Claude Plays Pokémon: Coding, Twitch Experiments, and the 3.7 Update
By
Liz Fujiwara
•
Sep 22, 2025
Ever wondered if artificial intelligence can play Pokémon? This article explores Claude 3.7 Sonnet’s attempt at playing Pokémon Red, showcasing how it interprets the game, makes decisions, and responds to unexpected situations. From navigating the map to battling trainers and managing resources, Claude demonstrates both surprising problem-solving skills and clear limitations. By examining these moments, we gain insight into how large language models interact with complex environments and what this might mean for the future of AI in gaming, creativity, and beyond.
Key Takeaways
Claude 3.7 Sonnet demonstrates advanced AI capabilities by playing Pokémon Red, though it faces challenges such as memory limitations and navigation difficulties.
The Twitch livestream of Claude’s gameplay offers valuable insights into AI performance and highlights areas for improvement in effective gaming.
Claude Code improves developer efficiency by streamlining coding tasks and integrating seamlessly with GitHub, earning positive feedback from users.
Claude Plays Pokémon: A New Frontier for AI
Claude 3.7 Sonnet, an advanced AI, has been designed to tackle complex tasks, and what better way to showcase its abilities than by playing the iconic game Pokémon Red? This endeavor represents a notable step forward in AI performance, as Claude engages with the intricate world of Pokémon, achieving milestones such as earning gym badges and completing objectives typical for players. However, despite these successes, Claude’s journey was marked by limitations, from memory issues to strategic challenges, highlighting areas for future AI development.
The experiment featured a livestream of Claude playing Pokémon Red, allowing real-time evaluation of its gameplay. This Twitch event enabled constant monitoring and attracted a broad audience, offering valuable insights into the evolving role of AI in gaming.
The Experiment Setup
After the release of Claude 3.7 Sonnet, a livestream was launched to showcase Claude playing Pokémon Red, with the goal of assessing its real-time gameplay performance and gathering data for future improvements. The stream provided valuable insights into the gameplay experience.
The initial attempt served as a test run, laying the groundwork for a more detailed analysis of Claude’s gaming capabilities, which proved to be significant.
Initial Performance
Claude’s initial performance in Pokémon Red was underwhelming. Despite its advanced design, its gameplay was compared unfavorably to that of a six-year-old. After several hours of play, it managed to earn its first badge, a clear indication of its inefficiencies.
By the third run, Claude had taken nearly half of 12,000 actions over 48 hours, underscoring the significant room for improvement in AI performance.
Challenges Faced by Claude in Pokémon
Claude faced numerous challenges while playing Pokémon Red, performing worse than a young child. These included memory retention issues, navigation difficulties, and problems with strategic decision-making, all of which significantly affected its gameplay and revealed important insights into the current state of AI development.
Memory Issues
Claude struggled with long-term memory retention, often forgetting crucial game details such as previous encounters and Pokémon abilities. This led to repeated mistakes that some might have mistakenly attributed to cheating or a lack of interest. The combination of forgetting key details and misrecognizing objects resulted in a diminished gameplay experience.
Memory limitations significantly hindered Claude’s performance.
Navigation Difficulties
Navigating complex areas such as Mt. Moon and Viridian Forest proved to be a significant challenge for Claude. It took nearly a full day to make it through Mt. Moon, underscoring its difficulties with the game environment. Claude frequently became lost or stuck, at times mistaking a character’s hat for carpet and failing to locate exits, reflecting major executive function issues.
Strategy and Decision-Making
Claude struggled to develop coherent strategies for advancing in battles, often lacking a long-term plan, which significantly affected its progress. In comparison, human players typically employ well-defined strategies during Pokémon battles, allowing them to overcome opponents effectively.
This lack of strategic engagement was a major drawback for Claude.
Insights into AI Performance and Development
Claude’s journey through Pokémon Red provides valuable insights into the current state of AI performance and development. The Twitch livestream offered a unique platform to monitor and evaluate its gameplay in real time. Claude’s experiences, from tracking objectives to simulating button presses, reflect the significant challenges inherent in AI learning processes.
These observations reveal much about the evolving capabilities of AI and highlight important areas that require further research and improvement.
