solveit

Product Introduction

1. SolveIt is an AI-powered coding course designed to teach developers how to build practical, maintainable projects by combining iterative problem-solving techniques with modern AI tools like LLMs. The course focuses on breaking down complex challenges into manageable components while ensuring full understanding of the underlying code.
2. Its core value lies in bridging the gap between experimental AI prototypes and production-ready systems, enabling users to transition from initial promising results to fully functional applications through structured, expert-guided workflows.

Main Features

1. The course employs a hands-on curriculum where students start solving real-world coding problems on day one, using tools like FastHTML and nbdev to build projects such as AI-powered message filters or interactive educational content.
2. It teaches a systematic decomposition framework that isolates complex tasks (e.g., implementing flow matching algorithms or configuring Cloudflare tunnels) into verifiable subproblems, ensuring each component is fully understood before integration.
3. Participants gain access to live sessions with AI engineering experts Jeremy Howard and Johno Whitaker, including code reviews and iterative development strategies refined through decades of industry experience at companies like Google and DataRobot.

Problems Solved

1. Addresses the "prototype plateau" where developers struggle to extend AI-generated code snippets into maintainable systems, particularly when modifying features or debugging opaque implementations.
2. Targets mid-level programmers and AI engineers (1-5 years of experience) who can write basic code but lack methodologies to independently architect solutions like semantic search layers or automated project showcases.
3. Typical scenarios include rebuilding legacy systems with AI augmentation (e.g., email spam filters), creating documentation-free deployment pipelines (e.g., Cloudflare tunnel setups), and implementing advanced ML techniques (e.g., Meselson-Stahl experiment simulations).

Unique Advantages

1. Unlike generic AI coding tutorials, SolveIt enforces deep code literacy through its "Test-Understand-Modify" cycle, requiring students to validate each module's behavior before progression, as demonstrated in projects like the 4,500-message Discord analyzer.
2. Integrates proprietary Fast.ai teaching frameworks with emerging tools like Jupyter-based nbdev, enabling real-time collaboration on production-grade codebases during live Monday/Wednesday sessions.
3. Combines Jeremy Howard's battle-tested curriculum (used at Google and Tesla) with a hard technical focus on system-level AI integration, evidenced by alumni projects like rebuz.fr's semantic IR solutions and enterprise-grade insurance pricing automations.

Frequently Asked Questions (FAQ)

1. What prerequisites are required? The course assumes familiarity with basic Python syntax and exposure to AI tools like ChatGPT, but provides starter templates for complex tasks like flow matching mathematics or HTML component engineering.
2. How is this different from fast.ai's deep learning courses? While fast.ai focuses on model training, SolveIt teaches full-stack implementation using AI as a coding partner, with concrete deliverables like Pol Avec's algorithm deep dives or Mat Miller's network configuration guides.
3. Can I access course materials after completion? All live sessions are recorded and include timestamped code repositories, with permanent access to the community-built project showcase containing 200+ implementations like Jay Suh's DNA replication experiments.
4. What time commitment is expected? The 5-week curriculum requires 8-12 hours weekly, including two 90-minute live coding sessions and self-paced work on projects like Aditya Kabra's FastHTML showcase or Rens Dimmendaal's solution pattern analysis.
5. Is there certification or job support? While no formal certification is issued, graduates receive detailed performance analytics and join Answer.ai's talent network, which connected multiple students to roles at AI-first companies through their public project portfolios.