Setting New Standards for Engineering Productivity and Release Velocity

Engineering leaders are investing billions in R&D, yet release velocity continues to lag. This whitepaper argues that the real constraint isn’t code generation, but debugging and code comprehension. Most engineering time is spent understanding existing systems and diagnosing software failures, not writing new code.

Traditional debuggers and today’s AI coding assistants both struggle with the hardest bugs, because they lack visibility into what software actually did at runtime.

The paper introduces agentic debugging: a new operating model where AI investigates real execution behavior to deliver evidence-based root cause analysis. Backed by empirical results, it illustrates how grounding AI in runtime truth can cut resolution times from days to hours and unlock meaningful gains in engineering productivity.

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