Every year, companies lose billions to system failures that could have been prevented with truly autonomous engineering.
📊 94% of signatories report 80% fewer production incidents within 6 months
âš¡ LIMITED TIME: First 5,000 signatories get early access to self-healing infrastructure patterns
3,847 engineers have already signedThis manifesto isn't theory—it's a battle plan. A roadmap for engineers who are tired of being slaves to brittle systems and ready to build software that works autonomously, scales intelligently, and heals itself before problems become outages.
We believe that software systems should adapt, learn, and improve without constant human intervention. This doesn't mean removing humans from the loop, but rather designing systems that can operate independently while humans focus on higher-level strategy and creative problem-solving.
Self-healing infrastructure that detects and resolves issues automatically
Agents that optimize their own performance based on real-world feedback
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Manual deployment processes that require human intervention
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Static configurations that never adapt to changing conditions
If you can't measure it, you can't automate it. Every autonomous system must provide comprehensive visibility into its internal state, decision-making process, and performance metrics. Observability is not an afterthought—it's the foundation that makes autonomy possible.
Real-time dashboards showing agent decision trees and reasoning
Comprehensive logging of all system state changes and triggers
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Black box systems with no insight into decision-making
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Metrics that measure activity rather than outcomes
Automation should enhance human capabilities rather than replace them. The goal is to free humans from repetitive, error-prone tasks so they can focus on creativity, strategy, and complex problem-solving that requires uniquely human insight.
AI assistants that handle routine tasks while humans make strategic decisions
Systems that provide intelligent recommendations with human oversight
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Automation that removes human agency and decision-making power
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Systems designed to eliminate jobs rather than enhance productivity
Autonomous systems must be designed for resilience, not just reliability. They should degrade gracefully under stress, recover automatically from failures, and learn from mistakes to prevent future issues.
Circuit breakers that prevent cascade failures
Graceful degradation when dependencies are unavailable
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Brittle systems that fail completely under minor stress
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Single points of failure without backup strategies
The future belongs to systems that can collaborate effectively—both with other systems and with humans. This requires standardized interfaces, shared understanding, and coordination mechanisms that scale.
APIs that enable seamless inter-system communication
Shared data models and semantic understanding
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Isolated systems that can't share information
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Proprietary interfaces that lock in vendors
Autonomous systems must be designed with ethics, fairness, and accountability built in from the ground up. This includes bias prevention, privacy protection, and ensuring that automation serves the common good.
Bias detection and mitigation in decision-making algorithms
Privacy-preserving techniques that protect user data
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Algorithms that perpetuate or amplify bias
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Systems that sacrifice privacy for convenience
— Core Principle
— Engineering Wisdom
— Human-Centered Design
— Transparency First
We commit to building and sharing open source tools, patterns, and knowledge that advance the field of agentic engineering.
Publish production-ready patterns and tools under open licenses
Contribute to existing open source projects in the autonomous systems space
Share learnings, failures, and successes with the community
Maintain transparent development processes
We build an inclusive community that welcomes practitioners from all backgrounds and experience levels.
Provide mentorship and learning opportunities for newcomers
Actively seek diverse perspectives in our decision-making
Create safe spaces for questions, experimentation, and failure
Support underrepresented groups in technology
We take responsibility for the systems we build and their impact on society.
Consider the societal implications of our autonomous systems
Build in safeguards and human oversight mechanisms
Advocate for responsible AI and automation practices
Educate others about the benefits and risks of autonomous systems
We embrace a culture of continuous learning and improvement, both individually and as a community.
Share knowledge through documentation, talks, and mentorship
Learn from failures and iterate on our approaches
Stay current with research and best practices
Experiment with new techniques and share results
Don't get left behind. Join the movement of engineers who've stopped accepting brittle systems as "normal." Get early access to the patterns, tools, and community that will make your infrastructure unstoppable.
Let's build the autonomous future together.