Resonant Computing: Between Manifestos and Cynicism
The debate around resonant computing reveals two absolutist positions, and neither serves users well.
Context
In late 2025, a group of technologists published the Resonant Computing Manifesto. The document, signed by figures like Tim O'Reilly, Kevin Kelly, and Bruce Schneier, argues that software should work more like good architecture. Beautiful buildings and bustling courtyards invite you to slow down, the manifesto says. Software could do the same. With AI, it finally can.
Within weeks, the blog Pivot to AI published a counter-argument. The author frames the manifesto as another tech industry exercise in lofty language that masks the same incentive structures it claims to oppose. Christopher Alexander's architectural philosophy, co-opted by people building venture-backed products. The critique is blunt: these are the same people, with the same business models, wrapping capitalism in poetic language.
Both positions are concrete. Both are absolute. And that is the problem.
"We shape our environments, and thereafter they shape us." The manifesto borrows this idea from architecture. The question is whether a signed document from Silicon Valley can deliver on it.
The Manifesto's Position
The Resonant Computing Manifesto opens with Christopher Alexander's concept of "the quality without a name," the feeling that certain built environments leave you more human, more alive. The authors apply this to software. Current technology, they argue, is designed around hyper-scale: feeds that hijack attention, platforms that mediate every transaction while draining warmth from the experience.
AI creates an opening. Software no longer needs one-size-fits-all solutions. It can adapt to the context and needs of each person. The manifesto lays out five principles: private, dedicated, plural, adaptable, prosocial. These are reasonable goals. Software that works for you, not against you. Data stewardship in the hands of users. Distributed power instead of centralized control.
The vision is appealing. A world where technology functions like a well-designed courtyard: inviting, human-scaled, alive. The signatories include respected thinkers across technology, design, and policy.
The Critique
David Gerard's response on Pivot to AI places the manifesto in a lineage of Silicon Valley declarations dating back to the 1990s. The "Declaration of the Independence of Cyberspace" was written at Davos. The Cluetrain Manifesto promised a new corporate honesty. These documents aged poorly. Gerard argues the Resonant Computing Manifesto is the same pattern: feel-good language from the people who caused the problems it describes.
The technical objections are direct. Software that "adaptively shapes itself" to each user does not exist. Chatbots are not adaptive, which is why companies keep retraining and releasing new ones. Gerard challenges readers to ask any signatory to hand over the software that "can now" do what the manifesto claims. He also notes that running AI locally requires expensive hardware that vendors themselves have made more costly.
Gerard's alternative: regulations with teeth, consumer protections, antitrust enforcement, larger fines. The problem is political, he argues, not technological. Building a bigger chatbot will not fix structural issues created by the same people who wrote the manifesto. There is validity in this. History shows that tech manifestos rarely survive contact with quarterly earnings.
Where Both Miss
The manifesto prescribes how technology should make people feel. The critique prescribes how people should view the manifesto's authors. Both are telling you what to think. Neither leaves room for the person using the technology to decide for themselves.
This is the friction. Two camps shouting past each other, each certain about what AI should be. One says AI should resonate with your deeper values. The other says the people saying that are lying. These positions generate heat. They do not generate understanding.
The more useful framing: treat both as perspectives. The manifesto offers a design philosophy worth considering. The critique offers a skepticism worth holding. Neither is the whole picture. Combining them gives you something more honest than either alone.
Social dynamics between humans and machines are not universal. My experience of interacting with AI is different from yours. My values are different. We might share similar shades of preference, but the specifics diverge. Prescribing a single methodology for how all users should relate to AI, or how all AI should relate to users, misses this. It flattens a space that is inherently individual.
Key Points
- The Resonant Computing Manifesto proposes five principles for human-centered AI: private, dedicated, plural, adaptable, prosocial
- Critics argue the manifesto repackages existing tech industry incentives in aspirational language
- Both positions are absolutist, leaving no room for individual user context
- Human-machine social dynamics are unique to each person and their values
- Personal AI systems running on local devices could make alignment with individual values possible
- The iPhone analogy applies: AI becomes universal when it becomes personal and portable
A Different Path: Personal AI
Instead of prescribing what AI should be for everyone, consider what it could be for each person. The manifesto's principles work better as a self-assessment tool than as an industry standard. Ask yourself which of those five principles matter most to you. Your answer will differ from mine. That is the point.
The path toward AI that actually serves individuals runs through a specific technical direction: models that can run on personal devices. Think about the iPhone. Smartphones did not become transformative when they were powerful. They became transformative when they were personal. Always with you. Offline-capable. Contextual to your life.
AI follows the same trajectory. When models run on low-power local hardware, they stop being services you access and start being tools you own. No server logs. No data extraction. No hidden agendas from the platform operator. The AI becomes yours in the same way your phone is yours.
This is where the manifesto's principles become achievable without requiring trust in any particular company or signatory. Private by architecture, not by policy. Dedicated because there is no other customer. Adaptable because the model learns your context, not an aggregate profile.
Open Questions
Personal, offline AI raises its own set of problems. Models that run on consumer hardware are smaller and less capable. Fine-tuning on personal data requires technical knowledge most people do not have. And local-only systems miss the benefits of shared intelligence: the reason centralized models are useful is that they learn from everyone.
The deeper question is whether the tech industry will build toward personal AI or away from it. The economics favor centralization. Server-side models generate recurring revenue and data flywheels. Client-side models do not. The manifesto's signatories could prove the critics wrong by building in this direction. Until then, both the optimism and the skepticism remain unresolved.