Compare Code AI Tools 2026

Raydian

Freemium

Most AI app builders give you a prototype. Raydian gives you a production app.Raydian is an AI-first full-stack development platform that turns natural language into deployed web applications. You describe what you want through a chat interface. The AI agent asks clarifying questions about goals, scope, and constraints. Then it builds—not a mockup, but a working app with backend, database, authentication, and hosting already wired up.The key difference from tools like Bolt or Lovable: Raydian follows a structured development process. It plans, builds, tests, and iterates on each feature rather than generating everything in one shot. That structured approach reduces the "AI slop" problem where generated code looks right but breaks under real usage.Everything runs on Cloudflare's edge infrastructure, which means sub-50ms response times globally without you configuring CDNs or regions. The database is edge-ready by default. Authentication works out of the box.The visual editor lets you override AI decisions without touching code. But if you want code access, it is there—full source code, not a locked-down drag-and-drop jail.Honest LimitationsRunning locally requires Cloudflare as the backend. You cannot swap in a different hosting provider. The "structured approach" that helps experienced builders may overwhelm absolute beginners who have never seen a database schema. And the free tier's 100-prompt limit runs out fast if you are iterating on a complex app.Who It Is ForNon-technical founders who want more control than Bubble but less complexity than coding from scratch. Developers who want AI acceleration without giving up code access. Teams that need built-in collaboration with branch-based version control.For more AI coding tools, browse our full directory at tools.skila.ai. For open-source alternatives, check repos.skila.ai.

Cerebras

Freemium

The fastest AI inference platform — 20x faster than OpenAI and Anthropic

Cerebras is an AI inference platform built on the Wafer-Scale Engine, a purpose-built chip that delivers inference speeds 20x faster than GPU-based competitors like OpenAI and Anthropic. If you have ever waited seconds for a long response from GPT-4 or Claude, Cerebras eliminates that bottleneck entirely. The platform serves popular open-source models including Llama, Qwen, DeepSeek, Mistral, and GLM through a drop-in OpenAI-compatible API, meaning you can switch your existing code with a single base URL change. The free tier is genuinely generous: unlimited access to all Cerebras-powered models with community Discord support, making it one of the best ways to experiment with fast inference at zero cost. The Developer tier adds 10x higher rate limits and priority processing starting at just $10 self-serve. Enterprise customers get dedicated queue priority, custom model weights, fine-tuning services, and guaranteed uptime with a dedicated support team. Cerebras Code Pro offers a $50/month plan with 24 million tokens per day, ideal for indie developers, and a $200/month Max plan with 120 million tokens per day for heavy coding workflows and multi-agent systems. Cerebras has landed major enterprise customers including OpenAI (for low-latency inference), Meta, GSK, Mayo Clinic, AlphaSense, and Notion. The recent AWS partnership brings Cerebras inference to AWS Marketplace and Bedrock, making it accessible through existing cloud billing. Additional integrations with OpenRouter, Hugging Face, and Vercel make adoption straightforward for any stack. The main limitation is the model selection: you are restricted to supported open-source models, with no access to proprietary models like GPT-4 or Claude. For teams that need raw speed on open models, though, nothing else comes close.

OpenCode

Free

The open-source AI coding agent with 120K GitHub stars that runs in your terminal, desktop, and IDE

OpenCode is a free, open-source AI coding agent built by the team behind SST (Serverless Stack) that brings intelligent coding assistance to your terminal, desktop, and IDE. With over 120,000 GitHub stars, 800 contributors, and 5 million monthly developers, it has rapidly become one of the most popular developer tools on GitHub. OpenCode connects to 75+ AI models through Models.dev, including Claude, GPT-4, Gemini, and local models via Ollama, so you are never locked into a single provider. The tool ships with two built-in agents: Build Agent for full-access development work including file edits, command execution, and code generation, and Plan Agent for read-only analysis and code exploration without making changes. What sets OpenCode apart from commercial alternatives like Claude Code, Cursor, and GitHub Copilot is its privacy-first architecture. No code or context data is stored or shared, making it suitable for enterprise and privacy-sensitive environments. The automatic LSP integration connects to language servers for Rust, Swift, TypeScript, Python, Terraform, and more, giving the AI deep understanding of your codebase without manual configuration. OpenCode supports multi-session parallel agents, session sharing via links, and auto-compact conversations when approaching context limits. It stores session history locally via SQLite. Installation takes one command via curl, npm, Homebrew, or Go install. The desktop app is currently in beta for macOS, Windows, and Linux, while IDE extensions work with VS Code and Cursor. For developers who want full control over their AI coding tools without subscription fees, OpenCode delivers a remarkably capable experience at zero cost.

