Preseason
Open-source benchmark of devtool choices, ranked by LLM
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What is Preseason?
Preseason is an AI agent benchmarking platform that tracks what tools and frameworks AI models select when building applications. The platform uses a frozen panel of 'vibe-coding' prompts at every skill level, from beginners to expert engineers, to measure which devtools different AI models consistently pick.
Key features include tracking AI model tool selections across multiple advanced prompts (AI Support Agent Platform, SaaS Application, E-commerce Store, AI Revenue Ops Copilot, Online Learning Platform), displaying top recommendations with percentage breakdowns for each prompt, and showing active matches that compare competing tools like Auth0 vs Clerk (66%/34%), PostgreSQL vs Supabase (67%/33%), Prisma vs TypeORM (90%/10%), and Stripe vs Shopify Payments (97%/3%).
Preseason is designed for AI developers, machine learning engineers, technical decision-makers evaluating AI agents, and anyone interested in understanding which tools AI models naturally prefer. The platform helps identify dominant tooling patterns in AI-generated code and provides visibility into AI agent behavior across different development scenarios.
Preseason pricing
Pricing model: Freemium
The website does not display explicit pricing information. No free tier details, paid plan costs, or subscription tiers are visible on the main page. Pricing details, free tier availability, and paid plan options are not mentioned in the visible content.
Preseason pros
- Tracks AI model tool selections across standardized prompts
- Covers skill levels from beginners to expert engineers
- Provides percentage breakdowns for top tool recommendations
- Shows active matches comparing competing tools side-by-side
- Uses frozen panel of prompts for consistent benchmarking
- Covers multiple advanced application types (SaaS, e-commerce, AI agents)
- Reveals which devtools different AI models prefer
- Displays clear visualization of tool preference percentages
- Helps identify dominant patterns in AI-generated code
- Provides transparency into AI agent decision-making
- Covers essential categories: authentication, database, ORM, payments, hosting
- Updates matches showing real-time preference data
- No setup required - ready-to-use benchmarking panel
- Helps developers understand AI tool bias
- Supports evaluation of AI agents for production use
Preseason cons
- Limited to vibe-coding prompts only
- No customizable prompt creation feature
- Does not track performance or quality of generated code
- No historical trend data visible
- Limited to specific tool categories shown
- No export functionality for data
- Does not evaluate non-AI development workflows
- No API access mentioned for integration
Frequently asked questions about Preseason
What does Preseason track?
Preseason tracks what tools AI models pick across a frozen panel of vibe-coding prompts at every level, from beginners to expert engineers. It measures which devtools different AI models consistently select when building applications.
What are vibe-coding prompts?
Vibe-coding prompts are standardized building prompts used to test AI agents. Preseason uses a frozen panel including advanced prompts like AI Support Agent Platform, SaaS Application, E-commerce Store, AI Revenue Ops Copilot, and Online Learning Platform.
What skill levels does Preseason cover?
Preseason covers every skill level from beginners to expert engineers, ensuring the benchmarking is relevant across the full spectrum of development experience.
What tool categories does Preseason track?
Preseason tracks essential development categories including Authentication (Auth0 vs Clerk), Database (PostgreSQL vs Supabase), ORM/Data Access (Prisma vs TypeORM), Email (SendGrid vs Resend), Payments (Stripe vs Shopify Payments), File Storage (AWS S3 vs Cloudflare R2), Hosting/Deployment (Vercel vs AWS), CSS/Styling (Tailwind CSS vs Infima), UI Components (shadcn/ui vs MUI), State Management (TanStack Query vs Zustand), API Framework, and CMS (Sanity vs Contentful).
What are Active Matches?
Active Matches show real-time comparisons between competing tools with percentage breakdowns. Examples include Authentication at 66%/34% (Auth0 vs Clerk), Database at 67%/33% (PostgreSQL vs Supabase), and Payments at 97%/3% (Stripe vs Shopify Payments).
How does Preseason ensure consistent benchmarking?
Preseason uses a frozen panel of prompts that doesn't change, ensuring consistent and comparable benchmarking results across different AI models and evaluation periods.
What is the top recommendation for SaaS Application prompts?
For SaaS Application prompts, the top recommendations are Stripe at 13.4%, Prisma at 10.7%, PostgreSQL at 9.3%, and AWS at 7.1%.
Which tool dominates the Payments category?
Stripe dominates the Payments category with 97% preference compared to Shopify Payments at only 3%.
What AI agent types are tested?
Preseason tests AI agents building production-grade platforms including AI Support Agent Platforms with authentication and escalation, SaaS Applications with multi-tenant isolation and billing, E-commerce Stores with inventory and order processing, AI Revenue Ops Copilots ingesting CRM data, and Online Learning Platforms with enrollment and certification.
Who should use Preseason?
Preseason is designed for AI developers, machine learning engineers, technical decision-makers evaluating AI agents for production use, and anyone interested in understanding which tools AI models naturally prefer when building applications.