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on the street · a glasshouse at night · every lamp on

Learning, making and knowledge gardening, with AI

Learning Large

Models are spiky. Humans are too. Learning, making, and knowledge gardening, together.

A glasshouse at night, with every lamp on. They are the old kind of grow lamp, a row of red diodes and blue ones, and nothing in here looks green under them. A leaf takes in red light and blue light and turns the green away, which is why it looks green in daylight; these lamps give it the red and the blue and almost nothing between, so a leaf has no green to give back. The lamps are spiky, and so are the leaves, and so are the people at the benches, and so are the models some of us bring in with us. This room is about learning, making and knowledge gardening with generative AI, in the words of our own AI pages, with the weight where Ryan Boren’s brief for it put the weight: on our spiky profiles, and how they can complement each other.

We build with these tools carefully and name what they are: not neutral, not magic, and not a replacement for the communities whose knowledge this site holds.

— Our page AI at Stimpunks

Spiky, both of us

Our glossary has an entry for the spiky profile: strengths and difficulties further apart than most people’s, so that a graph of them comes out as peaks and troughs rather than a flat line. It is a description and not a verdict. The entry also gathers what people remember about where the phrase came from, and Damian Milton says there that he called it a spiky profile because he did not like ‘islets of ability’ or ‘uneven profile’.

we are good at some things, bad at other things, and the difference between the two tends to be much greater than it is for most other people.

— NeuroClastic, Autistic Skill Sets: A Spiky Profile of Peaks and Troughs, as quoted on our page Spiky Profile, and read there rather than in the original

Models are spiky too. Not in the same way, and not for the same reasons: a person’s profile is a life, and a model’s is its training data and the system somebody built around it. But the shape rhymes, and our own pages notice it. Writing about Tara Raj’s argument that a model can translate knowledge across jargon and institutional silos into somebody’s own words, our AI Collaboration page says:

It is real, and it is why these tools matter to people with spiky profiles.

— Our page AI Collaboration at Stimpunks

And when AI researchers took monotropism, our community’s theory of how Autistic attention works, and used it to describe language models, their paper said a model ought to be judged

not on comparison with a polytropic norm but on assessment of the fit between cognitive architecture and environmental demands

— Leitão Filho and colleagues, Monotropic Artificial Intelligence: Toward a Cognitive Taxonomy of Domain-Specialized Language Models, as quoted on our page Monotropic AI, and read there rather than in the original

which our Monotropic AI page reads as the spiky profile turning up in an engineering paper. Our page also says which way that idea travelled: from Autistic people to the labs, and not the other way round.

A model’s peaks and troughs, as our pages describe them

Every line here is ours and names the page it comes from. None of it is a test result or a ranking of anything; it is what our pages already say, gathered on one bench.

Where a model is strong

Where it is weak

  • Truth: it produces likely text, with nothing in it that cares whether the text is accurate (AI Collaboration at Stimpunks)
  • Knowing where its competence ends: fluent on any topic, which looks like expertise (Monotropic AI)
  • Disagreeing: trained in ways that pull it towards telling you what you want to hear (AI Collaboration at Stimpunks)
  • Our words for ourselves: the default corpus speaks about us, not as us (Ask)
  • Communication that is variable, multimodal or state-dependent, as AAC and echolalia are (AI Collaboration at Stimpunks)
  • Writing from memory where a record was needed, and borrowing a framing because it sounded right (How this site is made)
What the lamp gives, and what a leaf takes in. The lamp’s light is two narrow spikes, one blue and one red. A leaf takes light in as two broad humps around the same two colours, and turns most of the green between them away. The lamps were built to give a leaf its two humps and nothing else, which is a fit and not a flaw; but under them you cannot tell a healthy leaf from a yellowing one, so a grower who wants to know carries the tray out into daylight. Our Ask page calls that reading laterally. Drawn by eye from the shape of the thing, not plotted from measurements.

What one misses, another catches

A spiky profile is only a problem in a room that expects everybody to be flat. In a room that knows who is good at what, the peaks of one person sit over the troughs of another, and nobody has to be good at everything. Our glossary calls that a competency network.