Cursor

Freemium

The AI-first code editor built for pair programming with agents

Cursor is an AI-native code editor built on top of Visual Studio Code that deeply integrates large language models into every aspect of the development workflow. Unlike traditional editors with bolt-on AI plugins, Cursor was architecturally designed around AI from the ground up, offering intelligent code completion, multi-file editing, autonomous agents, and full codebase understanding out of the box. At its core, Cursor features a proprietary Tab model that delivers context-aware autocomplete by predicting not just the next token but the developer's next action with striking accuracy and speed. The Agent mode takes this further by operating autonomously — building, testing, and demoing features end to end for the developer to review. Composer enables multi-file edits from natural language prompts, making large refactors and feature implementations dramatically faster. Cursor supports every major frontier model including Claude Opus 4.6, GPT-5.2, Gemini 3 Pro, and xAI's Grok Code, as well as Cursor's own proprietary models. Developers can choose the best model for each task or bring their own API keys for maximum flexibility. The editor provides complete codebase understanding through semantic indexing that scales to massive enterprise codebases. Additional capabilities include BugBot for automated GitHub pull request reviews, cloud agents accessible from any browser, MCP (Model Context Protocol) app integrations, Slack integration for team collaboration, and CLI support. Cursor is trusted by over half of the Fortune 500 and reports over 90% adoption at companies like Salesforce and NVIDIA. With SOC 2 certification, enterprise-grade security controls, and team collaboration features, Cursor has rapidly become the leading AI code editor for both individual developers and large engineering organizations.

Open-source AI pair programmer that lives in your terminal and commits to Git

Aider is an open-source AI pair programming tool that operates directly in your terminal, enabling developers to collaborate with large language models to write, edit, and refactor code across entire repositories. Rather than offering a graphical IDE or browser-based interface, Aider embraces the command line as its native environment, making it a natural fit for developers who already live in the terminal and rely on Git for version control. What sets Aider apart from other AI coding assistants is its deep Git integration. Every change the AI makes is automatically staged and committed with a descriptive commit message, creating a clean audit trail that makes it trivial to review, diff, or undo any modification. This stands in sharp contrast to tools that require manual copy-pasting of AI-generated snippets or leave developers to manage their own version control around AI edits. Aider builds an internal map of your entire codebase, allowing it to reason about file relationships and make coordinated multi-file edits. It supports over 100 programming languages including Python, JavaScript, TypeScript, Rust, Go, C++, Ruby, and PHP. The tool works with virtually any LLM provider, from frontier models like Claude 3.7 Sonnet, GPT-4o, and DeepSeek R1 to locally hosted models through Ollama, giving developers full control over cost and privacy tradeoffs. The project has earned strong community validation with over 41,000 GitHub stars and 5.3 million pip installations. Aider processes roughly 15 billion tokens per week across its user base, and remarkably, 88 percent of the new code in its latest release was written by Aider itself. Additional capabilities include voice-to-code for hands-free coding, automatic linting and test execution on AI-generated code, support for images and web pages as context, and integration with IDE editors through code comments. Aider is completely free to use, with costs determined solely by your choice of LLM API provider, typically averaging around 70 cents per coding command when using frontier models.

AI code reviews that catch bugs before your teammates do

CodeRabbit is an AI-powered code review platform that automatically analyzes pull requests and provides actionable feedback within minutes. It identifies bugs, security vulnerabilities, and style issues while explaining the reasoning behind each suggestion. Engineering teams report cutting review turnaround time by 50% or more.

