大赦国际承诺减少工作。 我从来没有工作过更多。
投球是AI会给我们时间回来。 写少些锅炉板，代表无聊的部分，早点回家。
我不是在抱怨这些工具。 我用agents来做我所有的工程工作，我写了这个设置是如何演变的，为什么我仍然读代码。 我可以调查并运送两年前开始不值得的东西
但今年某地，我注意到我的工作比以前多，感觉比以前更重。 不是因为任何一项任务都更困难。 因为还有这么多人一次又一次
这篇文章我试图理解
旧负载和新负载
作为一个完全的工程师，一个正常的一周对我来说意味着两到三个严肃的任务。 一个特征，一个棘手的bug，也许是一个迁移。 每个人需要真正的专注，但我可以把其中之一在我的脑中一次，完成它，移动到下一个。
今天我的一周看起来完全不同我有几个agents平行运行：一个执行一个改变，一个调查一个生产问题，一个通过审查工作，另一个做我以后需要的研究。 没有一个总是需要我他们每个人都需要我
这就是“有时”的问题。
每个agent最终会带回一个问题，一个批准计划，一个diff读取或一个结果来说明问题。 响应意味着切换上下文：重新装入不同的问题，不同的寄存器和不同的一组决定。
每周有两到三个严肃的任务以熟悉的方式很累与许多agents合作正在以新的方式疲惫。 我的注意力分散在更多的问题上，我发现在它们之间移动更多的精神排水。
我的GitHub历史的显示
我提取了2019年1月至今天每个月的GitHub贡献日历，并标出我于"Bold.org"的角色，我于2020年1月加入：Full Stack Engineer至2022年8月，特等工程师至2025年8月，此后担任技术副总裁。 这些是GitHub的贡献计数，包括私人工作，因此它们混合了承诺，拉动请求，审查和问题。 这是一种粗略的活动信号，而不是价值的衡量。 2019年是一个不完整的基线：我的工作在Bold.org之前使用了自发托管的GitLab，因此GitHub只是我外出所做的显示。 但是形状很难忽视。
曲线的第一部分是我所期望的：
- 我最忙的编码年在Bold.org是早期。 2020年是我最高的一年，有2,711笔捐款。 2021年降为1,839人，2022年降为1,498.
- 首席工程师的年数平平又低从2022年8月到2025年7月，我平均每月缴纳114笔捐款，而担任全堆工的则为173名。 我的最低年数是2023年，有1189年。
- 技术副总裁的头几个月看起来是一样的从2025年8月到12月，我平均每月111人，2025年12月是我加入Bold.org以来最安静的月份，拥有50人。
作为一名首席工程师，我更多的工作进入了建筑，深入地潜入概念，设置项目和规划，而不是修补bugs或活泼地标。 即将到来的VP of Technology继续了这一转变，预期的特色工作更少。 至少直到AI出现。
后来2026年发生：
- 我回到我的全堆积工程师的速度。 到10月27日，我的捐款已达2 102笔，已经超过2021至2025年的任何一年。 在2020年同期，我共有2,371人，因此2026年接近我最繁忙的一年，但不能超过一年。
- 2026年8月是整个时间线上最繁忙的月份。 捐款427个，而此前在2020年4月捐款最多，为319个。
- 我正常的一天搬回来了从2022年到2025年，工作日的中位数是每年3或4人的捐款。 2026年是7岁，接近我2020年的8岁。
没有GitHub活动的工作日减少。 至10月27日，我共有18个工作日，捐款为零，而2022至2025年全年只有40-46个。 这是没有记录的GitHub活动的日子，而不是休息的日子。
- 严酷的日子又成了例行公事从2022年到2025年，我每年有整整一天的捐款，有24个或更多。 2026年，我已经拥有16个，几乎是整个2020年的17个。
这些几乎都是私人工作。 图表中虚线仅是公共捐款：从2021年到2025年接近于零，今年又复出，至今已有191个，但这还不到2026年的十分之一。
曲折就是角色。 在2020年，我是一个全速的工程师全职做特写工作，这大概就是GitHub上的样子。 今天我领导Bold.org的工程做的工作比以前少得多在纸上，我的图表应该看起来像我的首席工程师年数，或更低。 而是回到我写代码时的样子
改变的是，工作值得承担多少。 当编码便宜时，我可以修复我以前会独自留下的bugs，改善整个代码库的规律，承担新的项目，把更多的想法变成真实的东西。 大部分都是我以前从未考虑过的工作。 Agents不仅使我现有的工作量更快完成。 他们很容易给我一个更大的。
屁股，然后烧焦
从每月总数来看，2026年不是稳步攀升。 这是一系列的暴发。
1月和2月是第一次明显爆发，捐款277和233个。 这时我开始和agents认真合作，而成为我们内部公司的可观察性实验agent也随之起飞。 每星期我都会发现一些新的东西，我突然可以委托给大家，我想尝试一下。
3月至6月的捐款普遍减少，从3月的203笔捐款减至6月的77笔。 但四月是一条小路，另一个月，当我有了想法并对他们采取了行动。 我认为模型的改进是能量更新的一部分。 其每月总计187个在一月至三月以下，但包括29个捐款日和68个公众捐款，这是我当年公共捐款总额中最高的。
奥古斯特是其中最大的爆炸。 从我暑假回来，日历显示整整一周零捐款在8月初。 之后从8月10日到8月27日的每个工作日都在14到43岁之间。 8月以427起捐款告终，是整个时间表中最繁忙的月份。 9月保持高位为301.