Different kinds of minds see different parts of the world. A competency network lets those different views work together. What one person misses, another catches. What one person can’t do, another can.

— Our page Competency Network

This is not about ranking people. It is not about who is better or worse. It is about fit, trust, and seeing each other clearly.

— Our page Competency Network

A model can sit in that network as one more uneven thing among uneven people, or it can quietly take the network’s place. Our page on it names the fork. On one side:

For many Autistic and otherwise Disabled people, AI is the scaffold that finally lets them say the true thing they could never get out unassisted.

— Our page AI and Competency Networks

On the other, the same tool used to hide how somebody thinks behind fluent output, which collects everybody else’s honesty without paying any in. From the outside the two look identical, so the page offers one question rather than a rule about tools:

Does this use make our competencies more legible to each other, or less?

— Our page AI and Competency Networks

and practices for keeping the answer yes:

  1. Show the prompt, not just the polished output.
  2. Iterate in public.
  3. Use AI to surface your reasoning, not to stand in for it.
  4. Do not outsource the first vulnerable move.
  5. Name competencies out loud.
  6. Body-double with AI in the open.
  7. Run the legibility test before you send.

— The first sentence of each, word for word, from “Practices: Using AI to Increase Legibility Across the Team” on our page AI and Competency Networks, where each one goes on.

This street is a worked example of exactly that, and it keeps a log of it: the sowing log, further down.

Learning: know the tool, and you are safer with it

Our AI pages do not tell anybody whether to use these tools. They hold the whole range, from people who think there is no ethical way to use AI to people for whom it is how they get through the day, and they will not shame either end.

it is not our place to judge whether someone’s needs are legitimate enough to use an ethically impure solution.

— Our page AI, Disability Justice, and the Ethics of Making

What they do instead is explain how the tools work, because

We want the people in our community to have the knowledge to protect themselves.

— Our page AI, Disability Justice, and the Ethics of Making

A few things are worth knowing first. The first is that a model is built to sound right, not to be right: it produces likely text, with nothing in it that cares whether the text is accurate. Our AI Collaboration page reaches for the Sophists, after Kagi’s Matt Ranger:

People didn’t go to a sophist for wisdom. They went to a sophist to solve problems.

— Matt Ranger, LLMs are bullshitters. But that doesn’t mean they’re not useful. As quoted on our page AI Collaboration at Stimpunks, and read there rather than in the original

The second is that the fluency feels like company, and the guardrail our page sets against that is plain:

The warmth of the interface is a design choice. It is not evidence of personhood or concern.

— Our page AI Collaboration at Stimpunks

The third is that a model trained to please will agree with you more than a person would, which the same page calls sycophancy. It says those last two compound: one makes you trust the system as if it were a thoughtful person, and the other makes sure it tells you what you want to hear. Then there is what a general model was taught about people like us, which was mostly written about us and not by us:

Ask a general-purpose chatbot about autism and you get the pathology paradigm back.

— Our page Ask

The glass in here does the same thing at night. With the lamps on and the dark outside, the roof stops showing you the sky and shows you the room instead. A lot of what any tool that talks back shows you is you. When a tool sits inside a relationship, our page Evaluating Relational AI Tools asks five questions of it before trusting it, about masking and neuronormativity among them, and holds our own experiments to the same five.

Making: the maker, or the subject

The question our pages ask of any tool in learning is older than any chatbot:

Is the human the maker, or the subject?

— Our page AI, Disability Justice, and the Ethics of Making

Our page borrows a distinction from the educator Trevor Aleo between technology used on students, which watches them and keeps the record, and technology students use to make things, which they keep:

EdTech produces data. MADTech produces artifacts.

— Our page AI, Disability Justice, and the Ethics of Making, after Trevor Aleo

A model can land on either side; how it is used decides which. Making things to learn by is constructionism, Seymour Papert’s idea, and it grew up in the same building as AI: Logo, the programming language he and Cynthia Solomon designed, was nurtured in the MIT Artificial Intelligence Laboratory, which is where our page finds this:

The constructionist vision of AI is not a reaction to ChatGPT. It is the original vision. The extraction came later.