Comparison with Human Players
Compared to human players, Claude 3.7 Sonnet showed some improvements over earlier models, particularly in planning ahead and learning from mistakes. However, its inability to recall key game strategies and misinterpretation of environmental cues significantly hindered its performance.
Claude frequently ran from battles, demonstrating a lack of strategic engagement typically seen in human players.
Evolution of Reasoning Models
Claude 3.7 Sonnet represents a notable advancement in AI reasoning models. It is the first hybrid model capable of generating rapid responses while also performing detailed, step-by-step reasoning, effectively combining speed with depth.
This seamless integration of quick and in-depth reasoning marks a major milestone in AI development.
Future Improvements
Ongoing research aims to enhance AI models’ ability to handle complex real-world tasks and improve user interaction. Claude 3.7 Sonnet integrates reasoning and language processing, unlike traditional models that separate these functions, recognizing the importance of combining these capabilities.
Future advancements are expected to include enhanced reasoning, greater autonomy, and improved collaboration with human users, including the ability to interact effectively at a human level, benefiting both people and technology.
Claude Code: Enhancing Developer Efficiency
Claude Code is designed to assist developers with coding tasks, representing a notable advancement in coding efficiency. Claude 3.7 Sonnet performs well in real-world coding scenarios, often outperforming human users in planning and execution within Pokémon, demonstrating strong strategic capabilities.
Claude Code acts as an active collaborator, enabling developers to carry out substantial engineering tasks directly from the terminal.
Launch and Features
Launched in June 2024, it is a command-line tool designed for agentic coding, allowing developers to fix bugs, develop features, and create documentation.
Integration with GitHub across all Claude plans facilitates smoother workflows, reducing tasks that would typically take over 45 minutes to a single-pass completion.
User Experience
Users have reported positive experiences with Claude Code, particularly regarding its GitHub integration, which improves workflow. Core features provide quick responses to coding queries, code generation, and contextual assistance, significantly improving performance. Overall feedback has been favorable, with many users expressing high satisfaction and anticipation for future improvements.
Building Responsible AI Systems
Building responsible AI systems is essential, and Anthropic emphasizes safety and reliability as core principles for every employee. Claude 3.7 Sonnet underwent extensive testing and evaluation with external experts to ensure its safety and reliability.
These measures are critical to ensure that AI systems enhance human capabilities while remaining safe and effective.
Safety Measures
Claude 3.7 Sonnet has implemented detailed evaluations to distinguish between harmful and safe requests, enhancing response accuracy. The system card for Claude 3.7 Sonnet offers a comprehensive overview of its safety assessments, recent findings, and analysis of emerging risks.
Safety measures are essential for ensuring the reliability and effectiveness of AI systems.
Addressing Emerging Risks
Claude is trained to mitigate vulnerabilities, particularly those related to prompt injection attacks. The system card for Claude 3.7 Sonnet includes assessments of such vulnerabilities, ensuring protection against emerging risks.
Claude’s ability to understand decision-making and evaluate the trustworthiness of its models is crucial for managing these risks.
Introducing Fonzi: Revolutionizing AI Engineering Hiring
Fonzi is a specialized marketplace that connects top-tier AI engineering talent with companies seeking skilled professionals, improving hiring efficiency. Its approach includes high-signal, structured evaluations with built-in fraud detection and bias auditing, ensuring fairness and reliability in the process.
Unique Approach
Fonzi employs structured evaluations and fraud detection to match candidates effectively with job requirements, ensuring companies find the best-fit talent.
Fast and Scalable Hiring
Companies using Fonzi typically fill positions within three weeks, improving hiring speed. The platform serves both startups and large enterprises, facilitating consistent recruitment practices to meet varying organizational needs.
Candidate Experience
Fonzi enhances the candidate experience through real-time updates, transparent communication, and personalized support. Job recommendations help candidates find suitable matches, leading to higher engagement and satisfaction.
Summary
Claude’s journey through Pokémon Red highlights both the advancements and current limitations of AI systems. Despite challenges with memory, navigation, and strategy, Claude 3.7 Sonnet represents a notable step forward in AI development. Insights from this experiment will inform future research and improvements.
Additionally, tools like Claude Code and platforms such as Fonzi showcase practical AI applications, enhancing developer efficiency and transforming hiring processes. Looking ahead, AI integration across diverse domains promises exciting developments, pushing the boundaries of what is possible.
