David Heinemeier Hansson, the renowned tech entrepreneur and creator of Ruby on Rails, has expressed cautious optimism about AI’s long-term potential while remaining skeptical of its current capabilities in software development. Speaking on the “Next Token” podcast, Hansson compared AI’s current state to “a flickering light bulb” that briefly illuminates before plunging users back into darkness.
At 37 Signals, where Hansson serves as a key leader, the company has found that AI-generated code doesn’t match the quality of even junior programmers. When developing Fizzy, their Kanban-inspired organization product, humans coded 95% of the code. The company experimented with AI-powered features but ultimately left them “on the cutting room floor.” Hansson challenges the prevalent narrative that AI can enable SaaS businesses to fire half their programmers while maintaining or increasing productivity.
Despite his skepticism about current AI coding tools, Hansson acknowledges impressive implementations elsewhere. He praised Shopify, where he serves on the board, for their SiteKick AI agent that helps merchants set up and optimize their shops, calling the results “truly incredible” with “real tangible benefits.”
Hansson draws parallels between the AI revolution and the 2007 iPhone release, noting this is the first technological shift where “we, in real time, know the world is going to look totally different” without knowing the final outcome. He advises embracing uncertainty and “holding onto your hat” while riding this wave of change.
The entrepreneur expressed amazement at how much of the US economy is betting on AI achieving Artificial General Intelligence (AGI)—the theoretical point where AI matches human capabilities. “The entire American economy right now is one big bet that that’s going to happen,” he observed, marveling at the conviction to invest “100 trillion, a thousand trillion” to reach that goal. While maintaining his AI-positive stance, Hansson emphasized that AI “isn’t going away” regardless of personal preferences, though individuals can choose whether to use or purchase AI-aided products.
Key Quotes
I feel like it’s a little bit like a flickering light bulb. You’re in total darkness and then it’ll flicker on and you go like, ‘I can see everything.’ And then two seconds later, boom, pitch black.
David Heinemeier Hansson used this metaphor to describe AI’s current inconsistent performance, particularly in coding tasks. This captures the frustration many developers experience with AI tools that occasionally produce brilliant results but frequently fail to deliver reliable output.
I’m not feeling that we’re falling behind at 37 Signals in terms of our ability to produce, in terms of our ability to launch things or improve the products.
Hansson directly challenges the prevailing narrative that companies must adopt AI immediately or risk competitive disadvantage. This statement is significant because it comes from a successful tech company leader with firsthand experience, not theoretical speculation.
The entire American economy right now is one big bet that that’s going to happen. And I, as AI positive as I am, still marvel at that.
Hansson reflects on the massive economic investment in achieving Artificial General Intelligence, expressing amazement at the scale of conviction driving AI investment. This observation highlights the unprecedented nature of the current AI boom and the enormous financial stakes involved.
This is the first one where we, in real time, know the world is going to look totally different, and we don’t know what the final result is going to be.
Comparing AI to the iPhone revolution, Hansson notes the unique characteristic of this technological shift—widespread awareness of impending transformation despite uncertainty about the outcome. This perspective encourages embracing uncertainty rather than making premature commitments.
Our Take
Hansson’s perspective is particularly valuable because it comes from someone deeply embedded in both successful tech companies and the broader development community. His willingness to publicly question AI coding tools’ current effectiveness—while maintaining long-term optimism—provides a necessary counterweight to vendor hype and fear-driven narratives about AI replacing developers.
The contrast between his experience at 37 Signals and Shopify’s success with SiteKick reveals an important truth: AI’s effectiveness is highly context-dependent. Customer-facing applications that help non-technical users may see immediate benefits, while tools for expert developers face higher quality bars and more critical evaluation.
His observation about the US economy’s massive AGI bet is particularly prescient. We’re witnessing unprecedented capital allocation based largely on faith in future breakthroughs rather than current capabilities. Whether this represents visionary investment or a speculative bubble remains the defining question of our technological moment. Hansson’s measured skepticism, combined with genuine openness to AI’s potential, models the intellectual honesty this moment demands.
Why This Matters
This perspective from a prominent tech figure offers crucial balance to the AI hype cycle dominating Silicon Valley. Hansson’s real-world experience at 37 Signals provides empirical evidence that contradicts claims about AI’s immediate transformative impact on software development, particularly the notion that companies can dramatically reduce engineering headcount while maintaining productivity.
His observations highlight the gap between AI’s promise and current reality in coding applications, which matters significantly for businesses making strategic decisions about AI adoption and workforce planning. The fact that a successful tech company is thriving without heavy AI integration challenges the narrative that early AI adoption is essential for competitive survival.
Simultaneously, Hansson’s acknowledgment of successful AI implementations like Shopify’s SiteKick demonstrates that AI’s value varies dramatically by use case. His comparison to the iPhone revolution suggests we’re in an uncertain transitional period where the ultimate impact remains unclear. For investors, developers, and business leaders, this nuanced view—neither dismissive nor uncritically enthusiastic—provides a more realistic framework for navigating AI’s evolution and making informed decisions about resource allocation in an economy increasingly betting on AGI’s eventual arrival.
Related Stories
- CEOs Express Insecurity About AI Strategy and Implementation
- Tailwind CEO Blames AI for 75% Engineering Layoffs, 80% Revenue Drop
- The Future of Work in an AI World
- AI’s Role in Tech Hiring Freeze: White-Collar Job Market Slump
- Andrej Karpathy Reflects on ‘Vibe Coding’ Revolution in AI
Source: https://www.businessinsider.com/ruby-on-rails-creator-ai-coding-development-future-2026-1