A vocabulary for talking about technology that serves human flourishing. These are recurring concepts that appear across experiments and writing — named so they can be discussed, challenged, and refined.
Foundational stances that shape how we approach technology and human flourishing.
Active participation vs. passive consumption. Learning through doing.
Engaged play means encountering ideas through activity, not just reception. It’s the difference between reading about something and actually trying it.
This matters for technology design because most implementations treat users as passive recipients of information. Engaged play means designing for active participation.
Discover applications through humanist thinking, not evaluate against checklist.
Humanism as a generative lens means using humanist principles to find new possibilities, not just to judge existing ones. It’s the difference between “does this pass the ethics test?” and “what would it look like to build this with human flourishing as the goal from the start?”
A checklist approach asks whether something is ethical enough. A generative lens asks what becomes possible when you design for humans first.
Not a disposition but a practice—choosing to act as if things can improve.
Optimism as action isn’t about feeling hopeful. It’s about making choices that assume improvement is possible. It’s choosing to build something that might work, rather than accepting that nothing will.
This is different from naive optimism, which ignores obstacles. Optimism as action acknowledges the obstacles and acts anyway—because the alternative is accepting that the current state is the best we can do.
Understanding emerges from context, not abstraction. From somewhere, for someone.
Situated knowledge rejects the view from nowhere. All understanding comes from a particular position, shaped by particular experiences. Acknowledging this isn’t a weakness—it’s the foundation of honest inquiry.
This matters for technology because most systems pretend to objectivity while encoding particular perspectives. Situated knowledge makes those perspectives explicit.
How AI and software systems should relate to human capability and decision-making.
Quality out proportional to what you bring in.
AI as amplifier means the technology multiplies human capability rather than replacing it. The more you bring to the interaction—clarity of purpose, specific context, genuine thought—the more you get out.
This is different from AI as replacement, where the system’s output doesn’t depend on what the human contributes. Amplification requires—and rewards—human engagement.
Make the invisible legible so humans can act, don’t automate decisions away.
The goal of pattern visibility isn’t to remove humans from the loop—it’s to give them better information for their own decisions. Show the patterns, don’t just act on them.
This is the difference between a system that makes decisions for you based on what it sees, and a system that helps you see what it sees so you can decide.
AI that helps you notice what you couldn’t otherwise see.
Perceptual augmentation is the use of AI to extend human perception—not to make decisions for us, but to help us see patterns we’d otherwise miss.
This is different from automation, which replaces human judgment. Perceptual augmentation enhances it by making the invisible visible.
Using foresight to open possibilities, not narrow them.
Most predictive systems use their predictions to route you toward expected outcomes. Prediction that expands agency does the opposite—it uses foresight to show you paths you hadn’t considered.
The question isn’t whether AI can predict what you’ll do. It’s whether that prediction opens doors or closes them.
Patterns for building things that respect human attention and agency.
Meaningful results over scale. Clear benefits over speculation.
Bounded experiments prioritize depth over breadth. Instead of building for everyone, build something that works completely for a specific context. Prove the concept before scaling.
This runs counter to typical tech culture, which prioritizes growth above all. Bounded experiments insist on proving value before expanding scope.
Context shapes meaning. The pathway to engagement shapes what you find.
Culture as filter means that how you arrive at something changes what it is for you. The same content, reached through different pathways, carries different meaning. Context isn’t just packaging—it’s part of the message.
This has implications for design: you can’t just put content out there and assume it means the same thing to everyone. The filters people come through—their culture, their context, their pathway—shape the meaning they find.
Resistance as design principle. Optimizing for meaning, not volume.
Deliberate friction introduces intentional resistance to slow down, create space for reflection, or ensure engagement is genuine. It’s the opposite of frictionless design—but not because friction is good in itself.
The value of friction is in what it enables: pauses that create thinking, effort that creates ownership, delays that create anticipation. Friction is a tool, not a goal.
How technology mediates relationships between people and groups.
From indigenous law traditions. Relational thinking, obligations to people and place.
Respect and enablement come from indigenous legal traditions that emphasize relationships and obligations rather than just rights and rules. Respect means taking seriously the autonomy and value of others. Enablement means actively helping others achieve their purposes.
In technology, this translates to building things that treat users as capable adults with their own goals, and that actively help them achieve those goals rather than just not obstructing them.
Bringing different ways of knowing together creates something new.
Synthesis over extraction means combining insights rather than just collecting them. It’s the difference between aggregating opinions (which often produces averages) and creating something new from the combination (which can produce breakthroughs).
Extraction treats knowledge as a resource to be mined. Synthesis treats it as a conversation to be had.
Approaches to the work of building technology differently.
Asking how things actually feel to use.
Applied phenomenology means investigating experience rather than just behavior. For technology, this means asking not just “does it work?” or “do people use it?” but “how does it feel to use? What is the experience actually like?”
This is the through-line of Applied Humanism. Technology should be evaluated not just on what it does, but on what it’s like to live with. Does it leave you feeling more capable or less? More human or less? More connected to your purposes or more disconnected?
The answers aren’t always what the metrics say.
Share the journey and the struggle, not just the destination.
A trophy shows you what someone achieved. A map shows you how they got there. Both have value, but they serve different purposes. Trophies inspire; maps enable.
Map vs trophy is a choice in how you share work. Showing only results (trophies) makes the process invisible. Showing the journey (maps) gives others something they can follow, adapt, and build on.
Applied Humanism prefers maps. The point isn’t to impress, but to enable.
Proof of systematic thinking. Portable and referenceable.
When a pattern has a name, it becomes visible and discussable. Named mechanisms show that you’ve thought systematically about how something works—and they give others a way to refer to that thinking.
This patterns vocabulary is itself an example. Each pattern has a name, making it portable—you can reference “deliberate friction” without explaining it every time. The names accumulate into a vocabulary for talking about technology that serves human flourishing.
Permission to publish thinking at different stages (hot/thinking, warm/developed).
Temperature labels signal the maturity of thinking without requiring perfection. “Hot” means thinking in progress—rough, exploratory, possibly wrong. “Warm” means developed—more polished, more considered, more confident.
The value of temperature labels is publishing velocity. Without them, you either publish only finished work (slow, rare) or publish rough work without context (confusing, risky). With them, you can share thinking at any stage, as long as you’re honest about where it is.
This gives readers calibrated expectations and gives writers permission to be incomplete.
If this work resonates—or if you're building something that asks similar questions—I'd like to hear from you.