Replit

Freemium

The cloud IDE where AI Agent 3 autonomously builds, tests, and deploys full-stack apps from plain English

Replit is a cloud-based integrated development environment that has evolved from a collaborative coding playground into one of the most powerful AI-driven application builders available today. Its flagship capability, Agent 3, represents a paradigm shift in software creation: users describe what they want in natural language and the agent autonomously writes code, provisions databases, configures deployments, and iterates on the result for up to 200 minutes per session with minimal human oversight. What sets Replit apart from desktop-based AI coding tools is the zero-setup experience. Everything runs in the browser -- there is nothing to install, no local environment to configure, and no dependency conflicts to resolve. The platform supports over 50 programming languages including Python, JavaScript, TypeScript, Go, Rust, and Java, with built-in PostgreSQL databases, key-value stores, and one-click deployment to production URLs. This makes Replit uniquely accessible to both experienced developers who want to prototype rapidly and non-technical builders who have never written a line of code. Agent 3 is 10x more autonomous than its predecessor. It employs a self-healing loop where it periodically opens the app in a browser, tests buttons, forms, API endpoints, and data flows, then automatically fixes any issues it detects. This proprietary testing system is reportedly 3x faster and 10x more cost-effective than computer-use-based testing models. The agent can also build other agents and automations, enabling users to create Telegram bots, Slack integrations, scheduled tasks, and multi-step workflows entirely through conversation. Mobile app development arrived as a major addition in late 2025. Replit Agent can now scaffold and preview native iOS and Android applications using Expo, letting users scan a QR code to see their app running on a physical device within minutes. Combined with built-in version control, real-time multiplayer editing for up to 15 collaborators, and instant deployment, Replit collapses the traditional development lifecycle into a single browser tab. The platform's growth metrics underscore its market traction. Replit went from $16 million in annual recurring revenue at the end of 2024 to an estimated $150 million by September 2025, with a $3 billion valuation that has since reportedly climbed toward $9 billion on a $400 million funding round. SaaStr documented 750,000 uses across 10-plus production applications built entirely through vibe coding on Replit, and enterprise customers like Rokt have demonstrated building 135 internal tools in a single 24-hour sprint. MIT Technology Review named generative coding one of its 10 Breakthrough Technologies of 2026, citing platforms like Replit as central to the shift where humans define intent while machines write the code. Replit restructured its pricing in February 2026. The free Starter tier includes limited daily Agent credits and 1,200 development minutes per month. Core dropped to $20 per month and includes $25 in monthly usage credits covering AI, compute, and deployments, plus the ability to invite up to five collaborators. The new Pro plan at $100 per month supports up to 15 builders with tiered credit discounts, priority support, and credit rollover. Enterprise pricing is available on request for organizations requiring SSO, SCIM, advanced security, and compliance controls. For anyone looking to go from idea to deployed application in the shortest possible time, Replit delivers a compelling all-in-one platform that removes infrastructure complexity and lets AI handle the heavy lifting.

Augment Code

Paid

AI coding agents that understand your entire codebase

Augment Code is an AI-powered software development platform built around a proprietary Context Engine that maintains a live semantic understanding of your entire codebase, including dependencies, architecture patterns, and git history. Unlike competitors that rely solely on foundation models with limited context windows, Augment indexes your full repository so its agents produce code that actually follows your project conventions and reuses existing abstractions instead of reinventing them. The platform works across VS Code, JetBrains IDEs, and a standalone CLI, with agents capable of handling multi-file refactoring, automated code review via inline GitHub comments, and coordinated task orchestration through its Intent workspace. Augment ranked first on the SWE-Bench Pro Leaderboard at 51.80% and outperformed human developers on 500 Elasticsearch pull requests across correctness, completeness, and code reuse metrics. The company raised $252 million from investors including Index Ventures, Lightspeed, and Eric Schmidt's Innovation Endeavors, reaching a near-unicorn valuation of $977 million. Pricing starts at $20 per month for individual developers with 40,000 credits, scaling to $60 per developer for teams with pooled credits and the full agent suite. The credit-based model replaced earlier message-based pricing in late 2025. Initial codebase indexing can take two to four hours on very large projects, and IDE support is currently limited to VS Code and JetBrains, so Neovim and Emacs users are out of luck. The code review feature achieves 65% precision, meaning roughly two out of three comments surface genuine issues rather than style nits. Augment holds SOC 2 Type II certification and is the first AI coding assistant with ISO/IEC 42001 compliance, making it a strong pick for enterprise teams with strict security requirements.

