About ContradictMe
By Liz Stein • Published
ContradictMe is an AI project built to help people think through difficult topics by seeing the strongest case for the other side. Most online systems optimize for agreement and engagement. This project does the opposite. It prioritizes constructive disagreement so users can test their assumptions, identify blind spots, and improve judgment.
Features Overview
- Intelligent Chat Interface: Natural conversations with context-aware follow-up questions, conversation history with search and bookmarks, and auto-save functionality.
- AI Debate Arena: Watch Pro and Con AI agents debate any topic through 5 structured rounds, submit interjections, vote for winners, and export transcripts.
- Analytics Dashboard: Track topics explored, visualize tag clouds, earn achievements for critical thinking milestones, and review engagement metrics.
- Premium Experience: Dark/light/system theme preferences, smooth Framer Motion animations, keyboard shortcuts (⌘⇧L for theme), and full accessibility compliance.
- Smart Follow-ups: AI-generated contextual questions based on your conversation to deepen understanding and explore nuances.
Our approach emphasizes steel-manning over straw-manning. Each response aims to surface the most credible opposing evidence, explain limitations, and avoid personal attacks. This product is intended for education and critical thinking. It is not a replacement for professional medical, legal, or financial advice.
We continue improving source quality, citation clarity, and topic coverage so arguments stay useful and honest. If you have feedback about quality, bias, or missing context, please visit the contact page and share specific examples.
Editorially, we prefer claims that can be traced to public research, transparent methods, and verifiable sources. We also try to surface uncertainty whenever evidence is mixed, evolving, or context-dependent. When users ask complex policy questions, we aim to expose tradeoffs rather than force a single answer. This makes the tool useful for classrooms, writing preparation, decision memos, and strategy discussions where intellectual honesty matters more than rhetorical victory.
The core product standard is simple: represent opposing viewpoints accurately, anchor arguments to traceable evidence, and reveal uncertainty instead of hiding it. We iterate on ranking and retrieval quality as new topics emerge and as source quality shifts. If you are evaluating this for classroom use, team workshops, or editorial research, you can inspect the technical foundations in the Next.js documentation and follow search quality guidance from Google Search Central.
Common Use Cases
- •Debate Preparation: Students and professionals use ContradictMe to anticipate counterarguments before presentations, debates, or policy discussions.
- •Critical Thinking Practice: Educators assign prompts to help students engage with opposing evidence and develop intellectual humility.
- •Decision-Making: Individuals exploring career changes, policy positions, or personal beliefs use the tool to surface blind spots before making commitments.
- •Research Starting Point: Writers and researchers use responses as a curated starting point for exploring opposing perspectives and evidence gaps.
Evidence Standards
ContradictMe prioritizes arguments backed by peer-reviewed research, transparent methodologies, and verifiable sources. Each argument includes quality scores based on evidence strength, sample size, and study design. We explicitly flag limitations, conflicts of interest, and areas where scientific consensus is absent or evolving.
Unlike generative AI models that produce plausible-sounding text, our system is designed to cite specific studies and acknowledge when evidence is thin, contradictory, or context-dependent. This approach helps users distinguish between well-supported claims and speculative arguments.
About the Creator
ContradictMe was created by Liz Stein, a developer focused on building tools that promote critical thinking and intellectual honesty. This project emerged from a desire to create an AI system that challenges beliefs rather than reinforcing them.
The project is built using Next.js, Algolia Agent Studio, and curated argument databases with peer-reviewed sources. All arguments are evaluated for quality, credibility, and evidence strength before being included in the system. For questions or feedback, please visit the contact page.