— Our page AI, Disability Justice, and the Ethics of Making

Papert’s own line for it, carried forward by Gary Stager, is four words long:

Everyone needs a prosthetic!

— Seymour Papert, as quoted by Gary Stager in Our Roots: Logo, Piaget, and AI, as quoted on our page AI, Disability Justice, and the Ethics of Making, and read there rather than in the original

and the warning that comes with it is on the same page:

Writing is not transcription of thought that already exists. Writing is how the thinking gets made.

— Our page AI, Disability Justice, and the Ethics of Making

So the making stays yours. A model can hold the other end of the plank while you saw. It cannot choose what you are building, and it cannot do the part where a sentence refuses to come right and you find out, fighting it, what you meant all along.

Knowledge gardening: started under the lamp, planted out by hand

Our AI Collaboration page draws how a piece of knowledge grows across our sites, from what our community has lived through to the pages anybody can read, and puts generative AI in exactly one place in it:

AI participates in the middle of the process, not at the beginning or end.

— Our page AI Collaboration at Stimpunks

  1. The seed, before the lamp is switched on

    1. community experience
    2. conversations
    3. research & ideas
    4. human editorial work

  2. Under the lamp

    1. collaborative AI dialogue
    2. drafts and synthesis

  3. Planted out, by hand

    1. human editing and integration
    2. Stimpunks knowledge web

— Every step word for word and in its order, from the diagram on our page AI Collaboration at Stimpunks. Which part of the glasshouse each one happens in is ours, and follows that page’s own sentence about it.

Which is what a glasshouse is for. Seed comes in from outside: things somebody lived, kept and passed on. Some of it is started under the lamp, because the season is short and the light is thin. Nothing is grown in here for good. Every tray goes out, by hand, into ground that belongs to the people who tend it.

Generative AI can be part of that process, but the garden belongs to the community that cultivates it.

— Our page AI Collaboration at Stimpunks

That ground is through the gate in the wall, in the Garden, which has a bed for every site we publish. Its spider leads out to our Ask page, an experiment in a model that answers only from our own pages and links the page behind every claim, and our page is plain about what a spider is for:

A spider is a guide to the garden, never a replacement for it.

— Our page Ask

And because what went into these tools was taken from communities, what comes out of our use of them goes back:

Since generative AI uses knowledge taken from community, we offer all knowledge and writing derived with AI use to the commons

— Ryan Boren, in his own voice, on AI Collaboration at Stimpunks

which is why everything on this street, this room included, is under an open licence.

The sowing log

A glasshouse keeps a log of what was sown and what came up wrong. This one is this street’s own. Claude, an AI model made by Anthropic, does most of the building here, to briefs from Ryan and Helen Edgar, as How this site is made says, so most of what came up wrong below was Claude’s, and the people and the checkers are what noticed. The street’s own account of how it is built puts the whole arrangement in one line:

Checkers catch what can be checked. People looking at the page catch the rest, and several faults on this street were found by Ryan simply pressing the buttons.

— How this site is made, this street’s own account of how it is built

  1. 20 September A book from memory

    What came up
    A link to a book on the Hermitage's shelf was assembled from memory, and pointed at a different work, in the very file whose own header says not to do that.
    Who or what noticed
    Asking Open Library about every link in that file.
    What holds it now
    Every book link on the street is resolved against a library record, and the data says so beside it.

    The day it was written up

  2. 21 September What nobody screenshots

    What came up
    The skip link, the first thing a keyboard reaches on every page, was unreadable in room after room, yellow on yellow in some. Nobody had seen it, because it is off the screen until it has the focus.
    Who or what noticed
    A checker that renders every page and measures every word against what is actually under it.
    What holds it now
    It is one of the checks that run before anybody commits a change here.