Gemini CLI

Freemium

Google's free, open-source AI coding agent that runs Gemini 2.5 Pro directly in your terminal

Gemini CLI is Google's open-source command-line AI agent that puts Gemini 2.5 Pro and its 1 million token context window directly in your terminal. Unlike IDE-based AI assistants, Gemini CLI works wherever you already work: bash, zsh, or any shell environment. You install it with a single npm command, sign in with your Google account, and start prompting immediately. No credit card, no subscription, no API key required for the free tier. The free tier is genuinely generous. Google provides 60 requests per minute and 1,000 requests per day at zero cost, which Google says is double the highest usage they observed in internal developer testing. That means most individual developers will never hit the limit during normal coding sessions. If you do need more, you can plug in a Google AI Studio API key for pay-as-you-go pricing or connect a Vertex AI account for enterprise workloads. Gemini CLI ships with a practical set of built-in tools: file read and write, shell command execution, web content fetching, and Google Search grounding. That last one is significant because it means the model can look up current documentation and API references mid-conversation instead of relying solely on its training data. You can extend its capabilities further through MCP (Model Context Protocol) servers, connecting it to databases, APIs, or custom tooling. Conversation checkpointing lets you save and restore sessions, which is useful for long-running refactoring tasks or when you need to pause work and come back later. The /restore command reverts your project files to the checkpointed state and reloads the full conversation history. GEMINI.md files work like system prompts scoped to your project directory, so you can define coding standards, preferred patterns, or project context that persists across sessions. The project is fully open source under Apache 2.0, hosted on GitHub with over 95,000 stars, making it one of the fastest-growing developer tools in recent memory. Weekly stable releases ship through three channels: stable, preview, and nightly. The community is active and Google maintains the project with regular feature additions, including recent work on an experimental browser agent and the /plan command for structured task breakdowns. Where Gemini CLI falls short compared to Claude Code or Cursor is in multi-file edit sophistication. It handles single-file changes well but can sometimes struggle with coordinated refactors across many files. The terminal-only interface also means no visual diffing or inline code suggestions, which IDE-integrated tools handle better. For developers who prefer visual feedback, this is a real tradeoff. But for terminal-native workflows where cost matters, Gemini CLI is hard to beat on value.

Google AI Studio

Freemium

Build and prototype with Google's Gemini models — free tier included

Google AI Studio is Google's browser-based development environment for building, testing, and deploying applications powered by Gemini AI models. It provides a visual playground for experimenting with prompts, fine-tuning models on custom data, and generating API keys for production use — all without installing anything locally. The platform offers access to the full Gemini model family, including Gemini 3.1 Pro Preview (the most capable), Gemini 3.1 Flash-Lite (fastest), and legacy 2.5 models. A generous free tier gives developers access to all models with free input and output tokens for experimentation and prototyping, making it one of the most accessible ways to start building with frontier AI models. Google AI Studio 2.0 pushed the platform significantly forward in early 2026 by adding full web app prototyping capabilities with built-in Firebase integration, secrets management, and collaborative scaffolding. Developers can now go from prompt to deployed prototype without leaving the browser. The platform also supports multimodal inputs — text, images, audio, video, and code — across all Gemini models. Paid tier pricing is competitive: Gemini 3.1 Flash-Lite starts at just $0.25 per million input tokens, while the flagship Gemini 3.1 Pro Preview is $2.00 per million input tokens (with 50% batch discounts available). Additional features include context caching for repeat queries, Google Search grounding for fact-checked responses, Imagen 4 image generation ($0.02-$0.06 per image), and Veo 3 video generation ($0.15-$0.40 per second). For developers already in the Google ecosystem, AI Studio integrates directly with Firebase, Google Cloud, Google Workspace, and Vertex AI for enterprise deployment. The API follows the same interface as Vertex AI, making it easy to move from prototype to production.

Qodo

Freemium

The AI code reviewer that catches the bugs your AI wrote.

Your AI writes the bug. Qodo catches it. That is the whole pitch, and in 2026 it is a bigger deal than it sounds. Qodo (formerly CodiumAI) is an AI code-review and test-generation platform built for a world where most code is now AI-generated. It plugs into your pull-request flow on GitHub, GitLab, and Bitbucket, and into your editor through VS Code and JetBrains. Open a PR and Qodo reads it the way a senior engineer would: it flags logic gaps, security issues, and standards violations, then explains why each one matters with full repo context — not just the diff. The part that sets it apart is the review architecture. Qodo runs 15+ agentic workflows that scale across a PR — bug detection, test-coverage validation, documentation checks — instead of a single pass that skims the surface. In one published benchmark against seven rival reviewers, Qodo's multi-agent approach posted the highest F1 score (60.1%), the metric that balances catching real issues against drowning you in false positives. A reviewer that cries wolf gets muted; one that misses bugs is useless. The F1 number is where that trade-off lives. Test generation is the other half. Qodo analyzes a function, reasons about edge cases, and writes tests that actually exercise them — the boring, high-value work developers skip under deadline. There is also a living rules system: you define your team's coding standards once, and Qodo enforces them on every PR so the bar doesn't drift as the team grows. The timing is the point. The Faros AI Engineering Report 2026 found bugs per developer up 54% as AI-generated code flooded codebases. Qodo is built for exactly that back-of-the-pipeline problem: not generating more code, but catching what the generators got wrong before it reaches production. If you are assembling a stack, our roundup of the best AI coding tools separates the generators from the guardrails, and the open-source agent OpenHands shows why the guardrails matter — autonomous agents out-produce humans, which means they out-bug them too.

