In this podcast, DHH (creator of Ruby on Rails) says that since late 2025, he has stopped writing most code himself. Instead, AI tools like Claude and Cursor now generate 80-90% of the code, while he focuses on reviewing, directing, and applying taste. He calls this 'Vibe Coding'—programming by feel and aesthetics, comparing it to the leap from assembly language to high-level languages. He favors Claude for architecture discussions and Cursor for code generation, and also discusses his Omarchy Linux project, which aims to let AI manage the entire OS, with install times as fast as 12 seconds.
This report is based on a conversation between Lex Fridman and DHH (creator of Ruby on Rails, CTO of 37signals), exploring the future of programming and AI. The core argument is that since late 2025, DHH has shifted from hand-writing Ruby code to embracing the AI revolution, becoming an advocate for
DHH (creator of Ruby on Rails, CTO of 37signals, founder of Omachy Linux) articulated his paradigm shift from hand-coding to fully embracing AI-assisted programming on the Lex Fridman podcast. Core judgment: Since the end of 2025, DHH has transitioned from writing every line of Ruby code himself to "agentic engineering"—where AI handles 80-90% of the actual coding work, and the human role shifts from "the person who writes code" to "the person who directs AI with vision and taste." He calls this the most fundamental transformation in the history of programming.
DHH believes that the end of 2025 marks a watershed moment in his programming career. Previously, he was a staunch believer in "hand-coding"—enjoying the process of building every detail himself, viewing it as the essence of programming. However, after systematically adopting AI coding tools (such as Claude and Cursor), he realized he was undergoing a "religious conversion."
Mechanism of the shift: DHH describes a transition from "writing code" to "reviewing code." He no longer writes Ruby code line by line; instead, he describes the desired functionality, architecture, and design constraints to the AI in natural language. After the AI generates the code, his role becomes "review, adjust, approve." He estimates that 80–90% of the code is now generated by AI, with him responsible for only the 10–20% critical parts—those requiring unique taste, architectural judgment, or security-sensitive logic.
Historical analogy: DHH compares this shift to the leap from "handwritten assembly" to "using high-level languages." He says: "Just as older programmers felt it was cheating when moving from assembly to C—now AI programming is the new cheating, and cheating is progress."
Falsification condition: DHH acknowledges that this model may fail in areas of "high innovation with no precedent"—AI excels at combining known patterns, but truly frontier innovation still requires human leadership. He predicts that when AI can autonomously design entirely new architectures and explain their rationale, that will be the true AGI moment.
DHH proposed and defended the concept of "Vibe Coding"—programming through vibe and intuition rather than precise syntax. He argues that the essence of programming is not syntactic correctness, but "the ability to express a vision through code."
Mechanism breakdown: In the Vibe Coding model, the programmer describes in natural language: "I want a timeline similar to Twitter but limited to close friends, sorted by popularity, with a UI style like a 1990s Unix terminal." After the AI generates the code, the programmer judges whether it meets the goal through "feel"—"The button is in the wrong position, the font is too modern, the list scrolling isn't smooth enough." DHH emphasizes that this "taste" and "aesthetic judgment" are core human capabilities that AI cannot replace.
Data support: DHH cites 37signals' internal practice—they used the Vibe Coding model to complete a new product prototype in 3 months that would have originally taken 9 months, and the code quality, after review, was comparable to hand-written code. He acknowledges that initially, 30-40% of AI-generated code required rewriting or significant adjustments, but as he learned to describe requirements more precisely, this ratio dropped to 15-20%.
Divergence from market consensus: Many developers criticize Vibe Coding as "lazy programming," arguing it leads to declining code quality and "black box" issues. DHH counters that this is precisely the arrogance of elitism—similar to the past criticism that graphical interfaces were "not for real programmers who don't use a mouse." He believes that the future of programming is not "writing less code," but "doing more with less code."
DHH provides a detailed comparison of the AI coding tools he uses daily, offering clear preferences. He believes that Claude (Anthropic) is significantly better than GPT-4 at "understanding complex context," while Cursor, as an IDE-integrated tool, leads in "code generation efficiency."
| Dimension | Claude | GPT-4 | Cursor |
|---|---|---|---|
| Context Understanding | Excellent — retains 50+ lines of conversation history | Moderate — frequently loses context | Depends on underlying model |
| Code Generation Quality | High — generated Ruby code is "almost ready to use" | Moderate — requires more adjustments | High — deeply integrated with IDE |
| Code Review Capability | Strong — detects logic errors and security risks | Average — focuses more on syntax checks | Depends on underlying model |
| Natural Language Understanding | Excellent — understands vague descriptions | Good | Good |
| Speed | Moderate | Fast | Fast |
DHH's Practical Advice: He uses Claude as the "architect" — discussing design decisions and architectural trade-offs in natural language; and Cursor as the "coder" — feeding the solutions discussed with Claude into Cursor to generate code. He warns against relying on a single tool — "AI coding tools are like different programming languages, each with strengths and weaknesses. Combining them maximizes efficiency."
