I lead a bazel conversion for a pretty complex piece of software written in 5+ programming languages and shipping native binaries to all 3 major OSes a few years ago, and it took multiple years to get it done.
For a less complex project (1 programming language, still shipping to all 3 major OSes), with my knowledge and agents I got the bazel conversion done in 2 weeks.
The setup cost for bazel just went down by a lot, and I don't think the industry as a whole is aware of that yet.
The entire industry, including its outputs that LLMs are trained on, hasn’t reconsidered what’s easy vs. hard or fast vs. slow. LLMs consistently recommend against code changes because they will take “a weekend”. No, Claude. You will do the work and it will take 20 minutes.
Can't comment on Bazel specifically, but having worked with both nx and turbo, the bottleneck was usually network and disk IOPS rarely compute.
Even fully cached outputs needs to fetched and read from a remote server[1]. A step n-1 outout fetched from remote cache server need to written to disk and then again read by step n[3] - all disk I/O and network bound operations.
10s may be achievable/realistic goal in the Java/C++ world where Bazel normally seen. In TS eco-system most people would be over the moon to get into ballpark of 1-2m for a decently large monorepo.
We should define Build more clearly here, if you mean running just transpile/compile steps or the full series of steps that includes tests (as the linear post here is talking about). It is hard to see even a small sub-set of a large suite of test that require a virtual DOM or a real browser can run in 10s or less.
[1] Typical for say managed CI setup .
[3] Common run-of-the-mill frontend + backend stacks in different languages etc.
If you don't need to rebuild anything, bazel can fetch only the final artifact (not the intermediates) from the remote cache.
Also, if you have persistent CI workers with a persistent bazel instance, you save on some network roundtrips, but that's obviously harder to set up and make bulletproof.
Bazel seems to have a lot of tradeoffs, from setup time of the sandbox for each task, to ergonomics that lead folks to maintain parallel 'normal' tooling.
Plus, 'with a warm cache' is doing heavy lifting, what's the real cache hit rate for a week of development? Investing in improving the cold build and frequent actions is still important with bazel or any incremental builder.
I'm not sure it's useful to talk about bazel broadly, it's actual performance and behavior comes down to the rules you use. You can configure bazel like turbo/nx and cache tsc/vitest/eslint on each package.json module, and get course cached units that are evicted on every change, or you can use gazelle and target per-file actions which are only invalidated when their dependencies change. But that trades off batching unless you use workers.
Agentic Coding has been a huge strain on CI,
I have been using Bazel to improve our build times and ultimately building customized runners to improve our CI
Anyways great blog post from linear team a lot to learn from it
My recent winnowwallet.com still has build times of over 10 minutes. I'm convinced the agent really wants build times around 5m to move at a quick pace. Also to not drive me insane. It took a ton of work to get it down from 45 minutes because my tests launch a full version of the app, and walk it through major usecases while recording video and screenshots. I then use AI to qa this. It also generates its webpage this way. All from CI/CD
Maybe I'm alone in this, but as someone who is in tech, I don't know what CI is, and I don't think it's unreasonable to expect it to have an expansion within the article the first time you use it...
AI is in the cultural zeitgeist, but you gotta expand most other things at least once.
So if you don't know what CI is, what does "I am someone in tech", mean? Marques Brownlee probably doesn't know CI is, but he's also in tech. Because if you by mean "I am in tech" that "I am a software engineer", and you don't know what CI is, then boy; I'd be worried for you.
I recommend making a habit of googling or asking AI about terms you run into. As someone who is in tech, you will hear tech jargon your whole career that will not be explained if it's considered standard terminology for the audience being spoken to. It is better to learn to educate yourself than expect others to go out of their way.
Most days I feel like I must be the dumbest person on HN. I don't understand what 80%+ of submissions are about. But if it sounds interesting, I'll dig into it a bit and learn a few things along the way.
Within the engineering tech sphere, CI/CD have also been terms that have been standard for at least a decade now.
You would probably be rejected from most interviews at the first stage if you didn't vaguely know what they mean at this point.
Linears entire product is tailored towards software engineers/engineers in general or people who work alongside engineers, so its not surprise their posts have a bit of assumed knowledge.