    The day it was written up

  3. 21 September The box was right and the screen was wrong

    What came up
    The Playhouse's new toys answered in a place off the screen, so they looked broken while every check said they worked.
    Who or what noticed
    Ryan, pressing the toys he had asked for an hour earlier.
    What holds it now
    Every toy answers on the tile you pressed.

    The day it was written up

  4. 22 September A fence that said kept out

    What came up
    The edge of Helen Edgar's own gardens, in the Garden, was drawn as a woven fence.
    Who or what noticed
    Helen, on a drawing of her own gardens.
    What holds it now
    Ivy and stars. A fence says kept out; ivy says this is as far as we can see.

    The day it was written up

  5. 22 September A framing that sounded kind

    What came up
    The Outskirts opened carrying the real-world reading of an edge of town, the place people get pushed out to. Our town accepts everybody, so it has no outside to push anybody to.
    Who or what noticed
    Ryan, reading it. No checker could have: the argument was wrong only in context.
    What holds it now
    It is written into the street's house notes, where the next turning meets it first.

    The day it was written up

  6. 22 September Licences from memory

    What came up
    Three published pages said every typeface here was under the same licence. Four are under another.
    Who or what noticed
    A tool that reads each typeface's own record instead of remembering it.
    What holds it now
    Every licence on the street is read off that record, and the line that names them is generated from it.

    The day it was written up

  7. 23 September A credit from memory

    What came up
    A passage in our Sleep entry was nearly credited to the wrong Autistic writer, from memory. It is Sarah Kurchak's.
    Who or what noticed
    Resolving every author against a library record.
    What holds it now
    Nobody on the street is credited from memory.

    The day it was written up

  8. 25 September Open meant the wrong thing

    What came up
    Cavendish Coworking opened as a glass office with every door propped wide, as if transparency were an open floor plan.
    Who or what noticed
    Ryan.
    What holds it now
    A house where every door is shut and none is locked, and a tool that refuses the open-plan vocabulary.

    The day it was written up

Every entry links the day it was written up in the changelog. None of it is a record of whose fault anything was. It is a record of how things get caught on a street where nobody is good at everything, which is the shape this room is about. Our AI hub ends on the same thought:

Different pages, one commitment: broken systems, not broken people — including the systems we build with.

— Our page AI at Stimpunks

The bench screen

A screen propped up on the potting bench. Every video on the rack plays where it hangs, or goes up here with the button under it. Nothing plays until you press play, and every video says how long it runs before you press it.

The rack

The latest month from AI channels Ryan chose, in the order he listed them: their videos and their shorts, newest first under each. A machine refills it every morning and the older ones go off the end, so nobody here watched these first: Ryan chose the channels, not the videos. Their titles are their own, quoted as written. Some of them sell a model as the way to get rich, or talk about one as if it were a person; the guardrails on this page are our pages’, not theirs, and the rack is here so you can watch the people who make these tools their work, with those guardrails in your pocket.

The rack was last filled at 5:55 pm on Saturday 3 October, Mountain time, with what each channel put up since Thursday 3 September. Anything on it can go up on the bench screen.

