{"id":794846,"date":"2026-10-07T13:20:27","date_gmt":"2026-10-07T13:20:27","guid":{"rendered":"https:\/\/www.newsbeep.com\/uk\/794846\/"},"modified":"2026-10-07T13:20:27","modified_gmt":"2026-10-07T13:20:27","slug":"rails-originator-roasted-over-rust-boosterism","status":"publish","type":"post","link":"https:\/\/www.newsbeep.com\/uk\/794846\/","title":{"rendered":"Rails originator roasted over Rust boosterism"},"content":{"rendered":"

<\/p>\n

\n devops\n <\/p>\n

<\/a><\/p>\n

\n David Heinemeier Hansson’s agent-coded bakeoff produced curious results\n <\/p>\n

Last month at Rails World 2026, Ruby on Rails creator David Heinemeier Hansson gave a relentlessly optimistic keynote<\/a>\u00a0in which he suggested AI has all but eliminated the need for developers to manually write code.\u00a0<\/p>\n

But perhaps DHH, as he is known online, shouldn\u2019t delete his code editor quite yet.<\/p>\n

On Sunday, DHH posted<\/a> about a test in which he had frontier agents implement and optimize his company\u2019s Campfire<\/a> group chat app in three languages: Elixir, Go, and Rust. He then compared the runtime performance of those versions with the original Ruby on Rails implementation.<\/p>\n

DHH\u2019s post includes data that seemingly demonstrates the efficiency of the Rust programming language, and AI agent coding itself. But many observers came to another conclusion: Don’t trust DHH\u2019s benchmarks.\u00a0<\/p>\n

As of press time, the post and accompanying chart garnered over 900,000 views. It showed the Rust rewrite of the chat app outperformed others by a wide margin on five tasks, including searching or posting a message.\u00a0<\/p>\n

DHH did not say which AI services he used for these rewrites, but noted that each rewrite took only a few hours, as the original code itself,\u00a0largely written in Ruby<\/a>, is relatively compact.<\/p>\n

Many observers, notably advocates of other languages, quickly surmised from the source material that DHH had optimized the Rust results but didn’t do the same for the other languages he tested.\u00a0<\/p>\n

Whither high-level languages?<\/p>\n

Rewriting applications in Rust, often with the help of AI agents, seems to be a popular undertaking these days, with Microsoft’s Copilot runtime<\/a>, the pnpm JavaScript installer<\/a>, and the Bun JavaScript toolchain<\/a> all getting the Rust treatment.<\/p>\n

In DHH\u2019s test, the Rust implementation handily bested the others across all five workloads, sometimes by a wide margin. To serve a \u201croom page,\u201d for instance, Rust knocked out 36,260 requests per second. In contrast, Ruby on Rails was only able to fulfill a paltry 241 requests, while Elixir delivered 722 requests, and even runner-up Golang only knocked out 3,860 requests a second.<\/p>\n

Rust executed the other tasks with similar alacrity, easily besting the other languages DHH used.\u00a0<\/p>\n

The takeaway was obvious to DHH: Rewriting an application in Rust, or better yet having AI agents do the job, may very well result in major performance improvements for an app.<\/p>\n

DHH suggested that many factors go into choosing a programming language for a particular job, and execution speed is not the sole criterion. Rust can be agonizingly slow to compile, and for many, writing or even reading Rust code is an arduous job. <\/p>\n

DHH himself began developing Rails in 2003 while building Basecamp in the then relatively obscure Ruby programming language to ease the developer experience. He doesn\u2019t seem to mind that Ruby ranked the slowest in his own tests.\u00a0<\/p>\n

\u201cI didn’t care about [performance] when the pay-off was huge in terms of productivity and developer joy.\u201d\u00a0<\/p>\n

But AI agents don\u2019t give a hoot about joy.<\/p>\n

\u201cYou really have to bury your head in the sand not to see that when agents write the code and validate the output, we need to adjust to a new reality,\u201d he wrote.<\/p>\n

Chips on the table<\/p>\n

DHH\u2019s ad-hoc test was quickly met with skepticism, criticism and outright mockery, especially on X. (It\u2019s as if DHH\u2019s conservative views on immigration<\/a> and his work to bring yet another Linux desktop<\/a> into the world didn\u2019t give him enough headaches).<\/p>\n

\u201cWhat worries me about the future of programming is you see this and don\u2019t immediately know there must be something wrong with the results or what you actually measured,\u201d wrote prominent Google engineer Jaana Dogan in an X response<\/a> to DHH\u2019s tests.<\/p>\n

Dogan did not elaborate on the test\u2019s shortcomings, but many others, especially advocates of other languages, were more than happy to provide details.\u00a0<\/p>\n

One Elixir advocate called DHH\u2019s implementation \u201cmoronic<\/a>,\u201d while a couple of others actually rewrote the Elixir code<\/a> to make its performance comparable to Rust\u2019s. After that rewrite, the Elixir version of the app bested Rust\u2019s performance on some tasks, despite further third-party Rust optimizations<\/a>.<\/p>\n

DHH expressed surprise<\/a> that others would assume a high-level language like Elixir or Ruby could even compete with a language like Rust, which runs closer to the metal. But he also noted on X<\/a> that \u201cIt’s not exactly extra points for Elixir if frontier agents can’t find the magic \u2018go fast\u2019 switches.\u201d<\/p>\n

Elsewhere, observers noted that the Rust rewrite got a lot more post-coding attention<\/a> than the other implementations of Go and Elixir, both of which seemed to be quickly wrapped up<\/a> after the initial agent requests. \u201cYou’re not benchmarking languages, you’re benchmarking how much attention each port got,\u201d one observer wrote on X<\/a>.\u00a0<\/p>\n

Golang advocates were likewise unamused. \u201cThe benchmark was unfair. More time was put into the Rust code while the rest were one-shotted,\u201d one wrote on X<\/a>. Someone else even made their own chart showing how much more the Rust code was tuned compared<\/a> to the quick passes on the other languages.\u00a0<\/p>\n

None of these rebuttals actually negates DHH\u2019s advocacy of using agents to code. But clearly, skipping a manual review of the resulting work will still leave a lot of potential gains on the table. \u00ae<\/p>\n","protected":false},"excerpt":{"rendered":"devops David Heinemeier Hansson’s agent-coded bakeoff produced curious results Last month at Rails World 2026, Ruby on Rails…\n","protected":false},"author":2,"featured_media":794847,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[20],"tags":[554,733,4308,86,56,54,55],"class_list":["post-794846","post","type-post","status-publish","format-standard","has-post-thumbnail","category-artificial-intelligence","tag-ai","tag-artificial-intelligence","tag-artificialintelligence","tag-technology","tag-uk","tag-united-kingdom","tag-unitedkingdom"],"_links":{"self":[{"href":"https:\/\/www.newsbeep.com\/uk\/wp-json\/wp\/v2\/posts\/794846","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.newsbeep.com\/uk\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.newsbeep.com\/uk\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/uk\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/uk\/wp-json\/wp\/v2\/comments?post=794846"}],"version-history":[{"count":0,"href":"https:\/\/www.newsbeep.com\/uk\/wp-json\/wp\/v2\/posts\/794846\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/uk\/wp-json\/wp\/v2\/media\/794847"}],"wp:attachment":[{"href":"https:\/\/www.newsbeep.com\/uk\/wp-json\/wp\/v2\/media?parent=794846"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.newsbeep.com\/uk\/wp-json\/wp\/v2\/categories?post=794846"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.newsbeep.com\/uk\/wp-json\/wp\/v2\/tags?post=794846"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}