outdated information when developing because of their training cutoff. Context7 fixes this through their MCP, which provides up-to-date documentation for your LLM. All you have to do is include ‘use context7’ at the end of your prompt, and your LLM will receive high quality documentation, including API usage examples, and code examples. Context7 7. Ruler Modern collaboration with others has become confusing and complicated, with everyone having separate instructions for their LLMs in a given codebase. Ruler fixes this by standardizing LLM instructions for over 10 different AI Agents, including Claude Code, Cursor, and Windsurf. Ruler also breaks down complex markdown instruction files into separate, organized guides making AI Assisted development clearer and easier. Ruler Ruler 8. Mem0 - Memory for Agents Mem0 is an open-source memory management tool, boasting better accuracy, speed, and cost compared to OpenAI’s memory management and full-context approaches. Mem0 does this through memory abstraction and prioritization based on importance. Instead of storing whole conversations to reference, Mem0 stores facts such as ‘User prefers Python to JavaScript’. Mem0 also uses LLM classification to judge fact salience, reducing unnecessary memories. Mem0 better accuracy, speed, and cost Final Thoughts Final Thoughts These tools allow you to rethink your existing development processes, making your coding, testing, debugging and automation workflows more efficient and elegant. From model-agnostic CLI agents to visual UI editing and autonomous test orchestration, we're witnessing a shift toward integrated, AI-native development environments. Try them out, experiment, and shape the way development evolves with AI. Let us know your experiences with these tools, or any tools we might have missed!

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8 AI Tools That You Should Be Excited About (And Adopt!)

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