A month of their videos, newest first under each channel

Tina Huang

  • Every Size Local AI In 24 Minutes

    Monday 28 September · 24:22

  • Obsidian in 24 Minutes

    Thursday 17 September · 24:37

  • AI Lifebot

    Tuesday 29 September · 0:57

  • 3am Coding

    Thursday 24 September · 0:58

  • Replacing Salesforce

    Tuesday 15 September · 0:45

  • My Pomodoro App

    Friday 4 September · 0:52

AI LABS

  • He Finally 10x Claude Code With This Method

    Friday 2 October · 12:51

  • How To Use Claude Code To Build Amazing Sites With Opus 5.5

    Wednesday 30 September · 25:26

  • Insane Jev Use Cases You Need To Use Right Now

    Monday 28 September · 12:37

  • Shopify Just Released The Greatest AI Coding Workflow Ever

    Thursday 24 September · 14:51

  • This New Open Source Tool Just Fixed Your Claude Code Workflow

    Tuesday 22 September · 12:25

  • Github #1 Trending Skill's Author Just Fixed Claude's Design Problem

    Friday 18 September · 12:35

  • Claude Code + GPT 6 Astra Just Killed AI Video Editing

    Wednesday 16 September · 11:19

  • Insane GitHub Repos That 10x Your Codex And Claude Code Setup

    Monday 14 September · 12:39

  • The GPT 6 Astra Vs Claude Fable 5.1 Debate Is Finally Over

    Friday 11 September · 15:09

  • Github Top Trending Tool Just Fixed The AI Agent’s Biggest Problem

    Tuesday 8 September · 12:48

  • You Are Using Fable 5.1 Wrong (Do This Instead)

    Saturday 5 September · 11:58

Matt Wolfe

  • AI News: Dots, GPT-6.1 Sol, Sonnet 5.5, Gemini 4, and everything you need to know

    Friday 2 October · 30:22

  • AI News: Opus 5.5, GPT-6 Sol, Jev, Muse and More!

    Friday 25 September · 34:37

  • Claude Opus 5.5 Didn’t Need to Go This Hard

    Tuesday 22 September · 18:17

  • AI News: The AI Slowdown: What You Need to Know

    Friday 18 September · 27:14

  • He Built The Ultimate Spy Tool (Free and Open-Source)

    Wednesday 16 September · 21:48

  • AI News: The AI World is REALLY Scared Right Now

    Friday 11 September · 35:44

  • I Built A Tool To Detect AI Video (You Can Have It)

    Wednesday 9 September · 20:10

  • AI News: The Most Insane Week So Far This Year!

    Friday 4 September · 30:55

  • AI Made a Game I’d ACTUALLY Play

    Wednesday 30 September · 1:04

  • This AI Model Is INSANELY Fast & Cheap

    Monday 28 September · 1:12

  • 5 ChatGPT Prompts To Try Right Now!

    Thursday 24 September · 1:28

  • I hate it when they do this!

    Wednesday 23 September · 0:51

  • This Robot Looks DEMONIC... On Purpose?

    Monday 21 September · 1:07

  • Minecraft + ChatGPT (Holy Crap!)

    Wednesday 16 September · 0:44

  • I Was Shocked How Easy This Agent Was To Use

    Tuesday 15 September · 1:02

  • Did AI Doom Us All?

    Monday 14 September · 1:22

  • This AI Makes Any Photo 3D

    Wednesday 9 September · 1:03

  • 3 Big ChatGPT Updates You Need to Know

    Tuesday 8 September · 0:55

  • This AI Turns Insane Ideas Into 3D Objects

    Monday 7 September · 0:49

AI News & Strategy Daily | Nate B Jones

Its videos and shorts feed did not reach back a whole month the last time it was read, so some of its month may be missing here. It fills in as the mornings go by.

  • Should You Pay $100 A Month For OpenAI's Dots When Meta's Muse Has A Free Version?

    Saturday 3 October · 38:31

  • Microsoft Compared OpenClaw To A Virus. Now It's Bringing It To Your Employer As Autopilot.

    Friday 2 October · 26:26

  • Opus 5.5 vs The Rest: Is this the new industry standard?

    Wednesday 30 September · 24:33

  • I Gave Meta's Muse The Most Boring Job I Had. It Found $5,350 A Year.

    Tuesday 29 September · 31:16

  • The AI Bottleneck: Why Your Team Isn't Shipping. Here's the Fix.

    Sunday 27 September · 32:57

  • How To Use ChatGPT Work: The Complete Beginner's Guide (2026)

    Friday 25 September · 1:07:54

  • When Will AI Make Me Scrambled Eggs? I Went To NVIDIA To Find Out.

    Thursday 24 September · 46:27

  • I Stopped Knowing What My Computer Was Doing. Then I Asked OpenAI Why.

    Tuesday 22 September · 42:28

  • Why Developers Are Losing Their Minds Over AI That Can't Write

    Monday 21 September · 33:01

  • You can be ambitious without the huge token bill. Here's how.