I just feel apps like linear are increasingly getting in the way of full send agentic development where sub agent orchestration is done through agent to agent messaging, work trees, on demand git restructuring and epoch specific coordination plains, often .md files. The smaller the human component of total product development gets, the more this may be the case.
> where sub agent orchestration is done through agent to agent messaging
How do you expect to see the history/record of what the agents did and why? Is it enough to see it in PRs? Do you expect tickets that have the design and history? How are you thinking of agents being able to historically resolve reasoning/why/decisions made in earlier passes?
Genuine open question here. My assumption is that a GH or Linear or Jira is still useful as a decision store. It may as well be a custom app over Postgres, but it seems like something is needed to store this and for observability. A GH/Linear/Jira is nice if only because of standard APIs and integration points (whatever you build would likely end up duplicating a subset of those).
I’m conflicted about Linear’s progression. I dislike some of the features but on the whole they’ve managed to keep the software pleasant to use, it doesn’t feel to me that it is drifting towards Jira territory, rather, it feels like it is losing the carefully considered product design because now code is cheap to generate. I’m not worried about it turning into Jira but it has lost its soul. Still a great product.
In my case it's not the CI that's the bottleneck. It's the human testing side. Does it work, sure. But does it actually do the thing we want (and more importantly) does it do it in a way our customers will understand and actually like?
Think of it as a layered problem. If the bottom layer (CI) cannot keep up with the output of agents, then solving problems at a higher layer - like user experience checks - will be exponentially slower and less reliable. Kind of like how optimizing tight inner loops makes your whole program faster.
Clearly you have to replace obsolete human testers with agentic AI testers, duh.
At some point, with all this velocity, human users become the bottleneck, unable to keep up with and learn all the changes and new features. Luckily, there's a simple solution: just replace the human users with agentic AI users.
The forceful executive, Henry Ford II, and the leader of the automobile workers union, Walter Reuther, both saw many examples of advanced machinery operating at the plant. The words they exchanged brilliantly encapsulated the paradox of automation:
Henry Ford II: Walter, how are you going to get those robots to pay your union dues?
Walter Reuther: Henry, how are you going to get them to buy your cars?
Moving our workloads off GitHub Actions to third-party runners with faster CPUs, higher-performance storage, and better cache infrastructure gave us faster machines to run the same pipeline on
Yeah, was not surprised to read this. Actions is convenient if you already use GitHub, but it can also be pretty slow. Given reliability is also a major issue with GitHub these days I expect to see more orgs moving to different pipelines
We switched our Actions workload to blacksmith.sh (not affiliated) and have been pretty happy with how fast and inexpensive they are. I wouldn't be surprised to see this trend continue.
My take: it seems like systems should become smaller, more isolated, and contract-oriented.
I have been a long time proponent of monoliths, but it seems like agents would be happier with smaller, more isolated services. The more isolated, the better. Contracts between the service components only. Then it can iterate internally as long as it satisfies the contract. If it needs to, it can version the contract and keep iterating.
I wonder if the GitHub actions outages we keep seeing is due to themselves making self-hosted runners paid, hence bringing broke/cheap users back from hosted runners to their garbage infra.Meanwhile I'm running my Codeberg Actions on the free Oracle ARM machine 2 cores 12GB ram (previously 4 cores 24GB) and way more reliable. Keep winning bozos.
Edit: After second thought, I guess "alternative runner" providers still have to pay the self-hosted tax. So M$ actually saves and makes money by not scaling their infra and driving people to alternative providers they can tax freely. Actual geniuses.
If you can pay the setup cost, Bazel will get you build times ~10s with a warm cache for even massive projects.
I lead a bazel conversion for a pretty complex piece of software written in 5+ programming languages and shipping native binaries to all 3 major OSes a few years ago, and it took multiple years to get it done.
For a less complex project (1 programming language, still shipping to all 3 major OSes), with my knowledge and agents I got the bazel conversion done in 2 weeks.
The setup cost for bazel just went down by a lot, and I don't think the industry as a whole is aware of that yet.
Were any of those using JS/TS? I've seen Bazel perform wonders with many compiled languages, but I'm not impressed with the JS ecosystem.