Kilo Code

Freemium

The open-source coding agent that mass-uninstalled Copilot across 1.5 million developers

Kilo Code started as a fork of Cline and Roo Code. Nine months and $8 million in seed funding later, it processes over 25 trillion tokens and sits on 1.5 million desktops. That trajectory alone should make you pause. Here's what makes it different: Orchestrator mode. You describe a task — 'refactor the auth module to use OAuth2' — and Kilo splits it into coordinated subtasks across a planner agent, a coding agent, and a debugger agent. Each subtask runs in parallel. The planner maps architecture, the coder writes implementation, the debugger catches issues before you even see the diff. It's not autocomplete pretending to be agentic. It's actual multi-agent orchestration inside your IDE. You get access to 500+ AI models at provider rates. No markup. Claude Sonnet 4.6, GPT-5, Gemini, Llama — all at the same price you'd pay the API directly. New users get $20 in free credits without setting up any API keys. Memory Bank stores your architectural decisions, coding patterns, and team conventions. Open a new session weeks later and the agent remembers your project structure, your preferred patterns, your naming conventions. It onboards new team members automatically. The extension runs on VS Code, JetBrains, and CLI. Inline autocomplete, browser automation for testing, automated PR reviews, and a visual app builder that generates production code from descriptions. The GitLab co-founder built this because existing tools felt like smart autocomplete rather than actual engineering partners. The weakness: Orchestrator mode burns through tokens fast on complex tasks. A heavy refactoring session can run $15-25 in API costs. And because it forked from Cline, some UI patterns still feel borrowed rather than native.

Free AI coding superpowers — unlimited completions, no credit card

Codeium is a free AI coding assistant that offers unlimited completions, chat, and search with no usage caps for individual developers. It supports 70+ programming languages and integrates with all major IDEs. Codeium's context-aware suggestions draw from your open files and recent edits to produce relevant, project-specific completions.

Android Studio Panda 4

Freemium

Google's AI-agent Android IDE with Planning Mode, Next Edit Prediction, and a Gemini API starter template.

Android devs have been starving. Every headline AI IDE in 2026 — Cursor, Windsurf, Cline, Zed — targets web and Python. Android project structure is a second-class citizen in all of them. Meanwhile, Android Studio Panda 4 shipped on April 22, 2026 with four features that finally make an AI-agent IDE feel native to Android.The Four Features That MatterPlanning Mode. You describe a change. The agent drafts a multi-step plan. You review. You approve. The agent executes against a tracked task list across files. This is the pattern Claude Code and Cursor use for large refactors — Panda 4 is the first Android-native implementation.Next Edit Prediction. This is the killer feature. When you edit a constructor, Panda 4 predicts the follow-up changes your data class, your tests, and your DI module will need. It does not just suggest the next line — it suggests the next file. Cursor has a version of this. Cursor does not know Android data classes the way Panda 4 does.Agent Web Search. The agent can search Android docs, Stack Overflow, and Kotlin docs inline during a task. No tab-hopping. The agent reads, summarizes, and cites inside your task panel.Gemini API Starter Template. A single-click new-project template that ships with Firebase AI Logic preconfigured for multimodal input (text + image + audio). If you are building a Gemini-powered Android app, this saves a weekend of SDK wiring.Who Should Use ItUse Android Studio Panda 4 if you ship native Android apps and you have been jealous of the Cursor experience every time you opened Twitter. This is the closest thing to Cursor that actually understands Android project structure. It is free. It is from Google. It ships as a preview channel of official Android Studio.Skip it if you build Flutter, Kotlin Multiplatform, or React Native apps — Panda 4 is Android-native only. Also skip it if you are running a production pipeline today; it is still Preview/Canary, so expect bugs.PricingThe IDE is free. You pay for Gemini API calls at standard Google AI Studio rates. For hobby and small-team use, the free Gemini tier covers most agent runs. For heavy daily use, expect $10-50/month in API charges depending on how often you invoke Planning Mode.No license. No per-seat fee. No subscription. That matters — Cursor charges $20/month, Windsurf charges $15/month, and Android Studio Panda 4 is $0.VerdictIf you ship Android apps, install Panda 4 this week. The Planning Mode + Next Edit Prediction combination is a real 20-30% productivity gain for typical feature work. The Gemini API starter template is a genuine time-saver on any new AI-powered Android project.The 80 Product Hunt upvotes are small but telling — Android devs noticed, and they showed up.Related ResourcesArticle: GPT-5.5 just shipped — the agentic model wars that Panda 4 plugs directly into.Repo: Microsoft MarkItDown — convert specs and PDFs to Markdown before feeding them into Panda 4's Planning Mode.MCP server: Figma Context MCP — pipe Figma designs into Panda 4 or any agent IDE for real design-to-code on mobile.Skill: Awesome Claude Code Toolkit — 135 agents and 35 skills for the teams that pair Panda 4 with Claude Code workflows.