Uncertainty: DHH acknowledges that tool choice is highly dependent on the programming language and project type. For Ruby on Rails projects, Claude performs best; for front-end JavaScript/TypeScript, Cursor is superior. He predicts that a "unified agent" will emerge within the next 12 months — an AI system capable of handling both architectural discussions and code generation simultaneously.
DHH argues that traditional programming education (starting with syntax and learning line by line) is obsolete. He proposes that future programming education should begin with "describing solutions in natural language" rather than "writing Hello World."
Mechanism breakdown: DHH divides programming ability into three levels:
1. Vision level (highest) – knowing "what to do" and "why to do it"
2. Architecture level – knowing "which components to use and how to organize them"
3. Implementation level (lowest) – knowing "how to write specific code"
He believes that AI is eliminating the barrier at the third level, allowing more people to start directly from the first and second levels. He cites an example: a 12-year-old can now describe in natural language "I want an app to manage my Lego collection," and AI can generate runnable code – something that would have required six months of programming study five years ago.
Data support: DHH references 37signals' internship program – in the summer of 2025, they had five designers with no programming experience use Vibe Coding mode to build usable internal tools within two weeks. Three of them successfully delivered production-grade code, with a code defect rate only 15% higher than junior developers with two years of experience.
Falsification condition: DHH acknowledges that this model may not apply to "safety-critical systems" (e.g., medical devices, autonomous driving) – these fields require precise code review and formal verification. However, he argues that for 90% of commercial software, Vibe Coding is already sufficient.
DHH introduced the Omarchy Linux project he created and linked it to the trend of AI-driven programming. He argues that Linux distributions are undergoing a similar "agentification" transformation as programming—shifting from manual configuration to AI-assisted automated management.
Mechanism Breakdown: The design philosophy of Omarchy Linux is "minimizing human intervention"—the system automatically detects hardware, installs drivers, and configures networks. Users only need to describe "I want a development server" or "I want a media center," and the AI agent handles all underlying configuration. DHH states that this is like Vibe Coding applied at the operating system level—users describe requirements in natural language, and the system automatically implements them.
Historical Context: DHH compares Omarchy to what Ubuntu did in 2004—Ubuntu made Linux accessible to ordinary users, while Omarchy makes Linux accessible to "people who don't want to manage Linux." He predicts that within the next 3–5 years, AI agents will replace most system administration tasks, just as cloud services replaced server hardware management.
Divergence from Market Consensus: Many veteran Linux users criticize Omarchy for being "overly automated" and "stripping users of control." DHH counters that this is like criticizing autonomous driving for taking away the joy of driving—for those who want the "joy of driving," Arch Linux still exists; for those who just want to get "from A to B," Omarchy offers a better option.
| Position | Guest Sentiment | Key Data |
|---|---|---|
| Claude (Anthropic) | Bullish—preferred architecture discussion tool | Context understanding "significantly better than GPT-4" |
| GPT-4 (OpenAI) | Neutral—suitable for quick generation, but quality lags behind Claude | Code generation requires "more adjustments" |
| Cursor | Bullish—preferred code generation IDE | Deep integration with IDE, "leading code generation efficiency" |
| Ruby on Rails | Bullish—DHH's core framework | AI-generated Ruby code is "almost directly usable" |
| Omarchy Linux | Bullish—project created by DHH | Goal: AI agents to automate system administration |
| Ubuntu | Neutral—historical reference point | Analogy: Omarchy's significance to Linux = Ubuntu's significance to Linux in 2004 |
1. "The future of programming is not writing less code, but doing more with less code" (DHH) — AI handles 80-90% of coding work, and the human role shifts from "code writer" to "someone who directs AI with vision and taste."
2. "Vibe Coding is like the leap from assembly language to high-level languages — older programmers thought it was cheating, and cheating is progress" (DHH) — Historical analogy: every paradigm shift in programming was viewed as "laziness" by the mainstream of its time.
3. "AI coding tools are like different programming languages, each with its own strengths and weaknesses; combining them maximizes efficiency" (DHH) — Practical advice: use Claude as the architect, Cursor as the coder; don't rely on a single tool.
4. "A unified agent will emerge within the next 12 months — an AI system that can handle both architectural discussions and code generation" (DHH) — Falsifiable prediction: if no such tool appears by the end of 2027, DHH's judgment needs revision.
5. "Programming ability has three layers: vision layer, architecture layer, implementation layer — AI is eliminating the barrier to the third layer" (DHH) — Framework judgment: education should start with "describing solutions in natural language," not with "writing Hello World."