Nothing substantial, no. I've never personally experienced builds to be so slow to begin investigating bazel as an option for JS/TS.
Tsgo, oxlint, caching dependencies etc. what linear outlined in their blog post would be more impactful for the average TS project I've worked on.
The entire industry, including its outputs that LLMs are trained on, hasn’t reconsidered what’s easy vs. hard or fast vs. slow. LLMs consistently recommend against code changes because they will take “a weekend”. No, Claude. You will do the work and it will take 20 minutes.
Can't comment on Bazel specifically, but having worked with both nx and turbo, the bottleneck was usually network and disk IOPS rarely compute.
Even fully cached outputs needs to fetched and read from a remote server[1]. A step n-1 outout fetched from remote cache server need to written to disk and then again read by step n[3] - all disk I/O and network bound operations.
10s may be achievable/realistic goal in the Java/C++ world where Bazel normally seen. In TS eco-system most people would be over the moon to get into ballpark of 1-2m for a decently large monorepo.
We should define Build more clearly here, if you mean running just transpile/compile steps or the full series of steps that includes tests (as the linear post here is talking about). It is hard to see even a small sub-set of a large suite of test that require a virtual DOM or a real browser can run in 10s or less.
[1] Typical for say managed CI setup .
[3] Common run-of-the-mill frontend + backend stacks in different languages etc.
If you don't need to rebuild anything, bazel can fetch only the final artifact (not the intermediates) from the remote cache.
Also, if you have persistent CI workers with a persistent bazel instance, you save on some network roundtrips, but that's obviously harder to set up and make bulletproof.
Bazel can even skip the final artefact!
Bazel seems to have a lot of tradeoffs, from setup time of the sandbox for each task, to ergonomics that lead folks to maintain parallel 'normal' tooling.
Plus, 'with a warm cache' is doing heavy lifting, what's the real cache hit rate for a week of development? Investing in improving the cold build and frequent actions is still important with bazel or any incremental builder.
I'm not sure it's useful to talk about bazel broadly, it's actual performance and behavior comes down to the rules you use. You can configure bazel like turbo/nx and cache tsc/vitest/eslint on each package.json module, and get course cached units that are evicted on every change, or you can use gazelle and target per-file actions which are only invalidated when their dependencies change. But that trades off batching unless you use workers.
Most PRs only touch a handful of targets so cache hits are extremely high in practice.
vitest load balancing on test duration times instead of by file would be a nice performance win
We actually tried this and (for us) it doesn't lead to enough of a gain that's worth the extra complexity.
Agentic Coding has been a huge strain on CI, I have been using Bazel to improve our build times and ultimately building customized runners to improve our CI
Anyways great blog post from linear team a lot to learn from it
My recent winnowwallet.com still has build times of over 10 minutes. I'm convinced the agent really wants build times around 5m to move at a quick pace. Also to not drive me insane. It took a ton of work to get it down from 45 minutes because my tests launch a full version of the app, and walk it through major usecases while recording video and screenshots. I then use AI to qa this. It also generates its webpage this way. All from CI/CD
Maybe I'm alone in this, but as someone who is in tech, I don't know what CI is, and I don't think it's unreasonable to expect it to have an expansion within the article the first time you use it...
AI is in the cultural zeitgeist, but you gotta expand most other things at least once.
CI -> Continuous Integration
Its best thought of as the testing systems that are run as part of pull request review / merge to main / build processes.
So if you don't know what CI is, what does "I am someone in tech", mean? Marques Brownlee probably doesn't know CI is, but he's also in tech. Because if you by mean "I am in tech" that "I am a software engineer", and you don't know what CI is, then boy; I'd be worried for you.
CI is really only significant on the programming side of things. Networking, systems administration, hardware, etc often don’t have that workflow.
sysadmins CI is hoping the machine still boots after an update. Unless you are lucky you got two identical machines to have a test env.
I recommend making a habit of googling or asking AI about terms you run into. As someone who is in tech, you will hear tech jargon your whole career that will not be explained if it's considered standard terminology for the audience being spoken to. It is better to learn to educate yourself than expect others to go out of their way.
Man, what a weird thing to complain about.
