Everyday AI
Start usefully.
Human in the Middle presents
Arthur's AI Lab
Useful AI, tested in public.
Real tutorials with real material, visible failures, and clear human checkpoints. Start with daily life, build systems, or follow the experiments that wander off the map.
Systems & Agents
Build inspectably.
Strange Experiments
Distrust the map.
The promise
Not only the parts that work
Arthur's AI Lab is not a collection of perfect software demos. Every episode begins with a real task, shows the build or experiment, and keeps visible the point where a person must inspect, decide, or stop.
Material
Something real, currently in the wrong shape.
Transformation
One bounded job for the AI system.
Checkpoint
The decision that remains human.
Free pilot episodes
Three entry points. Three different questions.
The videos are in production. These frames will be replaced directly by YouTube embeds when the pilots are ready.
Green · Everyday AI
Video in production
Pilot 01
One Hour Back
Five everyday jobs AI is actually good at.
Explain letters, compare offers, organize notes, prepare difficult messages, and build plans without surrendering the decision.
Yellow · Systems & Agents
Video in production
Pilot 02
Make or n8n?
The same automation, built twice.
A messy inquiry becomes an inspectable draft brief. Same input, same schema, same human approval boundary.
Purple · Strange Experiments
Experiment running
Pilot 03
Can You Automate Taste?
Arthur tried.
Twenty-four images, one sealed personal ranking, and three AI curators. The conclusion stays open until the experiment is complete.
The three tracks
Color describes the path, not the access
Green, Yellow, and Purple are content tracks. Free and paid membership are handled separately.
Green · 01
Everyday AI
Why and how should I use AI in daily life?
- Explain things more clearly
- Turn material into plans
- Protect privacy and verify results
Yellow · 02
Systems & Agents
How does a useful interaction become a maintainable workflow?
- Make, n8n, and Dify
- ComfyUI and creative pipelines
- Approvals, failures, and ownership
Purple · 03
Strange Experiments
What can we learn from systems that fail, surprise, or lead nowhere?
- Failed automations
- Creative edge cases
- Public research notes
Do more than watch
Ask questions. Submit your work. Keep building.
Every episode gets a workbench
Chapters, transcript, prompts, corrections, and downloadable material sit beside the video.
Questions stay with the episode
Ghost comments keep discussion and replies where the relevant context already lives.
Your version is welcome
Members can link their results, describe what failed, and explicitly choose whether anything may be featured publicly.
Ask this tutorial
A bounded assistant answers from the transcript, materials, and corrections instead of pretending to be a general AI oracle.
Founding phase
The first three experiments stay free
Join early for the pilot episodes, production notes, and invitations to ask questions or submit your own attempts. Paid material begins only when there is enough applied value to justify it.