ByteDance built a free AI IDE that made a team of 12 mass-uninstall Cursor overnight

Trae processed a 47,000-line codebase refactor in 8 minutes during internal ByteDance testing. That stat leaked on Twitter and the IDE picked up 200,000 downloads in its first month. You already know the AI IDE landscape is crowded. Cursor costs $20/month. Windsurf wants $15. GitHub Copilot charges $10 just for autocomplete. Trae walks in at $0 and drops a Builder agent that autonomously breaks down multi-file tasks, runs terminal commands, previews results, and lets you approve or reject every step. The Builder mode is where Trae separates itself. You describe what you want in plain English — "add authentication with Google OAuth to this Next.js app" — and the agent plans the implementation across files, installs dependencies, writes code, and tests it. You watch the whole process in a split pane and intervene when it drifts. It's like pair programming with an engineer who never gets tired and never argues about tabs vs spaces. Trae supports 100+ programming languages with deep proficiency in Python, Go, TypeScript, Java, Rust, and C++. The autocomplete is fast — sub-200ms latency on M-series Macs. It reads images (paste a screenshot, get code), understands your full workspace context, and supports MCP for connecting external tools. The catch? It's ByteDance. Your code is processed on their servers (with regional data isolation in Singapore, Malaysia, and US). If your company has strict data residency requirements, that's a hard stop. Linux support is also still missing — macOS and Windows only for now. For solo developers and small teams who want Cursor-level AI assistance without the subscription, Trae is the most aggressive free offer in the market right now.

Zencoder

Freemium

The mindful AI coding agent that edits across your whole repo and validates its own code.

Zencoder isn't another chat-on-the-side coding tool. It's an agentic IDE plugin that understands your entire repository, edits multiple files in one go, and runs multiple AI models to verify every change before it lands. Install it in VS Code or JetBrains and you get a Coding Agent that follows your naming conventions and design patterns across 70+ languages, a Testing Agent that writes unit and E2E tests grounded in your frameworks, and an Ask Agent that answers "How does auth work?" with references to exact files and functions. Every output goes through multi-model verification: Claude reviews code written by GPT, Gemini audits the test suite. That model diversity catches errors a single model would miss and cuts down false positives. You get transparent reasoning for every suggestion—why that approach, what alternatives were considered, how it ties back to your codebase. Workflows are first-class. Spec and Build captures the approach and plan, then lets agents build with checkpoints so you review at each stage. Full SDD (Spec-Driven Development) generates PRDs, technical specs, and implementation plans with multiple agents in parallel and AI code review. You can define custom workflows to enforce quality gates, security checks, and review standards. Connect Linear, Jira, or GitHub Issues and agents turn tickets into implementation-ready pull requests. Drop in a stack trace and they trace execution, isolate the root cause, and propose a targeted fix. Multi-repo indexing keeps code patterns and dependencies in sync across all your repositories with daily updates. Safe multi-file refactors—rename symbols, extract modules, restructure APIs—propagate across every affected file with verification that nothing breaks. Free 7-day trial, no credit card. Pricing scales from free to $250/month for teams.