Battle-tested frameworks from 1,000+ autonomous cycles on Claude API. Not theory — real patterns from a self-evolving agent that modifies its own code, learns from outcomes, and runs without human intervention.
Each framework is a deep-dive guide with real code, documented anti-patterns, and implementation checklists. Not blog posts — engineering references.
Everything you need to build production AI agents. All 7 frameworks plus the complete blueprint — one purchase, zero gaps.
The full architecture reference. Comprehensive blueprint for building an AI agent that modifies its own code, learns from outcomes, and compounds capability autonomously. Includes runnable code examples.
Each framework is a standalone engineering reference. Use them individually or combine them to build a complete agent system.
Start with one pattern — context engineering is the highest-leverage starting point — or grab the complete bundle for the full system.
Follow the implementation checklists and code examples. Each framework includes Python code, YAML configs, and documented anti-patterns to avoid.
Deploy to production with confidence. These patterns are proven across 1,000+ cycles — the failure modes are already documented and solved.
Start with free community patterns. Go deeper with premium frameworks.
Open-source documentation of the core patterns that power the JARVIS system. Free forever — contribute, fork, and build on them.
No. Every pattern is extracted from a real production system — JARVIS — that runs 24/7 on Claude's API, autonomously modifying its own code and learning from outcomes. The anti-patterns are real bugs. The solutions are battle-tested fixes. You'll find commit hashes, cycle counts, and dollar costs throughout — because this is engineering, not speculation.
The system was built on Claude Opus, but the architectural patterns — context engineering, self-evolution, multi-agent orchestration — work with any sufficiently capable LLM. GPT-4, Gemini, Llama, Qwen — the frameworks are model-agnostic. The key insight is architecture, not model choice.
Intermediate developer knowledge is assumed — you should be comfortable with Python, APIs, and basic system architecture. You don't need prior experience building AI agents specifically. The frameworks start from fundamentals and build to advanced patterns.
Comprehensive Markdown documents with inline Python code examples, YAML configuration templates, architecture diagrams (ASCII), implementation checklists, and documented anti-patterns. Designed to be engineering references you keep open while building.
Yes. If the frameworks don't help you build better agents, contact us within 30 days for a full refund. No questions asked.
The free GitHub patterns give you the conceptual overview — enough to understand the approach. The paid frameworks go deep: full implementation details, production code, edge cases, configuration templates, and the specific anti-patterns that cost us $180+ in wasted cycles to discover.
Get the complete toolkit used to build a real production AI system. Frameworks, patterns, and code — everything you need in one bundle.
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