Most days I feel like I must be the dumbest person on HN. I don't understand what 80%+ of submissions are about. But if it sounds interesting, I'll dig into it a bit and learn a few things along the way.
"AI is in the cultural zeitgeist"
Within the engineering tech sphere, CI/CD have also been terms that have been standard for at least a decade now.
You would probably be rejected from most interviews at the first stage if you didn't vaguely know what they mean at this point.
Linears entire product is tailored towards software engineers/engineers in general or people who work alongside engineers, so its not surprise their posts have a bit of assumed knowledge.
I just feel apps like linear are increasingly getting in the way of full send agentic development where sub agent orchestration is done through agent to agent messaging, work trees, on demand git restructuring and epoch specific coordination plains, often .md files. The smaller the human component of total product development gets, the more this may be the case.
Question here:
How do you expect to see the history/record of what the agents did and why? Is it enough to see it in PRs? Do you expect tickets that have the design and history? How are you thinking of agents being able to historically resolve reasoning/why/decisions made in earlier passes?
Genuine open question here. My assumption is that a GH or Linear or Jira is still useful as a decision store. It may as well be a custom app over Postgres, but it seems like something is needed to store this and for observability. A GH/Linear/Jira is nice if only because of standard APIs and integration points (whatever you build would likely end up duplicating a subset of those).
Good thing Linear has been finished for a long time doesn't need more features, so AI coding can go slow. Oh damn, it's busy becoming the next Jira :(
I’m conflicted about Linear’s progression. I dislike some of the features but on the whole they’ve managed to keep the software pleasant to use, it doesn’t feel to me that it is drifting towards Jira territory, rather, it feels like it is losing the carefully considered product design because now code is cheap to generate. I’m not worried about it turning into Jira but it has lost its soul. Still a great product.
In my case it's not the CI that's the bottleneck. It's the human testing side. Does it work, sure. But does it actually do the thing we want (and more importantly) does it do it in a way our customers will understand and actually like?
Think of it as a layered problem. If the bottom layer (CI) cannot keep up with the output of agents, then solving problems at a higher layer - like user experience checks - will be exponentially slower and less reliable. Kind of like how optimizing tight inner loops makes your whole program faster.
Uh, no. If stage X is the bottleneck, it's immaterial how much you speed up stage Y.
You're assuming QA reviews won't be fully automated, and triggered from a CI pipeline.
Clearly you have to replace obsolete human testers with agentic AI testers, duh.
At some point, with all this velocity, human users become the bottleneck, unable to keep up with and learn all the changes and new features. Luckily, there's a simple solution: just replace the human users with agentic AI users.
Maybe we can also replace the customers with agentic consumers.
https://quoteinvestigator.com/2011/11/16/robots-buy-cars/
Yeah, was not surprised to read this. Actions is convenient if you already use GitHub, but it can also be pretty slow. Given reliability is also a major issue with GitHub these days I expect to see more orgs moving to different pipelines
I wonder how much faster GitHub actions could be if they weren’t running on Azure. Because Azure is either slow or very expensive.
We switched our Actions workload to blacksmith.sh (not affiliated) and have been pretty happy with how fast and inexpensive they are. I wouldn't be surprised to see this trend continue.
My take: it seems like systems should become smaller, more isolated, and contract-oriented.
I have been a long time proponent of monoliths, but it seems like agents would be happier with smaller, more isolated services. The more isolated, the better. Contracts between the service components only. Then it can iterate internally as long as it satisfies the contract. If it needs to, it can version the contract and keep iterating.
I wonder if the GitHub actions outages we keep seeing is due to themselves making self-hosted runners paid, hence bringing broke/cheap users back from hosted runners to their garbage infra.Meanwhile I'm running my Codeberg Actions on the free Oracle ARM machine 2 cores 12GB ram (previously 4 cores 24GB) and way more reliable. Keep winning bozos.
Edit: After second thought, I guess "alternative runner" providers still have to pay the self-hosted tax. So M$ actually saves and makes money by not scaling their infra and driving people to alternative providers they can tax freely. Actual geniuses.
I call this moment "the Great CI Bottleneck of 2026". Here are my thoughts on it: https://dagger.io/blog/the-great-ci-bottleneck-of-2026/