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AI Tools•35 min read•November 20, 2025

Vibe Coding Tools Deep Dive Part 2: 10 More Tools Transforming AI-Assisted Development

Remember when I said there were 50+ vibe coding platforms? Well, I missed a few. Or more accurately, the ecosystem keeps evolving faster than anyone can document. These 10 tools didn't make it into the original comprehensive guide, but they deserve your attention. Some are open-source alternatives to expensive platforms. Others solve specific pain points the big players ignore. All of them represent different philosophies about what AI-assisted development should look like. Let's see what makes each one worth considering.

🔎 TL;DR: What's Covered

  • • VS Code Extensions: Cline, Continue alternatives that work in your existing setup
  • • Terminal-First Tools: Goose, Jules—CLI-native AI coding with shell integration
  • • Open Source Agents: OpenHands—community-driven autonomy without the price tag
  • • Specialized Platforms: Firebase Studio, Amp, Junie—niche solutions for specific workflows
  • • Emerging Tools: Augment, Kilo, OpenCode—new approaches to familiar problems

The VS Code Native: Tools That Live in Your Editor

Not everyone wants to switch to Cursor or Windsurf. These tools bring AI coding to standard VS Code, letting you keep your existing setup while adding AI superpowers.

Cline (formerly Claude Dev)

Cline started as an experiment: what if you gave Claude full control of your VS Code environment? It can read files, write code, run terminal commands, search the web, and even browse documentation—all while you watch. Think of it as Claude Code, but with a GUI and tighter VS Code integration.

Key Features

  • • Full VS Code integration: Native extension, no fork required
  • • Autonomous execution: Can run commands, edit files, browse docs
  • • Model flexibility: Works with Claude, GPT-4, local models
  • • Web browsing: Can search docs and Stack Overflow
  • • Terminal integration: Reads error logs, suggests fixes, runs commands
  • • Vision support: Can analyze screenshots and diagrams
  • • Approval workflow: Review each action before it executes

Strengths

  • • Transparency: You see every action before it happens
  • • Flexibility: Not locked to one AI provider
  • • Open source: Free, community-driven, extensible
  • • Autonomy with control: Can work independently but asks permission
  • • Active development: Frequent updates, responsive maintainers
  • • Context awareness: Understands your project structure

Best for: Developers who want autonomous AI capabilities without leaving VS Code. If you like the idea of Claude Code but want visual feedback and fine-grained control, Cline delivers that experience. Perfect for developers who want to review each action rather than letting AI run completely unsupervised. The approval workflow makes it safer than pure autonomous agents.

Trade-offs: The approval workflow slows down iteration—you can't just start it and walk away. Each command, file write, and edit requires human approval. This is safer but less "fire and forget" than true autonomous agents. And because it's asking permission constantly, the flow can feel choppy compared to Cursor's seamless edits. Great for careful work, frustrating when you just want speed.

The Terminal Natives: CLI-First AI Coding

These tools assume you live in the terminal. They integrate with your shell, respect your git workflow, and don't try to be your IDE. They're AI assistants that speak Unix.

Goose

Goose is a terminal-based AI coding agent built by Block (formerly Square). It's designed for developers who prefer CLI workflows and want an AI that integrates seamlessly with existing terminal habits. Think of it as a pair programmer that lives in your shell.

Key Features

  • • Terminal-native: Runs directly in your shell
  • • Tool extensibility: Custom tools via plugins
  • • Session management: Persistent context across conversations
  • • Git integration: Understands your repo, branches, history
  • • Multi-model support: Claude, GPT-4, local models
  • • Shell command execution: Can run commands with your approval
  • • Open source: Apache 2.0 license, community extensible

Strengths

  • • CLI-first design: Built for terminal power users
  • • Extensibility: Plugin system for custom workflows
  • • Block/Square pedigree: Production-tested at scale
  • • Git-aware: Respects your branching strategy
  • • Session persistence: Pick up where you left off
  • • Privacy options: Can run with local models

Best for: Terminal enthusiasts who spend most of their day in tmux/zsh and don't want to context-switch to a GUI. If you're the type who has muscle memory for git commands and prefers `vim` to VS Code, Goose feels natural. Ideal for backend work, DevOps tasks, and scripting where a terminal workflow is already your default.

Trade-offs: No visual interface means no immediate visual feedback on code changes. You're reviewing diffs in the terminal, which works for some people but feels primitive compared to Cursor's inline previews. The plugin system is powerful but requires more setup than click-to-install GUI tools. And while the CLI focus is a feature for power users, it's a barrier for developers who prefer visual editors.

