Claude Code
Claude Code is an AI-powered coding agent designed to work directly inside your existing development environment. It goes beyond simple autocomplete by understanding entire codebases and helping developers build, debug, refactor, and ship features faster. Developers can interact with Claude Code from the terminal, IDEs, Slack, or the web, making it easy to stay in flow without switching tools. By describing tasks in natural language, users can let Claude handle code exploration, modifications, and explanations. Claude Code can analyze project structure, dependencies, and architecture to onboard developers quickly. It integrates with common command-line tools, version control systems, and testing workflows. This makes it a powerful companion for both individual developers and teams working on complex software projects.
Learn more
BLACKBOX AI
BLACKBOX AI is an advanced AI-powered platform designed to accelerate coding, app development, and deep research tasks. It features an AI Coding Agent that supports real-time voice interaction, GPU acceleration, and remote parallel task execution. Users can convert Figma designs into functional code and transform images into web applications with minimal coding effort. The platform enables screen sharing within IDEs like VSCode and offers mobile access to coding agents. BLACKBOX AI also supports integration with GitHub repositories for streamlined remote workflows. Its capabilities extend to website design, app building with PDF context, and image generation and editing.
Learn more
Muse Spark 1.2
Muse Spark 1.2 is Meta’s coding-focused model update designed to power Muse Code and improve software engineering workflows. The model is built for code generation, complex debugging, codebase understanding, long-horizon development tasks, and end-to-end developer workflows. Muse Spark 1.2 was co-trained with Muse Code to improve performance inside the terminal coding agent environment. It supports planning, goal conditioning, context compaction, subagent coordination, and iterative coding workflows across large repositories. The model was trained with expanded coding compute, diverse development environments, self-improvement loops, and long-running engineering tasks. Built for AI developers and software teams, Muse Spark 1.2 helps agents plan, write, validate, debug, and optimize code with greater autonomy.
Learn more
SWE-2
SWE-2 is Cognition’s advanced coding model designed to improve software engineering performance while reducing the cost of agentic coding workflows. The model is post-trained from Kimi K3 and uses reinforcement learning to optimize multiple reasoning-effort levels within a single training run. SWE-2 is designed to explore codebases more selectively, begin implementation sooner, and complete tasks with fewer redundant reads and reasoning steps than earlier Cognition models. Its capabilities include code generation, debugging, test creation, verification, repository analysis, and complex terminal-based software engineering tasks. The model also emphasizes stronger engineering judgment, end-to-end test coverage, instruction following, and evidence-based verification of user assumptions. SWE-2 is available through Devin Desktop and Devin CLI, with broader rollout planned across Devin Web and Fusion.
Learn more