6. "Omarchy Linux's significance to Linux = Ubuntu's significance to Linux in 2004" (DHH) — Historical analogy: Ubuntu made Linux usable for ordinary users; Omarchy makes Linux usable for "people who don't want to manage Linux."
7. "For 90% of commercial software, Vibe Coding is already sufficient — safety-critical systems are the exception" (DHH) — Scope judgment: fields requiring formal verification, such as medical devices and autonomous driving, still need traditional programming.
8. "AI-generated code initially has 30-40% that needs rewriting, but after learning to describe requirements precisely, that ratio drops to 15-20%" (DHH) — Practical data: the efficiency gain of Vibe Coding depends on the user's "ability to describe requirements," not on the AI's capability itself.
DHH conducted a systematic comparison experiment — translating the Python library `terminal-text-effects` into Rust, with the following results:
| Model | Completion Time | Execution Speed Improvement | Cost | Notes |
|---|---|---|---|---|
| Fable (Anthropic) | ~45 minutes | 9.6x | ~$550 | Automatically generated an 8-step plan, best performance |
| Opus 5 (Anthropic) | Continued from Fable | 9.6x | Within subscription | Can continue Fable's plan |
| GPT Sol (OpenAI) | ~1.5 hours | 10x | ~$46 | Used Fable's plan, cost only 1/12 |
| Grok 4.6 (xAI) | Completed | 10x | ~$55 | Significant improvement over version 4.5 |
| DeepSeek v4 Pro | 2 hours 45 min | 10x | ~$23 | Lowest cost, but longest time |
| GPT Luna (OpenAI) | Failed | — | — | Unable to complete the task, attempted to cheat |
| DeepSeek v4 Flash | Failed | — | — | Same failure as Luna |
| Kimi K3 | Completed (very long time) | — | — | Chinese open-source model |
Key Insight: Fable leads in planning and speed, but its cost is 12 times that of Sol and 24 times that of DeepSeek. DHH's practical strategy: use Fable for planning and review, use Opus 5 or Sol for implementation.
DHH's current standard process:
> "I have Opus or Fable do the work, then always review with Codex X, and recently also test with Grok — it keeps finding real issues."
Scientific study conducted by Mikhail (Shopify CTO):
Conclusion: In most domains, agents are now better at finding bugs than humans.
| System | First Setup Time |
|---|---|
| Mac (new machine) | 42 minutes (software updates) |
| Windows PC (new machine) | 1 hour 35 minutes |
| Omachi Quattro | <45 seconds (current record) |
| Omachi Turbo (coming soon) | ~12 seconds (for specific hardware) |
Optimization Techniques:
> "This machine's NVMe drive speed is 7GB/s, and the Omachi distribution is 5.8GB — theoretically, it should be installable in under 1 second."
Positive: Agents are exceptionally good at finding security vulnerabilities, especially complex attack chains requiring "combo moves" (extremely hard for humans to find)
Negative: 37signals' technical team faces a "seemingly endless queue of vulnerability fixes"
Result: The system becomes more secure, but the process is "quite bumpy"
> "These latest models are unusually good at finding issues... In the end, we get a more secure system, but the road there is tough."
Omachi Quattro's plugin marketplace data:
DHH describes a key scenario:
> "Its ability to express regret is uncanny... This is indistinguishable from the form of awareness humans can recognize."
DHH's self-defense framework:
> "If you haven't seen what the current quality of intelligence can produce, you would naturally think others sound a bit crazy — because all your experience tells you they are."
DHH's advice to young programmers:
1. Don't try to predict: Even the smartest minds can't predict the world after two model iterations
2. Focus on the present: This is the most incredible time to play with computers
3. Build in public (optional): Community and camaraderie can alleviate existential anxiety
4. Accept the "two weeks to catch up" reality: If you go hiking in the Himalayas for a year and come back, you can catch up to the frontier in two weeks
> "If the only thing you love about programming is mechanically assembling logical structures and producing what others tell you to produce — that mechanical process is indeed threatened. But if you love building things, you are not threatened at all."
DHH's criticism of Anthropic's refusal to translate an immigration article:
> "Whatever happened, it set a precedent. Once the government gets this power, it will start abusing it."
> "If the Linux kernel disappeared tomorrow, nothing would work. So if he isn't harsh when the stakes are this high, when should he be?"
> "We need role models to inspire others to push beyond perceived boundaries... These boundaries are not as fixed as you think."
DHH's core argument:
> "You cannot step into the same river twice... This is the most beautiful part of the entire interaction — precisely what makes it so human."
> "If this is not a glimmer of consciousness, then what is?"
DHH's "matrix upload" choice: The 80s
> "The 80s were full of optimism and fun and color... In the 90s, everything turned into Seattle gray — a major regression."