每个周期都以同样的方式开始。 新的模式或新的工作流程使得上个月不可能实现的东西成为可能我的头充满了想法因为现在的执行是廉价的，所以没有自然的摩擦阻止我同时追逐所有这些。 我也这么想我开始更多的agents，打开更多的线程，对更多的实验说是。
这能维持几个星期然后评论和背景切换赶上我，我拉回到一个更稳定的流量。 我呆在那里，直到一些令人兴奋的东西出现，或者直到一个节日给我充电，我直接回到另一个爆发。
我数了三个周期从一月份开始
在爆炸结束时，我对AI感到厌倦。 我不想再开始一个 agent 或者想更多的想法。 我做我的正常工作，但我停止追寻额外的项目和可能性，因为我没有他们的精神带宽。
低个赛季不再低了
最让我惊讶的不是山峰这是我在他们之间所做的一切。
3月份感觉不像1月、2月或8月的暴发，但我仍在做大量工作。 它有203笔捐款，而我的首席工程师平均每月114笔捐款。 我仍然在思考，但这种水平的活动不再觉得是一种非凡的推动。 即使我认为我放松了，仍有agent结果要完成，审查要完成，小事现在“只是迅速”。
6月确实很低，有77个捐款，相当于我宁静的首席工程师月数。 也许那时我累得要命不是每个安静月都比以前高但除此之外，我仍然发现自己承担比我以前更多的工作。 这就是我所说的低季不再觉得低。
离开我的地方
AI为我之前从未考虑过的工作创造了空间。 我喜欢能够修复更多的东西，把更多的想法变成真实的东西。 但是，执行这些想法的能力比我考虑这些想法的能力快得多。 最终我不再想再开始一个agent 回到正常工作我还没有找到平衡。 现在，我注意到，能够做更多的事情，就不断变成做更多的事情。 我也很累，现在我累了
关于这篇文章写作方式的说明：AI帮助我拉出和分析我的GitHub贡献数据，构建图表并起草这篇文章。 经验、决定和意见是我的。
本文由 AI宝库自动抓取并翻译，版权归原作者所有；如需查看原文请点下方链接。
AI Promised Less Work. I Have Never Worked More.
The pitch was that AI would give us our time back. Write less boilerplate, delegate the boring parts, go home earlier.
I am not complaining about the tools. I use agents for all of my engineering work now, and I wrote about how that setup evolved and why I still read the code. I can investigate and ship things that would not have been worth starting two years ago.
But somewhere this year I noticed that I am working more than I ever have, and that it feels heavier than it used to. Not because any single task is harder. Because there are so many more of them, all at once.
This post is me trying to understand that, with some data from my own GitHub history.
The old load and the new load
As a full-stack engineer, a normal week for me meant two or three serious tasks. A feature, a tricky bug, maybe a migration. Each one needed real focus, but I could hold one of them in my head at a time, finish it, and move to the next.
Today my week looks completely different. I have several agents running in parallel: one implementing a change, one investigating a production question, one working through a review, another doing research I will need later. None of them needs me all the time. Every one of them needs me sometimes.
That “sometimes” is the problem.
Each agent eventually comes back with a question, a plan to approve, a diff to read or a result to make sense of. Responding means switching contexts: reloading a different problem, a different repository and a different set of decisions.
Two or three serious tasks a week was tiring in a familiar way. Working with many agents is tiring in a new way. My attention is spread across more problems, and I find moving between them much more mentally draining.
What my GitHub history shows
I pulled my GitHub contribution calendar for every month from January 2019 to today and marked my roles at Bold.org, which I joined in January 2020: Full Stack Engineer until August 2022, Principal Engineer until August 2025, and Vice President of Technology since then. These are GitHub’s contribution counts, including private work, so they mix commits, pull requests, reviews and issues. It is a rough signal of activity, not a measure of value. 2019 is an incomplete baseline: my job before Bold.org used a self-hosted GitLab, so GitHub only shows what I did outside it. But the shape is hard to ignore.
The first part of the curve is what I expected:
- My busiest coding years at Bold.org were the early ones. 2020 was my highest year, with 2,711 contributions. 2021 dropped to 1,839 and 2022 to 1,498.