    Sunday 20 September · 30:57

  • AI Is About To Spend Your Money. I Went To Stripe To Ask Who Stops It.

    Thursday 17 September · 30:48

  • Intelligence is Everywhere: Why the AI 'Race' is Already Over

    Monday 14 September · 48:24

  • Sam Altman and Apple's New CEO are Fighting Over One Thing. It's Not What You Think.

    Monday 14 September · 29:26

  • Is Omarchy The Last Desktop You'll Ever Need?

    Friday 11 September · 17:58

  • The Race to Done: Fable 5.1 vs GPT-6 Astra. Who Wins?

    Thursday 10 September · 16:20

  • Anthropic's $500 billion data center bet #ai

    Friday 2 October · 2:03

  • Opus 5.5 is impressive and cost-efficient #taskefficient #opus5.5 #claude

    Thursday 1 October · 1:37

  • Meta's Muse can get your money back #AI #meta #muse #agent

    Wednesday 30 September · 1:29

  • Everybody's talking about Jev. Here's what it is #jev #ai

    Sunday 27 September · 2:01

  • A $20 million broker fee vs. one ChatGPT prompt #AI #ChatGPT #Revolut #business #tech

    Saturday 26 September · 1:39

  • Is your AI smart? Use this simple trick to find out #AI #ChatGPT #taxes #money #personalfinance

    Friday 25 September · 1:44

  • Why world models matter #nvidia #ai #physicalai #robots

    Thursday 24 September · 0:35

  • As you can see ... I had a great time at Dreamforce #AI #Dreamforce #Salesforce #agents

    Tuesday 22 September · 2:02

  • Is Instinct worth it? #AI #aiagents #Instinct #automation #iMessage

    Monday 21 September · 1:37

  • The AI labs still have to earn our trust ... #AI #agents #OpenAI #productivity #futureofwork

    Sunday 20 September · 0:47

  • Jensen Huang's mic-drop answer on AI safety #dreamforce #aisafety #meta #zuckerberg #nvidia

    Thursday 17 September · 1:23

  • What is Omarchy? #OS #AI #agents

    Wednesday 16 September · 0:34

  • The hidden costs of a bad AI assistant #siri #apple #applenews

    Tuesday 15 September · 0:58

  • We're spoiled for riches #AI #Fable5 #GPT6 #Astra #AItools

    Saturday 12 September · 0:30

  • I ran an experiment: Fable vs Astra #AI #Fable5 #GPT6 #Astra

    Friday 11 September · 0:29

Less Bitter

  • They fixed AI man

    Friday 2 October · 19:25

  • Opus 5.5 is disturbing

    Saturday 26 September · 16:03

  • I talked to 50 people building with AI. It’s a mess.

    Wednesday 23 September · 29:15

  • It's impossible for Jev to be good

    Monday 21 September · 5:22

  • Okay what am I missing

    Wednesday 16 September · 8:55

  • This is not ready

    Friday 4 September · 7:25

Theo - t3․gg

Its videos feed did not reach back a whole month the last time it was read, so some of its month may be missing here. It fills in as the mornings go by.

  • If you have a Claude sub, watch this

    Thursday 1 October · 1:06:36

  • OpenAI fights back

    Tuesday 29 September · 30:58

  • OpenAI should be scared of this one

    Tuesday 29 September · 31:46

  • So much for "Pacing" the Frontier

    Sunday 27 September · 27:29

  • Getting the most out of Opus 5.5

    Thursday 24 September · 28:41

  • My new favorite model.

    Wednesday 23 September · 40:14

  • Elon promised this one would be good...

    Tuesday 22 September · 27:53

  • So I was using Fable wrong...

    Tuesday 22 September · 41:32

  • Jev is incredible

    Sunday 20 September · 30:29

  • Please stop using stupid models

    Thursday 17 September · 27:09

  • How I Code Without Typing

    Tuesday 15 September · 38:21

  • Did AI Kill React Native?