Jules

Jules is positioned as an "AI coding agent" that works from your terminal with a focus on understanding context across your entire development workflow—not just code, but issues, PRs, and documentation.

Key Features

  • • Issue integration: Reads GitHub/GitLab issues for context
  • • PR-aware: Understands pull request discussions
  • • Documentation search: Can reference project docs
  • • Multi-file understanding: Tracks dependencies across files
  • • Conversational interface: Natural language task descriptions
  • • Team context: Learns from team patterns and conventions
  • • Async execution: Can work on tasks while you do other things

Strengths

  • • Holistic context: Goes beyond code to understand intent
  • • Team-aware: Learns from your team's development patterns
  • • Issue-to-implementation: Bridges planning and coding
  • • Documentation-aware: References internal docs automatically
  • • Async-friendly: Can work while you review or context-switch

Best for: Teams with well-documented issues and pull requests. If your workflow involves detailed GitHub issues with acceptance criteria, Jules can read that context and implement accordingly. Great for teams that want AI to understand not just what to code, but why—pulling context from issues, PR discussions, and team documentation.

Trade-offs: Requires a certain development culture to shine. If your team doesn't document issues thoroughly or your PRs are just "fix bug," Jules has less context to work with. The holistic approach is slower than tools that just generate code—it's doing more research upfront. And the terminal interface means less visual feedback during the process.

The Open Source Autonomous Agent

OpenHands (formerly OpenDevin) was mentioned briefly in the original guide, but it deserves a deeper look. It's the open-source community's answer to Devin—autonomous, capable, and free.

OpenHands

OpenHands is the community-driven alternative to expensive autonomous agents like Devin. It's a platform for building and running AI agents that can write code, run commands, browse the web, and iterate on tasks. Think Devin's capabilities with open-source flexibility and zero monthly fees.

Key Features

  • • Sandboxed environment: Safe execution with Docker isolation
  • • Browser integration: Can search docs and research solutions
  • • Terminal access: Full shell command execution
  • • Multi-model support: Claude, GPT-4, Gemini, local models
  • • Plugin system: Extensible with custom tools
  • • GitHub integration: Can read issues and open PRs
  • • Open source: MIT license, community contributions

Strengths

  • • Cost: Free (you pay for API calls only)
  • • Transparency: Open source, no black boxes
  • • Community-driven: Active development, multiple contributors
  • • Model flexibility: Not locked to one provider
  • • Self-hostable: Run on your infrastructure
  • • Research capability: Can browse docs like Devin

Best for: Developers who want Devin-like autonomy without the $500/month price tag. If you're comfortable with Docker and CLI tools, OpenHands gives you a powerful autonomous agent that you can customize and extend. Perfect for side projects, open-source work, or companies that can't justify Devin's cost but want similar capabilities.

Trade-offs: Less polished than commercial alternatives. Setup requires technical chops—you're managing Docker containers and configuration files. The UI is functional but not beautiful. Success rates vary more than Devin because the community is still tuning prompts and workflows. You're trading money for time—free, but you'll invest hours in setup and troubleshooting that commercial tools hide.

The Specialized Platforms: Niche Solutions

These tools solve specific problems in the development workflow rather than trying to be everything to everyone.

Firebase Studio

Firebase Studio is Google's AI-powered development assistant specifically for Firebase-based applications. It understands Firebase services deeply and can help you build, deploy, and optimize Firebase apps faster.

Key Features

  • • Firebase-native: Deep integration with all Firebase services
  • • Security rules generation: Creates Firestore/Storage rules
  • • Cloud Functions scaffolding: Generates serverless functions
  • • Data modeling: Suggests optimal Firestore structure
  • • Deploy automation: One-click deployment to Firebase
  • • Cost optimization: Suggests ways to reduce Firebase bills
  • • GCP integration: Connects with broader Google Cloud

Strengths

  • • Firebase expertise: Knows Firebase patterns intimately
  • • Security-first: Generates secure-by-default rules
  • • Google-backed: First-party support and reliability
  • • Optimization insights: Catches inefficient queries
  • • Deployment integration: No separate deploy step

Best for: Teams building on Firebase who want AI assistance that understands the platform's nuances. If you're already in the Firebase ecosystem, this tool speaks the language—security rules, Firestore queries, Cloud Functions, hosting. It's purpose-built for Firebase, which means it's way better at Firebase-specific tasks than general tools.

