The 5 Levels of Self-Driving Production — Eric Schwartz, Traversal

Self-driving production addresses the growing complexity in software engineering caused by the rapid adoption of AI coding agents. While these tools accelerate development, they inadvertently shift the burden toward troubleshooting, with engineers spending significant time resolving issues in increasingly complex environments. Traditional observability tools often fail to identify root causes, leaving teams overwhelmed by alert fatigue and manual debugging. Traversal utilizes causal machine learning to automate incident response, effectively moving enterprises toward autonomous production. By mapping relationships across vast datasets, this approach enables systems to detect, diagnose, and resolve incidents without human intervention. Real-world applications at companies like Pepsi and American Express demonstrate significant reductions in alert noise and incident resolution times, allowing engineering teams to prioritize creative architecture and system design over repetitive manual troubleshooting.