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We raised a $45M Series B led by Peak XV, with YC and GV tripling down. Blacksmith is now valued at $550M. We closed this back in March. CI volume is up 5-10% every week as codegen makes writing code easy and validating it the bottleneck. 6,000+ companies run CI on us. What's the money for? Compute. We're building a cloud and that ain't cheap. We're hiring in NYC + SF. Links below.
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Blacksmith now supports GitHub Enterprise Server (GHES) and GitHub Enterprise Cloud with data residency. Companies who require their own GitHub instance or a fixed data region no longer have to pick between security and faster CI. Learn how to get set up in the comments.
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Blacksmith retweeted
It’s never been easier to ship code, but testing has still been a massive bottleneck for us… so I decided to change that 🫡 With @Cap, we’re currently making a full transition to GPUI, and a screen recorder is a strange thing to test reliably, because you can export a perfectly playable video that has the wrong frames in it. Everything appears to work until you look closer! I don’t want to ship slop, and any regressions are my worst nightmare. The faster we’re shipping code (and generously from contributors!) the more time I find myself spending trying to 100% prove that we haven’t broken something So I’ve spent the last couple of days building an automated testing harness for Cap… 🥁 It runs our actual media code through repeatable scenarios whenever a relevant PR changes it and runs simultaneously across macOS, Windows and Linux. Also made it so that a draft gets a smaller suite so feedback comes back quicker (this is great for agents!) The interesting part though is how we know whether the video is correct… To do this, we generate test videos with an ID encoded into every frame, alongside audio markers placed at exact moments. These are our video fixtures. When we put one through Cap’s exporter, we can decode the result and check which frames actually made it through So a cut would change which frame should appear next, or maybe a speed change alters when it should appear. We calculate that independently of Cap’s implementation, so the test has something to check the output against For example, if frame 125 appears where frame 126 should be, we will know. We don’t need someone to sit there watching for it! Performance gets measured too. The PR and its merge base are built on the same machine, then benchmarked in alternating runs after warming up. That gives us a comparison of CPU time before and after the change, while reducing the noise you’d get from comparing unrelated CI runs We’ve moved most of this onto @useblacksmith . One Windows test batch went from 9m 52s on GitHub-hosted runners to 2m 59s, about 3.3x faster (!!) Another went from 5m 08s to 45s. Nearly 7x faster for that test step (!!!) What I hadn’t quite expected though was how much we’d fix while building the actual harness itself In one crash recovery test, the footage lost went from 11.03 seconds to 1.03 seconds. We also fixed a decoder bug that could show a frame from 89 frames earlier after seeking, without meaningfully increasing CPU usage There’s something almost self healing about having this in a loop. We get a reproducible failure, fix the cause, and the test stays behind to catch it if it ever comes back. Each fix leaves us less dependent on remembering everything that’s gone wrong before I think now that we have this in place, the logical next step is to scale it up and run performance/regression testing autonomously from things like Sentry logs and user feedback. Definitely going to commit a decent amount of $ to it. I probably need at least another 4x Claude subs! Really excited to ship the improvements we’ve already made just from building this. With the harness mostly in place, I can move much faster on my own changes and contributor PRs. Being able to make that progress without the constant worry of breaking someone’s recording feels pretty fucking good I can’t lie 🤩
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Blacksmith is in the Disruptors 60 Class of 2026, curated by @GreenfieldVC at @TechCrunch Disrupt. Writing code isn’t the slow part anymore. Every generated change still has to be built and tested before it merges. 10,000+ companies run that step on Blacksmith.
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Go build caching is now enabled by default for every Blacksmith org, free of charge. Across customer CI jobs, the median Go step got 20% faster and the slowest ones got 74% faster, with one test suite dropping from 58s to 5s. Try now, link in first comment.
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Blacksmith retweeted
We were fortunate enough to have our CI accelerated and sponsored by @useblacksmith Simply swapping to blacksmith accelerated build times by nearly 2x. We then layered on more improvements. @blankparticle wrote about it here: alchemy.run/blog/2026-09-24-…
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Two days at @WeAreDevs talking about what happens when agents write more code than ever and CI becomes the bottleneck. Our CEO @adijayaprakash covered the shift, Piotr Bejda the infrastructure behind it, and Abbe Piels showed engineers how to move CI to Blacksmith with one line of YAML. More highlights soon.
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Blacksmith retweeted
Imagine running agents on your boy’s hotspot at the Beford L grind sesh
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Most important part missing. Switch to @useblacksmith 🫡
Agents were shipping code faster than our CI pipeline could keep up. Our team optimized our pipeline, leading to a roughly 15% faster test suite and 50% reduction in runner-time spent per test, all while our test suite grew 4x in size. @moofeez explains how: linear.app/now/ci-bottleneck…
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We schedule more than 10 million CI jobs a day, and CI is one of the spikiest workloads that exists. When all your developers are pushing code, we routinely see a customer go from 0 to tens of thousands of CPUs for a few minutes and then settle back down. Extrapolate that across 7,000 customers of different sizes and bin packing becomes a genuinely hard technical problem. No one better than @ajwerner to think about this and solve it. Before designing anything, he built a simulator on top of our production data so he could replay real traffic against candidate designs and see how each one held up. The simulator is in the post, and you can play with it yourself! Link in comments.
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been working on devex with an awesome team, we've seen incredible results by introducing: - automatic PR approvals w/ evals against all historical incidents - 10x faster CI by updating build tools & using @useblacksmith - preview environments for every PR
We 3x'ed PRs in 6 months at Amplitude by building an autonomous software factory: - PR cycle time 5.2 hours to 44 minutes - Frontend CI: 30 minutes to 3-4 minutes - Bug reports down 55% - 5% of our PRs now come from designers and product managers - 3x the PRs with the same headcount What worked: faster CI, risk-based auto-approval, automated legacy migrations, and the hardest part: cultural changes in the team. amplitude.com/3x Bonus: our designers even built out an interactive video game you can play to tell the story. Data monster speedruns the development pipeline.
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Anthropic reported 25x growth in CI job volume over six months. For context, that lands above the 99th percentile in our data. They’re part of a small group experiencing explosive growth, but they’re not the only ones. Across more than 1,200 organizations from March to August, half grew by more than 1.87x. But the fastest-growing 10% grew 5.95x, and the fastest-growing 1% grew 19.24x! The companies pushing hardest into agentic coding are giving us a preview of what's coming. It’s a simple formula really: more code = more changes = more tests = a lot more CI. It’s great that software companies can pump out more code than they ever imagined, but someone still has to validate it. As AI code-gen scales, CI becomes the backbone of the modern org, where it needs to absorb an entirely new scale and pattern of work that didn’t exist before. If you’re curious how the fastest moving companies are navigating code validation in this new era, then stay tuned for our upcoming Blacksmith CI index; we’ve got a lot more to share. Anthropic source in first comment.
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How do you know when a scheduling approach stops working as you scale? We built simulations to find out, and used them to validate our scheduler designs as we built them. Andrew Werner (@ajwerner) ran them live at infra.nyc last week. Thanks to Megan for having us, and to Chelsea Dole and the other speakers for a great evening. Interactive version + technical deep dive coming this week 👀
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Before it became an anvil head, [code]smith almost ended up as a hammer with eyes, a literal blacksmith, or a clanker robot. We tried them all. Here’s the story behind how we designed the character, brought it to life, and made room for some fun personality in a product that takes performance really seriously. Read more here: blacksmith.sh/blog/does-a-co…
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