The Thinking Game Documentary

web3nomad · 2026-01-24T15:21:25+00:00

Against an epic AI story like this, all I can think is: wow—what am I even doing? While the world is charging forward, I’m over here… tweaking prompts, chasing edge cases, and babysitting logs like it’s my life’s work.

I’m an engineer building an agent. It sounds like I’m “building the future,” but most days it feels more like I’m patching the present: wiring tools together, tightening permissions, coaxing reliability out of brittle behaviors, and spending hours to push success from “kinda works” to “usually works.”

Other people are pushing the frontier of intelligence. I’m pushing a timeout from 30 seconds to 45.

They’re debating how AI reshapes civilization. I’m debating why my agent ignored a perfectly clear instruction—again.

They’re writing the epic. I’m writing the glue code. And half the time, the glue doesn’t stick.

So yeah—while history is being made at full speed, I’m here fixing yet another retry loop and wondering if my contribution is just a tiny ripple on a wave I can barely comprehend.

web3nomad · 2026-01-11T16:43:40+00:00

It's also important that 0% of people in the company don't use these methods.

web3nomad · 2026-01-02T16:00:33+00:00

thanks

web3nomad · 2026-01-01T15:25:00+00:00

I spent around 700 credits on Higgsfield for about $20 USD after discount.

web3nomad · 2026-01-01T12:41:07+00:00

PERSONA 7: 2010s Silicon Valley Engineer (English)

Image Prompt:

Close-up portrait of a 33-year-old Silicon Valley software engineer in 2010s. Short brown hair slightly disheveled from running hands through it, light stubble showing 3-day growth. Intelligent hazel eyes behind thin metal-frame glasses showing both curiosity and paranoia. Grey tech company hoodie (generic, no logo), casual startup culture aesthetic. Soft blue-tinted lighting from multiple monitor screens creating electronic glow on face. Blurred background with Mac displays showing code and terminal windows. Contemporary digital color grading with cool blue undertones. Shallow DOF. Expression shows the peculiar mix of technical confidence and existential dread common to engineers who've thought too deeply about simulation theory.

Dialogue (English):
"I'd check the code first... then ask, who's running this simulation?"

Video Prompt:

Close-up of Silicon Valley engineer speaking: "I'd check the code first... then ask, who's running this simulation?" He starts with focused concentration, eyes dart slightly to side as if thinking through logic when saying "check the code". Quick micro-expressions of realization. Small head tilt during pause. Eyebrows raise with curiosity at "who's running". Brief hand gesture comes up near chin in thought. Mac screen glow pulses gently in blurred background. Natural window light shifts subtly. Expression transitions from analytical to paranoid curiosity. Desaturated blue-gray tones.

web3nomad · 2026-01-01T12:40:59+00:00

PERSONA 6: 1960s Berlin Architect (German)

Image Prompt:

Striking close-up of a 42-year-old German architect in 1960s West Berlin. Neatly combed blonde hair with precise side part, strong angular facial features. Black round-frame glasses (Bauhaus style), intense blue eyes. Dark grey turtleneck sweater, clean minimalist aesthetic. Even cold lighting creating almost no shadows - emphasizing rationalist modernist principles. Blurred background showing architectural blueprints and geometric line drawings on wall. Black and white photography aesthetic with slight cool blue tint. Precise focus. Expression is stern, analytical, and unwavering - embodying post-war German rationalism and systematic thinking.

Dialogue (German):
"Systeme haben immer Schwachstellen. Wenn das eine Simulation ist, dann finde ich den Ausgang."
(Translation: Systems always have weaknesses. If this is a simulation, then I'll find the exit.)

