Why I use Cline - a free VS Code plugin - for AI engineering. @thankscline has:

Flexible context management: It lets you include only what's relevant, making it ideal for large codebases. Attach files, folders, URLs and problems. Visualizes how much of the context window you've used too.

Model flexibility: Cline isn't tied to one provider; it supports models from Anthropic, DeepSeek, Google Gemini, OpenAI, local models (via @ollama or @lmstudio) and more, allowing you to switch models for cost efficiency and capability.

Plan/Act Modes: The v3.2.6 update introduces modes for designing solutions (Plan) or direct implementation (Act), providing control when you need it most.

DeepSeek-R1 (Plan) + Claude 3.5 Sonnet (Act) workflow: This hybrid approach can reduce costs by up to 97% while improving output quality. DeepSeek as an architect, Sonnet for implementation.

Checkpoints: Beyond git, Cline captures workspace states, offering granular rollback and comparison, especially useful for exploring solutions or debugging.

Runtime awareness: Cline's integration with running systems is a game-changer, allowing real-time interaction with browsers (automatically check UI, interactions) and terminals to verify changes.

Model Context Protocol (MCP): This allows for custom tool integration, making Cline extensible for specific enterprise needs without complex prompt engineering.

How does it compare to alternatives? Cline shines with its system-level integration, model flexibility, and control, though it requires more attention to model selection and cost.

My take: Cline aligns with professional engineering practices, offering control, visibility, and extensibility for complex system development. Totally worth considering for serious engineering teams.