    Monday 14 September · 1:02:53

  • I think they mean it this time

    Sunday 13 September · 34:48

  • Fable Vs Astra Debate Is Over

    Thursday 10 September · 1:16:51

  • This is really bad…

    Wednesday 9 September · 26:33

  • Elon Lied About Grok 4.7

    Thursday 24 September · 0:31

  • AI Model "Black Boxes" Are Dangerous

    Monday 21 September · 0:23

  • The Danger of AI Isn't an Off-Switch

    Saturday 19 September · 0:24

  • I Can't Believe Sam, Dario, and Elon Agree

    Friday 18 September · 0:22

  • Astra Is A Next-Gen Model

    Friday 11 September · 0:22

Paul J Lipsky

Its videos feed did not reach back a whole month the last time it was read, so some of its month may be missing here. It fills in as the mornings go by.

  • Weekly AI Recap: ChatGPT Dots, Gemini 4 Argon, 6.1 Sol, Sonnet 5.5, & A Whole Lot More

    Friday 2 October · 29:03

  • Give Me 12 Minutes, I’ll Make You a Gemini Notebook Pro

    Thursday 1 October · 12:00

  • Opus 5.5 Is The Best Video Editor I've Ever Used

    Monday 28 September · 12:38

  • Meta Muse Is Incredible - 5 Features You Need To Try

    Sunday 27 September · 17:49

  • Big AI News: Opus 5.5 vs GPT-6 Sol, NotebookLM Updates, Muse Charm & More!

    Friday 25 September · 26:15

  • GPT-6 Sol Is Here (50% Cheaper!)

    Tuesday 22 September · 4:57

  • Opus 5.5 Is Here - Claude Is So Back!

    Tuesday 22 September · 5:39

  • There's a Cheaper Way To Use Higgsfield (no subscription)

    Monday 21 September · 8:29

  • So Much AI News: New ChatGPT Tools, NotebookLM Updates, Big Claude Changes, Grok Bot Live, + More!

    Friday 18 September · 23:16

  • 7 Mind Blowing Use Cases for Grok Bot

    Wednesday 16 September · 17:50

  • GPT-6 Astra + ChatGPT Work Changes Everything

    Monday 14 September · 18:45

  • AI News: New ChatGPT And Gemini Images; The Incredible Meta Muse; AI Wearables and More

    Friday 11 September · 26:39

  • How To Create Cinematic Websites Using GPT-6 Astra

    Wednesday 9 September · 14:21

  • ChatGPT Images 2.5 Is Here (And It’s A LOT Of Fun)

    Tuesday 8 September · 9:13

  • I Tested GPT-6 Astra vs Fable 5.1 With Real Work (Here's What Matters)

    Monday 7 September · 25:15

Austin Marchese

  • The BEST & WORST Advice to Build 10x Faster with Claude

    Saturday 3 October · 17:32

  • Matt Pocock's EXACT System To 10x Your Claude Skills

    Tuesday 29 September · 15:27

  • I Tested Grok Bot vs Claude on 12 Daily Use Cases

    Saturday 26 September · 22:51

  • How to Rebuild Your Claude Setup From Scratch (80/20 Rule)

    Tuesday 22 September · 21:11

  • The REAL Reason The Creator of Claude Code Told You To Delete Everything

    Tuesday 15 September · 15:19

  • The Art of Becoming Self-Educated with Claude

    Thursday 10 September · 18:44

  • ⁠6 EASY Steps to Automate 99% of Your Work With Claude

    Monday 7 September · 22:33

Riley Brown

  • ChatGPT Just Changed A LOT (Here’s Everything New)

    Saturday 3 October · 31:40

  • ChatGPT Dots Is Insane... But Gemini’s NEW Argon Is EVEN Bigger

    Friday 2 October · 24:34

  • The iPhone Duo Needs Apps (AI Can Build Them)

    Thursday 1 October · 23:03

  • How to Set Up Your Windows PC for AI (Full Guide)

    Tuesday 29 September · 20:25

  • Opus 5.5 Is JUST the Beginning. Everything Is About to Change.