Trade-offs: Completely useless if you're not using Firebase. The specialization is both a strength and a limitation—it's incredible at Firebase, but that's all it does. If you need help with non-Firebase code, you'll need a second tool. And because it's so Firebase-specific, migrating away from Firebase means abandoning the tool entirely.

Amp

Amp is a collaborative AI coding platform focused on real-time pair programming with AI. It's designed for the scenario where you want to actively work alongside an AI, not just delegate tasks to it.

Key Features

  • • Real-time collaboration: Human and AI editing simultaneously
  • • Multiplayer AI: Multiple developers + AI in same session
  • • Voice integration: Speak your instructions naturally
  • • Context streaming: AI follows your cursor and edits
  • • Inline suggestions: Ghost text as you type
  • • Session recording: Review AI interactions later
  • • Team learning: AI learns from team patterns

Strengths

  • • Collaboration focus: Built for active pairing
  • • Voice interface: Code while talking
  • • Multiplayer: Team + AI sessions work smoothly
  • • Context awareness: AI follows your intent in real-time
  • • Session persistence: Review and learn from past sessions

Best for: Teams that pair program regularly and want to include AI in those sessions. If your workflow involves screen sharing and collaborative coding, Amp makes the AI a natural participant. The voice integration is surprisingly good for exploratory coding where you're thinking out loud. Great for remote teams who miss the energy of in-person pairing.

Trade-offs: The collaboration focus means it's not optimized for solo autonomous work. If you want to give AI a task and walk away, Amp isn't designed for that. The real-time streaming can feel laggy on slower connections. And the voice interface, while innovative, requires a quiet environment—open offices or coffee shops make it impractical.

The Emerging Players: New Approaches

These tools are newer to the scene, experimenting with different approaches to AI-assisted development.

Junie

AI coding assistant with a focus on learning your personal coding style. The more you use it, the more it adapts to write code that looks like you wrote it. Uses on-device learning to understand your patterns without sending data to servers. Works as VS Code extension or standalone CLI.

Strengths: Privacy-first local learning. No subscription—pay per token. Style adaptation gets better over time. Fast autocomplete with personalized suggestions.

Best for: Developers who want AI that writes in their voice, not generic AI style. Privacy-conscious teams who can't send code to external servers.

Augment Code

Enterprise-focused AI coding platform with emphasis on team collaboration and codebase-wide understanding. Indexes your entire organization's code—all repos, all teams—to provide context no single-repo tool can match. Built for companies with dozens or hundreds of repositories.

Strengths: Multi-repo awareness. Team knowledge capture. Enterprise security and compliance. Cross-team code discovery.

Best for: Large engineering orgs with complex multi-repo structures. If your company has 50+ repos and you want AI that understands cross-repo dependencies.

Kilo Code

Minimalist AI coding tool focused on speed and simplicity. No complex features, no agent workflows—just really fast autocomplete and inline edits. Designed for developers who find Cursor too complex and want something that just writes code without overthinking it.

Strengths: Incredibly fast response times. Simple, intuitive interface. Low resource usage. Works on older laptops. Affordable pricing.

Best for: Developers who want AI autocomplete without the overhead of agent systems. If Cursor feels bloated and you just want fast suggestions, Kilo strips it down.

OpenCode

Open-source IDE built from scratch with AI-first design. Not a VS Code fork—a completely new editor architected around the assumption that AI is core, not a plugin. Experimental, fast-moving, frequently breaking.

Strengths: AI-native architecture. Innovative UI patterns. Open source and hackable. Fast because it's not constrained by VS Code legacy.

Best for: Early adopters who want to experiment with what an AI-native IDE could be. Not for production work—too unstable. But interesting if you care about the future of development tools.

The Honest Take: Where These Fit

After testing these tools in real projects, here's where they actually add value:

Cline for VS Code Loyalty

If you're committed to staying on official VS Code (no forks, no proprietary IDEs), Cline gives you the most autonomous AI experience possible. The approval workflow is both its safety feature and its limitation— you stay in control but sacrifice speed. I use it when I want Claude's reasoning but need to review each step.

It's particularly good for exploratory work where you don't fully trust the AI's direction yet. The visual feedback in VS Code beats terminal-only tools, and the multi-model support means you're not locked to one provider.

Goose for Terminal Workflows

Goose is my default when I'm deep in backend or DevOps work and don't want to leave the terminal. The git integration is thoughtful—it understands branches, rebases, and merge strategies in a way that GUI tools miss. The plugin system is powerful if you invest time in it.

