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Full Stack Developer

Based on 48 assessments

47% Moderate risk

Average realistic automation risk across all Full Stack Developer profiles in the dataset.

Raw potential
85%
Realistic risk
47%
Research benchmark ?
63%

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

Distribution across 48 profiles. Middle half of Full Stack Developers score between 43% and 49%.

0% 50% 100%
p10 · 41%
53% · p90
On-screen work 88%

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

In-person + screen 12%

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 0%

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

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

Task Time Type Exposure
Writing and maintaining server-side application logic (backend code) using languages like Python, Java, or Node.js to handle data processing, API requests, and business logic
32% DD 49%
Collaborating with product managers, designers, and other developers to translate business requirements into technical specifications and implementation plans
some context needed
24% AD 13%
Developing and maintaining client-side interfaces (frontend code) using frameworks like React, Angular, or Vue.js to create responsive and interactive user experiences
19% DD 46%
Debugging, testing, and optimizing code to ensure performance, security, and scalability of applications, including writing unit and integration tests
17% DD 58%
Designing and managing databases (e.g., SQL or NoSQL) to store, retrieve, and optimize data for applications, including writing queries and ensuring data integrity
4% DD 57%
Deploying and managing applications on cloud platforms (e.g., AWS, Azure, or Google Cloud) and ensuring infrastructure as code (IaC) practices are followed
1% DD 56%
Reviewing code submitted by peers to ensure quality, consistency, and adherence to best practices, often through pull requests and team discussions
deep expertise
1% DD 16%

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