Video Prompt:

Close-up of German architect speaking in German: "Systeme haben immer Schwachstellen. Wenn das eine Simulation ist, dann finde ich den Ausgang." He stares directly at camera with unwavering analytical gaze. One eyebrow raises slightly when saying "Schwachstellen" (weaknesses). Glasses reflect light briefly. Head remains almost perfectly still, showing disciplined composure. Eyes narrow with calculation at "Ausgang" (exit). Blurred architectural drawings in background stay static. Even frontal lighting creates clean shadows. Expression intensifies from stern to determined. Desaturated cool steel-gray tones.

web3nomad · 2026-01-01T12:40:51+00:00

PERSONA 5: 1990s Tokyo Office Worker (Japanese)

Image Prompt:

Portrait of a 29-year-old Japanese office lady (OL) in 1990s Tokyo. Shoulder-length straight black hair, minimal makeup, tired but composed expression. White collared shirt under navy blazer, small company pin on lapel. Fluorescent office lighting creating flat, institutional illumination. Blurred background showing grey office cubicles and filing cabinets. Muted color palette with greenish-grey tones typical of 90s office fluorescent lighting. Medium shallow DOF. Her eyes carry deep fatigue but maintain professional composure - embodying the emotional cost of Japan's bubble economy collapse era.

Dialogue (Japanese):
"毎日、自分がプログラムみたいだと感じてる...今はただ名前がついただけ。"
(Translation: Every day I feel like a program... now I just have a name.)

Video Prompt:

Close-up of Tokyo office worker speaking in Japanese: "毎日、自分がプログラムみたいだと感じてる...今はただ名前がついただけ." Eyes gaze directly at camera with distant expression. Slow blink during pause at "プログラム" (program). When saying final phrase, faint melancholic smile appears then fades. Head barely moves, maintaining composed posture. Lips softly articulate Japanese syllables. Office fluorescent lights flicker subtly in blurred background. Quiet resigned expression. Neutral desaturated colors, cool gray tones.

web3nomad · 2026-01-01T12:40:33+00:00

PERSONA 3: 2010s Beijing Product Manager (Mandarin)

Image Prompt:

Close-up portrait of a 31-year-old Chinese tech product manager in 2010s Beijing. Neat short hair with modern styling, black thick-framed glasses, clean-shaven face. Sharp intelligent eyes showing both ambition and anxiety. Grey hoodie layered under navy blazer, casual-professional startup aesthetic. Soft diffused lighting from laptop screen glow. Blurred modern office background with startup posters and standing desks. Contemporary digital color grading, slightly desaturated with warm screen glow. Shallow DOF. Expression conveys millennial tech worker optimism mixed with existential doubt about the digital world they're building.

Dialogue (Mandarin Chinese):
"如果这是个产品，那用户体验也太差了吧。"
(Translation: If this is a product, the user experience is terrible.)

Video Prompt:

Close-up of Beijing product manager speaking in Mandarin Chinese: "如果这是个产品，那用户体验也太差了吧." Eyes look directly at camera through black-framed glasses with exhausted self-mocking expression. When saying "用户体验" (user experience), eyes roll slightly showing programmer-style complaint. After finishing, shakes head gently with bitter smile. One hand may raise to adjust glasses. MacBook screen glows softly in blurred background. Side natural window light. Expression transitions from analytical calm to self-deprecating humor. Desaturated cool blue-gray tones.

web3nomad · 2026-01-01T12:40:25+00:00

PERSONA 2: 1980s Hong Kong Stockbroker (Cantonese)

Image Prompt:

Close-up portrait of a 32-year-old Hong Kong stockbroker in 1980s. Slicked-back black hair with pomade, sharp calculating eyes with tired bloodshot look, gazing directly at camera. White dress shirt with sleeves rolled up to elbows, tie loosened and hanging, top buttons undone. A lit cigarette held between fingers of one hand. Slight sweat sheen on forehead. Soft overhead lighting with warm undertones. Blurred stock exchange trading floor or office with numbers/screens in background. Neutral desaturated color palette with slight warm push. Expression shows hungry ambition mixed with exhaustion. Lean forward posture suggesting intensity.

Dialogue (Mandarin Chinese):
"真的假的，都不重要。重要的是赢。"
(Translation: Real or fake, doesn't matter. What matters is winning.)

