AI agents have not reduced Orestis Ioannou’s workload; they have made more work seem worth taking on. He now runs agents in parallel on implementation, investigations, reviews and research, but each periodically demands his attention. Responding means switching among problems, repositories and decisions, creating a constant cognitive load. GitHub activity offers a rough, imperfect measure of the change: it includes commits, pull requests, reviews and issues, and does not capture all work. Still, the contrast is striking. As a full-stack engineer, he averaged 173 monthly contributions; as a principal engineer, 114. After becoming VP of Technology, his activity initially remained low, but by October 2026 he had logged 2,102 contributions - more than in any full year from 2021 to 2025. August set a personal monthly record of 427.
The increase reflects not a return to full-time feature coding, but a lower barrier to starting projects: he can now fix neglected bugs, improve code patterns and pursue ideas that once seemed uneconomical. This produces cycles of intense bursts followed by fatigue. In 2026, January and February surged as he adopted agents; activity eased through June, then peaked in August after a summer break. During bursts, he launches many experiments, but reviewing their results and shifting contexts eventually exhausts his attention. Even quieter stretches now involve more work than before, and he sometimes stops wanting to use AI altogether. His central concern is that implementation capacity has expanded faster than his capacity to think, review and decide. Being able to do more repeatedly turns into doing more, without a workable balance yet.
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