AI promised less work. I've never worked more
- ID
- 40021
- Status
- summarized
- Published
- 27 Oct 2026, 7:08 PM
- Fetched
- 27 Oct 2026, 11:50 PM
- Provider
- Hacker News
- Category
- dev-community
- Original URL
- https://oioannou.com/blog/ai-promised-less-work/
- Source URL
- https://hnrss.org/best
Summary
- Score
- 8.3
- Created
- 27 Oct 2026, 11:50 PM
- Tags
- Audience
- developersvibe_codersai_agent_users
What happened
Orestis Ioannou argues that running multiple AI coding agents in parallel has increased, not reduced, his workload: instead of two or three focused tasks a week, he now juggles several agents that each intermittently need a plan approved, a diff read, or a question answered, and the constant context switching is more draining than the old mode. He backs this with his GitHub contribution calendar from January 2019 onward, showing 2,711 contributions in 2020, falling to 1,839 in 2021 and 1,498 in 2022, a low of 1,189 in 2023, and an average of 114 contributions a month as Principal Engineer (Aug 2022–Jul 2025) versus 173 a month as a Full Stack Engineer. He explicitly frames contribution counts as a rough activity signal, not a measure of value. The Hacker News thread drew 418 points and 374 comments.
Why it matters
If you've added parallel agents to your workflow, the bottleneck has shifted from writing code to managing interruptions — every agent that returns a question forces a full context reload across a different repo and decision set. Decide a cap on concurrent agents and a batching rule (e.g. agents report only at checkpoints) rather than assuming more agents equals more throughput; otherwise your review queue, not your typing speed, sets your week.
Discussion angle
Ask everyone running agents in parallel: how many are live right now, and how often do they interrupt you? Then compare notes on whether batching agent checkpoints or capping concurrency actually recovered focus time — and whether anyone has measured cycle time before vs after adopting agents.