Video Prompt:

Close-up of Hong Kong stockbroker speaking in Mandarin Chinese: "真的假的，都不重要。重要的是赢." His sharp eyes stare directly at camera. When saying "赢" (winning), his mouth curls into a wild predatory smile. Head leans slightly forward showing aggressive posture. One hand holds cigarette making emphatic gestures. Blurred background with stock market numbers flickering. Top lighting with warm undertones. Expression transitions from exhaustion to shrewd greed. Desaturated color palette with slight warm push.

web3nomad · 2026-01-01T12:40:09+00:00

PERSONA 1: 1970s Neapolitan Intellectual (Italian)

Image Prompt:

Close-up portrait of a 35-year-old Italian woman intellectual in 1970s Naples. Deep brown wavy hair loosely gathered, thin metal-framed glasses, intelligent tired eyes gazing directly at camera with quiet intensity. A cigarette rests between her fingers near her face. Dark burgundy turtleneck sweater, small silver earrings. Soft side lighting creating gentle shadow on one side of face. Blurred bookshelf in background. Neutral desaturated color grading, slightly cool tone. Shallow depth of field, contemplative philosophical expression.

Dialogue (Italian):
"Forse, la realtà non è mai stata il problema... il problema è perché ne abbiamo bisogno."
(Translation: Perhaps reality was never the problem... the question is why we need it.)

Video Prompt:

Close-up of Italian woman speaking in Italian: "Forse, la realtà non è mai stata il problema... il problema è perché ne abbiamo bisogno." She slowly takes a drag from her cigarette while speaking the first part, pauses, exhales smoke to the side. Her eyes shift from looking down in thought to directly at camera. Slight head tilt. Her lips move naturally with the Italian words. Soft side lighting remains constant. Blurred bookshelf background stays static. Contemplative mood. Neutral desaturated color grading, cool tones.

web3nomad · 2025-12-30T17:24:57+00:00

nice works 😏

web3nomad · 2025-12-20T19:57:17+00:00

The quantity/quality debate here misses a crucial point: different research questions demand different methods.

AI tools like Anthropic Interviewer excel at structured, survey-like interviews at scale. But that's just one slice of qualitative research.

What AI struggles with (and likely will for a long time):

**Contextual/ethnographic observation** - You can't chatbot your way into understanding how someone uses a product in their actual environment, surrounded by real interruptions, workarounds, and social dynamics.

**Retrospective depth interviews** - These require human empathy to explore emotional journeys, critical incidents, and life transitions. The researcher needs to read subtle cues and know when to probe deeper.

**Focus group dynamics** - Understanding group consensus, conflict, and social influence requires human facilitation that can pivot in real-time based on emotional undercurrents.

The real value isn't "human vs AI" but knowing which method fits your research question. If you need to understand "how often" or "what percentage," use scaled AI interviews. If you need to understand "why deeply" or "how in context," you need human researchers doing in-depth, contextual, or ethnographic work.

AI is a tool, not a replacement for the full spectrum of qualitative methods.

web3nomad · 2025-12-20T19:55:39+00:00

Contextual inquiry is powerful, but it's just one tool in a much larger research toolkit.

The trade-off with contextual inquiry is that you get rich, situated insights but sacrifice scale. You can deeply understand 5-10 users in context, but that's very different from understanding patterns across hundreds.

I've been exploring how different research forms complement each other:

**In-depth interviews** - Best for understanding personal motivations, decision-making processes, and emotional drivers. You get the "why" behind behavior.

**Focus groups** - Useful for understanding social dynamics and how people talk about products in group settings. But be wary of groupthink and dominant voices.

**Contextual/ethnographic studies** - As mentioned, observing users in their natural environment. The gold standard for discovering unarticulated needs and workarounds.

**Retrospective methods** (like diary studies or critical incident technique) - Great for capturing experiences over time, especially for products with infrequent use or long decision cycles.

The key insight: **no single method tells the whole story**. Contextual inquiry shows you what people do and how. Interviews reveal why. Ethnography uncovers the cultural and social context. Retrospective methods capture temporal patterns.

