TechnologySoftware Engineering

How Cognition Tripled Merged PRs Per Week Using Claude to Power Devin, Its Autonomous AI Engineer

Cognition is the company behind Devin, one of the first AI software engineers, deployed across enterprises including Goldman Sachs, Mercedes-Benz, and the US Army. Devin handles autonomous, long-horizon software engineering tasks — from scoping tickets and locating relevant files to writing and testing code and opening pull requests. Cognition routes its most demanding long-context agentic work to Claude, which powers Devin's ability to stay on track across complex, multi-step trajectories. Since adopting Claude Sonnet 3.6, Cognition achieved a 3.5× increase in merged PRs per week.

Outcomes

3.5×Increase in merged PRs per week after adopting Claude Sonnet 3.6
Goldman Sachs, Mercedes-Benz, US ArmyEnterprise customers using Devin

Tools & Technologies

1C
Claude
Anthropic's AI assistant for analysis, writing, and reasoning tasks.

AI Categories

Challenge

Autonomous AI software engineering demands that an agent sustain coherent, multi-step execution across complex codebases without drifting — a consistency requirement that most models failed, producing high variance and degraded quality over long contexts, which made autonomous deployment in enterprise environments too risky.

Solution

Cognition routes Devin's most demanding long-horizon agentic work to Claude, selected for its sustained long-context performance, intelligent tool use across codebases, and ability to expand two-line task descriptions into accurate full trajectories without requiring fully-specified instructions.

Full Story

Cognition launched Devin in early 2024 as one of the first AI software engineers — a product designed not to complete individual code suggestions but to take a well-scoped ticket and own the entire trajectory from understanding to shipped PR. The bar is categorically different from a code-completion tool. Users under-specify tasks by default; the agent has to clarify intent, infer context it wasn't given, and sustain focus across a long, multi-step sequence without drifting. A wrong starting inference doesn't just produce a bad line of code — it sends the entire trajectory off course.

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