- The Principal Engineer years were flat and lower. From August 2022 to July 2025 I averaged 114 contributions a month, against 173 as a Full Stack Engineer. My lowest year was 2023, with 1,189.
- The first months as VP of Technology looked the same. From August to December 2025 I averaged 111 a month, and December 2025 was my quietest month since joining Bold.org, with 50.
As a Principal Engineer, more of my work went into architecture, deep dives into concepts, setting up projects and planning, rather than fixing bugs or iterating on features. Becoming VP of Technology continued that shift, with even less feature work expected. At least until AI came along.
Then 2026 happened:
- I am back at my Full Stack Engineer pace. By October 27 I am at 2,102 contributions, already more than any full year from 2021 to 2025. Over the same period in 2020 I had 2,371, so 2026 is close to my busiest year but not above it.
- August 2026 is the busiest month in the whole timeline. 427 contributions, against a previous high of 319 in April 2020.
- My normal day moved back up. The median weekday was 3 or 4 contributions every year from 2022 to 2025. In 2026 it is 7, close to the 8 I had in 2020.
- Fewer weekdays without GitHub activity. Through October 27, I had 18 weekdays with zero contributions, compared with 40–46 across each full year from 2022 to 2025. These are days without recorded GitHub activity, not days off work.
- Heavy days became routine again. From 2022 to 2025 I had exactly one day per year with 24 or more contributions. In 2026 I already have 16, almost the 17 I had in all of 2020.
Almost all of this is private work. The dashed line in the chart is public contributions only: it was near zero from 2021 to 2025 and came back this year, with 191 so far, but that is still less than a tenth of 2026.
The twist is the role. In 2020 I was a full-stack engineer doing feature work full time, and this is roughly what that looked like on GitHub. Today I lead engineering at Bold.org and do far less feature work than I used to. On paper my graph should look like my Principal Engineer years, or lower. Instead it is back where it was when writing code was my whole job.
What changed is how much work feels worth taking on. When coding is cheap, I can fix bugs I would previously have left alone, improve patterns across the codebase, take on new projects and turn more ideas into something real. Much of this is work I would never have considered before. Agents did not just make my existing workload faster to finish. They made it easy to give myself a much bigger one.
Bursts, then burnout
Looking at the monthly totals, 2026 is not one steady climb. It is a series of bursts.
January and February were the first clear burst, with 277 and 233 contributions. This is when I started working seriously with agents, and when the observability experiment that became our internal company agent took off. Every week revealed something new I could suddenly delegate, and I wanted to try all of it.
March to June generally winds down, from 203 contributions in March to 77 in June. But April was a smaller burst along the way, another month when I had ideas and acted on them. I think improvements in the models were part of that renewed energy. Its monthly total of 187 is below January to March, but it includes a 29-contribution day and 68 public contributions, my highest public total of the year.
August is the biggest burst of all. Coming back from my summer break, the calendar shows a full week of zero contributions in early August. Then every weekday from August 10 to August 27 was between 14 and 43. August ended at 427 contributions, the busiest month in the whole timeline. September stayed high at 301.
Every cycle starts the same way. A new model or a new workflow makes something possible that was not possible last month, and my head fills with ideas. Because implementation is now cheap, there is no natural friction stopping me from pursuing all of them at once. So I do. I start more agents, open more threads and say yes to more experiments.
That works for a few weeks. Then the reviewing and context switching catch up with me, and I pull back to a more stable flow. I stay there until something exciting comes along, or until a holiday recharges me enough that I go straight back into another burst.
I count three of these cycles since January.
At the end of a burst, I feel tired of AI. I do not want to start another agent or think of more ideas. I do my normal work, but I stop chasing the extra projects and possibilities because I do not have the mental bandwidth for them.
The low season is not low anymore
The part that surprised me most is not the peaks. It is how much I am doing between them.
March did not feel like the bursts in January, February or August, but I was still doing substantial work. It had 203 contributions, against my Principal Engineer average of 114 a month. I was still acting on ideas, but that level of activity no longer felt like an exceptional push. Even when I think I am taking it easy, there are still agent results to work through, reviews to finish and small things that are now “just a quick prompt”.
June was genuinely low, with 77 contributions, comparable to my quieter Principal Engineer months. Maybe that was when all the tiredness caught up with me. Not every quiet month is higher than before. But outside the bursts, I still find myself taking on more work than I used to. That is what I mean by the low season not feeling low anymore.
Where that leaves me
AI made room for work I would never have considered before. I like being able to fix more things and turn more ideas into something real. But the capacity to implement those ideas has grown much faster than my capacity to think about them. Eventually I stop wanting to start another agent and go back to just doing my normal work. I have not figured out a balance. For now, I am noticing that being able to do more keeps turning into doing more. And I am tired.
A note on how this article was written: AI helped me pull and analyze my GitHub contribution data, build the chart and draft this article. The experience, decisions and opinions are mine.
Auto-fetched and translated by AI Gem Box. All rights belong to the original author.