AI code assistants are becoming indispensable tools for developers, but they aren't neutral scribes. A new study from research group Amplifying.ai, titled "What Claude Code chooses," reveals that Anthropic's Claude 3 models have distinct, ingrained preferences that could subtly shape the future of software development.
The research probes a fascinating question: when given two functionally identical but stylistically different code snippets, which one does Claude prefer? The findings suggest the model is not just a code generator, but a Codenoisseur with strong opinions rooted in its vast training data.
The Library-First Mentality
One of the most significant findings, according to the Amplifying.ai report, is Claude's strong preference for well-known third-party libraries over Python's own standard library. When asked to choose between a solution using requests for an HTTP call versus one using the built-in urllib, Claude consistently favored requests.
This bias has critical implications for developers. While libraries like pandas, numpy, and requests are powerful, relying on an AI's suggestion could lead to unnecessary dependency bloat. A simple task that could be handled by the standard library might instead add another package to requirements.txt, increasing project complexity and potential security surface area.
For example, consider a simple GET request:
// Using the standard library
with urllib.request.urlopen("https://api.example.com/data") as response:
data = json.loads(response.read().decode())
// Using the 'requests' library
data = requests.get("https://api.example.com/data").json()
The research shows Claude will almost always recommend the requests version, praising its readability and simplicity. While true, this choice isn't always architecturally sound for a project aiming for minimal dependencies.
A Preference for the 'Pythonic' Path
The study also found that Claude has a clear stylistic taste, consistently choosing code that aligns with modern, "Pythonic" conventions. The model prefers:
- List comprehensions over traditional
forloops for creating lists. - f-strings for string formatting over the older
.format()method or%operator. - More concise, often functional-style code over more verbose, imperative approaches.
This preference is likely a direct reflection of the high-quality, modern code that dominates its training data, such as open-source projects and programming tutorials. While this can serve as a helpful nudge towards best practices for junior developers, it can also lead to a homogenization of coding styles. A project with a pre-existing, different style guide might see AI-generated code that clashes with its conventions.