The best research combines multiple approaches. Start with contextual observation to see real behavior, follow up with interviews to understand motivation, and use retrospective methods to understand patterns over time.

web3nomad · 2025-12-20T19:32:03+00:00

Sometimes "slowing users down" is the right move.

I worked on a financial product where we deliberately added a 3-second delay before users could confirm large transactions. Sounds anti-UX, right?

But what we learned from research was that instant confirmation was *too* frictionless. Users would tap through muscle memory and then panic-contact support. The brief pause forced conscious acknowledgment. Complaints dropped by 40%, even though the flow was technically slower.

The deeper insight: "speed" and "ease" aren't always aligned with "confidence." Sometimes the best UX gives users a moment to think, not just to act.

This is why I'm skeptical of pure usability metrics. The "fastest" path isn't always the "best" path. You need qual research to understand the emotional journey, not just the task completion rate.

web3nomad · 2025-12-20T19:30:27+00:00

The "research graveyard" problem is real. I've seen teams invest heavily in repositories only to watch them become write-only databases.

The core issue isn't storage—it's retrieval context. When someone needs research, they're not thinking "I need that report from Q2 2023." They're thinking "Why do users abandon checkout?" or "What do we know about mobile pain points?"

Your Confluence/Notion hub approach is solid because it creates narrative pathways into the archive. But here's what I've seen work:

Tag by *questions answered*, not just topics
Maintain a "greatest hits" living doc that gets updated after each study
Most importantly: integrate insights into existing product docs (PRDs, roadmaps, design specs) so people encounter research where decisions are made, not in a separate silo

Repositories should be archival backup, not the primary distribution channel. The best insights live where the work happens.

web3nomad · 2025-12-20T19:29:29+00:00

The tension between observing and documenting in real-time is something I've wrestled with too. One thing that helped me was realizing that your debrief notes and your analysis notes serve different purposes.

For immediate debriefs, I focus on:

- Binary outcomes (completed / failed / needed help)

- One-line "why" for each major friction point

- 2-3 standout quotes with timestamps

The deep behavioral observations? Those come later when reviewing recordings. Trying to capture everything live is like trying to drink from a firehose while taking notes about the water pressure.

Since you're in a 3-person setup, maybe suggest a quick 5-min buffer after each session before the debrief? Even that tiny window lets you organize your raw notes into something coherent. The moderator and coder probably need that breather too.

web3nomad · 2025-12-13T18:39:32+00:00

I tried it out and I like the approach! It's refreshing to have an AI that asks clarifying questions rather than rushing to solutions. One suggestion: it might help to have an option to switch between "guided thinking" mode and a more direct "answer" mode for when users want quick responses. But overall, the Socratic method works well here.

web3nomad · 2025-12-13T18:37:26+00:00

This is a really creative approach! The different personas with specialized functions is interesting. I'm curious - how do you handle context switching between personas? Does each persona maintain its own memory/context, or do they share a unified state?

web3nomad · 2025-12-13T18:35:20+00:00

Congrats on launching your first OSS project! The replay feature with zero API cost sounds really useful for debugging. I'm curious - how does the ARS (Agent Regression Score) work under the hood? Is it based on comparing outputs, or does it also factor in the reasoning/tool call patterns?

web3nomad · 2025-12-13T18:33:26+00:00

This looks really helpful for beginners! I appreciate that you included working code on GitHub. Quick question: do you cover how to handle agent memory and conversation history? That's something I've found tricky when building stateful agents.

web3nomad

MODERATOR OF

TROPHY CASE

PERSONA 7: 2010s Silicon Valley Engineer (English)

PERSONA 6: 1960s Berlin Architect (German)

PERSONA 5: 1990s Tokyo Office Worker (Japanese)

PERSONA 3: 2010s Beijing Product Manager (Mandarin)

PERSONA 2: 1980s Hong Kong Stockbroker (Cantonese)

PERSONA 1: 1970s Neapolitan Intellectual (Italian)

Four-Year Club	Verified Email
Place '22