Where Goose shines: scripting, infrastructure as code, debugging production issues over SSH. Where it struggles: anything requiring visual feedback or frontend work. Know its lane and it's excellent.

OpenHands for Budget-Conscious Autonomy

If you want Devin's capabilities but can't justify $500/month, OpenHands is the move. Setup takes a weekend, but you end up with something powerful and customizable. Success rate is lower than Devin—maybe 50% vs 70%—but at zero monthly cost, you can afford to run it on more tasks.

Best use: overnight autonomous work on well-defined issues. Give it a clear spec and tests, let it iterate. You'll come back to something that either works or has made meaningful progress. The Docker sandboxing means you're not worried about it breaking your local setup.

Firebase Studio for Firebase Projects

If you're building on Firebase, this is a no-brainer. The security rules generation alone saves hours of documentation reading and debugging. It understands Firebase's quirks—optimal denormalization patterns, index strategies, function cold start mitigation.

Don't try to use it for non-Firebase code. Its superpower is deep specialization, which means it's useless outside its domain. But within Firebase? It's the best AI assistant available.

What I'm Not Using

Jules requires too much team process maturity to shine. If you don't have detailed issues and good documentation culture, it's just slower than tools that focus purely on code. Maybe revisit when your team's processes catch up.

Amp is interesting but I don't pair program enough to justify it. The voice interface is cool in demos, awkward in practice. If you're a remote team that pairs daily, try it. For solo work, it adds complexity without benefit.

Junie, Augment, Kilo, OpenCode are all too early or too niche for me to commit to. Junie's style learning is neat but I don't notice enough difference to justify learning a new tool. Augment solves enterprise problems I don't have. Kilo is too minimal—I'd rather have Cursor's features. OpenCode breaks too often for real work.

⚠️ Patterns Across All These Tools

  • Open source ≠ free. These tools are free to download but you pay in setup time, troubleshooting, and maintenance. Budget hours for configuration before you see value.
  • Specialization > generalization. Firebase Studio is better at Firebase than Cursor. Goose is better at terminal workflows than Windsurf. Choose tools that match your workflow specifics.
  • Terminal vs GUI is philosophical. Neither is objectively better. Match your tool to your habits. If you live in tmux, terminal tools feel native. If you prefer VS Code, don't force yourself into CLI.
  • Community size matters. OpenHands has momentum—you'll find help. Newer tools like Kilo have small communities, which means less support and slower bug fixes.
  • Multi-model support is table stakes. Any new tool that locks you to one AI provider is making a mistake. The best tools let you swap between Claude, GPT-4, and others based on the task.

Should You Try These?

Here's the decision tree:

You're happy with Cursor but want to stay on official VS Code

→ Try Cline. It's the closest you'll get to Cursor's autonomy without leaving official VS Code.

You prefer terminal workflows and CLI tools

→ Try Goose for general work or Jules if your team has detailed issues/docs.

You want autonomous agents but Devin is too expensive

→ Try OpenHands. Budget a weekend for setup, then enjoy free autonomy.

You're building on Firebase

→ Use Firebase Studio. No other tool understands Firebase this well.

You pair program regularly

→ Try Amp for collaborative sessions with AI as a third participant.

You're already satisfied with your current setup

→ Don't try these. Tool churn is a productivity killer. Master what you have.

Final Thoughts: The Long Tail of Tools

The vibe coding ecosystem has a long tail. Cursor and Windsurf dominate the IDE space. Bolt.new and v0 own rapid prototyping. But these 10 tools serve specific niches that the big players don't address.

Cline exists because some developers won't leave VS Code. Goose exists because some developers live in the terminal. Firebase Studio exists because generalist tools will never understand Firebase as deeply. OpenHands exists because open source matters to some people more than polish.

The question isn't "Which tool is best?" It's "Which tool fits my workflow, constraints, and philosophy?" If you value open source over convenience, OpenHands is better than Devin for you. If you value specialization over breadth, Firebase Studio is better than Cursor for Firebase work.

Most developers don't need more than 2-3 tools: one IDE assistant, one prototyping tool, maybe one autonomous agent. But knowing the long tail exists means you can reach for the right specialized tool when you need it.

Your move: If none of these solve a problem you actually have, don't try them. New tools are exciting, but focus is more valuable than novelty. Revisit this list when you hit a wall with your current tools—then you'll know exactly which one solves your specific pain point.

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📚 Tool Links