At Playtomic, we believe in sharing our engineering journey with the broader tech community. Recently, we conducted a comprehensive experiment to compare Claude Code against our existing standard, Cursor, to evaluate how they fit into our diverse development workflows. This follows our previous experiment with AI code review tools, where we evaluated tools like BugBot, CodeRabbit, and GitHub Copilot. After an intensive six-week trial during September and October 2025, we gathered some valuable insights that we hope will help other teams navigating similar decisions. The Experiment The goal of this experiment was to evaluate Claude Code as a potential alternative to Cursor. We wanted to determine if Claude Code offered significant advantages in productivity, code quality, or developer experience that would justify a transition. Methodology: We selected a diverse group of 8 developers across different stacks (4 Backend, 2 Frontend, and 2 Mobile Engineers). This group used Claude Code exclusively as their primary AI tool for the duration of the experiment, while the rest of the engineering team continued using Cursor. Key Objectives: Compare effectiveness in real-world development scenarios. Evaluate developer productivity and satisfaction. Assess the relevance and quality of code suggestions. Analyze the cost-effectiveness and ROI of both tools. Key Findings The feedback from our pilot group revealed distinct preferences based on the development stack: Frontend & Mobile Development Our Frontend and Mobile engineers expressed a strong preference for Cursor. The key differentiator was Cursor’s superior IDE integration and autocompletion features. For these workflows, the immediate, context-aware suggestions provided by Cursor were critical for maintaining flow and velocity. Backend Development The results were more nuanced for Backend development. While there was a slight preference for Claude Code, primarily due to its powerful agent capabilities, the gap was not as significant. Backend developers valued the agentic nature of Claude for complex tasks but found they could be flexible with their tool choice. Shared Learnings & Workflow Insights Beyond tool preference, the experiment surfaced several valuable insights about AI-assisted development: Plan Mode is the sweet spot: Across all teams, “Plan Mode” (or spec-first development) was identified as the most effective workflow, sitting comfortably between full agent autonomy and simple chat queries. Context is King: The quality of results is directly proportional to the quality of the context provided. “Garbage in, garbage out” remains the rule, requiring developers to actively manage and clean their context. Parallel Brainstorming: The ability to run subagents in parallel to explore multiple solution paths was highlighted as a powerful capability for complex problem-solving. Code Quality Watch-outs: We observed a tendency for AI tools to create monolithic code or reinvent existing utilities. Developers need to remain vigilant and explicitly prompt for componentization and reuse. Cost Comparison After tracking costs across both tools for approximately 1.5 months, the data reveals comparable overall expenses: Token consumption dynamics: While Claude offers a competitive cost per token, its agentic workflow tends to consume significantly more tokens per task. When combined with Cursor’s availability of very affordable models, Claude Code can be less cost-effective for certain workflows. Variable usage patterns: Some users have exceeded the equivalent monthly cost of Cursor when using Claude Code’s API-based pricing model, spending up to $150 monthly Cost balancing effect: The API-based nature of Claude Code means a big part of users fall below Cursor’s fixed monthly fee, creating a natural balance In short, both tools are proving to be in a similar order of magnitude when viewed across the entire team. While it remains challenging to project the exact total financial impact at a company-wide scale, the choice between the two may ultimately depend more on feature preferences, workflow integration, and user experience rather than significant cost differences. The Verdict: Standardizing on Cursor After analyzing the results, we have decided that Cursor will remain the officially supported tool for all development stacks at Playtomic. Why Cursor? Unified Tooling: Standardizing on a single tool reduces complexity in team collaboration, knowledge transfer, and onboarding for new members. Multi-Model Support: Cursor provides access to multiple AI models. This is a strategic advantage that allows our developers to leverage the best-performing models (including Claude) regardless of which provider is currently leading the market, effectively future-proofing our tooling investment. Lower Switching Costs: Since Cursor is already widely adopted across our teams, we benefit from existing familiarity and configurations. IDE Experience: For a significant portion of our team (Frontend and Mobile), the IDE features of Cursor are indispensable. Individual Flexibility While Cursor is our official standard, we recognize that developer tooling is personal. We are adopting a flexible approach that allows developers who strongly prefer Claude Code to continue using it, ensuring we balance organizational consistency with individual autonomy.