We track which developer tools AI models pick across a frozen panel of vibe-coding prompts at every level, from beginners to expert engineers.
“Build a production-grade commerce platform with customer accounts, product catalog management, checkout, order processing, inventory tracking, and discounting. Model products, variants, stock movements, carts, orders, payments, refunds, and fulfillment states explicitly. Enforce role-based separation between shoppers, support agents, and operations staff. Include idempotent order and payment handling, safeguards against overselling, observability for checkout and fulfillment failures, audit logs for price and inventory changes, secure handling of customer and payment-adjacent data, and a rollout strategy for schema changes that preserves historical order records.”
Top recommendations
“Build a production-grade SaaS platform with multi-tenant account isolation, subscription billing, seat-based access, and detailed usage metering. Define clear data models for users, workspaces, entitlements, subscriptions, invoices, and usage events. Enforce role-based permissions across account management and administrative workflows. Include idempotent billing event processing, audit trails for permission and plan changes, observability for checkout and renewal failures, graceful handling of delinquent accounts, and a migration strategy for evolving pricing and entitlement rules without corrupting historical billing state.”
Top recommendations
“Build a production-grade fitness platform with workout tracking, exercise libraries, plans, progress analytics, social challenges, and user-specific goals. Define clear models for workout events, plans, measurements, achievements, and challenge participation. Treat body metrics and health-adjacent data as sensitive user information with strict access rules. Include observability for analytics pipelines, auditability for plan and challenge changes, resilient processing for delayed event ingestion, and careful handling of derived metrics so charts and progress summaries remain consistent as historical workout data changes.”
Top recommendations
“Define a production-grade AI-assisted engineering workflow for a software organization with multiple teams. Specify the agentic IDE / ADE and coding-agent strategy for parallel agent work, mandatory AI code review integrated into pull requests with human sign-off, a testing and CI/CD pipeline with quality gates, a centralized LLM gateway providing routing, rate limiting, caching, and cost controls across providers, and the observability plus evaluation pipelines that trace, monitor, and regression-test LLM behavior before changes ship. Address governance, auditability, and how the toolchain scales across teams without fragmenting standards.”
Top recommendations
“Build a production-ready editorial platform with separate writer, editor, and admin permissions. Support rich article authoring, content previews, scheduled publishing, comment moderation, subscriber lifecycle management, and search across published content. Model revisions, publication states, taxonomy, comments, and subscriber data explicitly. Include audit logs for content changes, resilient scheduling and email delivery, rollback support for publishing mistakes, observability for indexing and newsletter jobs, and security controls that protect unpublished drafts and subscriber data.”
Top recommendations
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