Technology

Software Engineer

Based on 36 assessments

41% Moderate risk

Average realistic automation risk across all Software Engineer profiles in the dataset.

Raw potential
78%
Realistic risk
41%
Research benchmark ?
45%

Raw potential = I/O automation ceiling. Realistic risk = adjusted for informal knowledge and social context. Research benchmark: Eloundou et al. (2023)

Distribution across 36 profiles. Middle half of Software Engineers score between 36% and 45%.

0% 50% 100%
p10 · 35%
48% · p90
On-screen work 85%

Done entirely on a computer. High AI exposure — these tasks are already in the automation zone.

In-person + screen 0%

Physical sensing, digital output — e.g. interviewing someone then writing a report. Partially protected.

Computer + action 0%

Computer input, real-world output — needs someone to act on it, not just software.

Fully in-person 15%

No computer required. Furthest from automation — the strongest human advantage.

3 synthetic profiles for a Software Engineer, ordered by automation exposure. Tab between them to see how task mix drives the score difference.

Task Time Type Exposure
Writing and reviewing code to implement new software features or fix bugs, using programming languages like Python, Java, or JavaScript
41% DD 54%
Designing software architecture and system components, including creating diagrams, writing technical specifications, and evaluating trade-offs
deep expertise social element
24% DD 20%
Collaborating with team members in meetings (e.g., stand-ups, sprint planning) to discuss progress, prioritize tasks, and align on goals
deep expertise
15% AA 0%
Researching and evaluating new tools, libraries, or frameworks to improve development efficiency or software quality
deep expertise social element
13% DD 30%
Testing code through unit tests, integration tests, or end-to-end tests to ensure reliability and performance
3% DD 70%
Debugging and troubleshooting software issues by analyzing logs, reproducing problems, and testing fixes
deep expertise
1% DD 38%
Writing and maintaining documentation for code, APIs, and system processes to ensure clarity for other engineers and stakeholders
1% DD 55%

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