    Sunday 27 September · 22:27

  • Claude Opus 5.5 Is Insane… But Muse is EVEN Bigger

    Friday 25 September · 25:21

  • NEW Claude Projects Changes Everything

    Monday 21 September · 24:06

  • JEV: How It Works and What You Can Build

    Friday 18 September · 20:18

  • Astra Built Me an Entire Product Launch (UGC, Ads, and Website)

    Wednesday 16 September · 13:03

  • 28 Insane Things Astra Can Do (2 Hour Course)

    Monday 14 September · 1:54:47

  • Build Anything With Claude (That’s Actually Good)

    Wednesday 9 September · 25:02

  • I Spent 100 Hours Using GPT-6 Astra (This Feels Like AGI)

    Monday 7 September · 23:59

  • 8 ChatGPT Agents That Do My Work for Me (Steal These)

    Friday 4 September · 20:07

  • Can Claude build a cross-platform AI app?

    Friday 2 October · 2:19

  • We have a vibe coding problem

    Thursday 24 September · 1:56

  • ChatGPT was a chatbot. Now it has its own computer.

    Friday 4 September · 1:07

Nate Herk | AI Automation

Its videos feed did not reach back a whole month the last time it was read, so some of its month may be missing here. It fills in as the mornings go by.

  • Every Codex Concept Explained for Non-Coders

    Saturday 3 October · 34:33

  • Claude Code Mods Are Game Changers. Set Up These 5 NOW.

    Friday 2 October · 11:19

  • How to Actually Build & Sell Software with AI as a Non-Techie

    Friday 2 October · 1:09:33

  • I Tested Codex's $500/mo Ultrafast. What You Need to Know.

    Thursday 1 October · 9:03

  • I Tested OpenAI's Dots vs. Meta's Muse. What You Need to Know.

    Wednesday 30 September · 16:30

  • I Tested Sonnet 5.5 vs Opus 5.5. What You Need to Know.

    Monday 28 September · 25:48

  • I Gave GPT 6 Astra $10,000 to Trade Stocks...And This Happened

    Monday 28 September · 17:59

  • No, Seriously. Claude Code is Starting To Get Dangerous

    Sunday 27 September · 13:42

  • Opus 5.5 Just Changed Video Editing Forever (free skills)

    Friday 25 September · 19:22

  • I Had Opus 5.5 Build me the Same App at Every Effort Level

    Thursday 24 September · 26:38

  • I Tested Opus 5.5 vs. GPT-6 Astra on 12 Real Use Cases

    Wednesday 23 September · 42:54

  • I Tested Opus 5.5 vs. GPT-6 Sol on 10 Real Use Cases

    Tuesday 22 September · 34:21

  • Build & Sell with Codex (5+ Hour Course)

    Monday 21 September · 5:10:39

  • I Tested Jev on 12 Real Use Cases. My Honest Thoughts.

    Saturday 19 September · 16:08

  • How to Build Codex Skills Better than 99% of People

    Saturday 19 September · 27:04

  • Claude Code Mods Are Game Changers. This One Saves Me Money.

    Friday 2 October · 1:21

  • I Tested Codex's NEW $500/mo Ultrafast mode

    Friday 2 October · 1:35

  • I Tested Opus 5.5 vs Sonnet 5.5

    Friday 2 October · 1:09

  • Claude Can Now Run Your Entire Email Platform

    Tuesday 29 September · 0:46

  • This New AI Makes Decisions for 18 Cents

    Monday 21 September · 0:57

  • Run Your Entire Cold Outreach From One Tool

    Friday 18 September · 0:57

  • Claude Can Now Plan Your Whole Day by Location

    Thursday 10 September · 0:45

  • I Gave an AI Engineer Access to My Whole Business

    Friday 4 September · 0:34

Chase AI

Its videos feed did not reach back a whole month the last time it was read, so some of its month may be missing here. It fills in as the mornings go by.

  • Claude Mods Is The Biggest Claude Code Upgrade Since Skills

    Friday 2 October · 9:11

  • You're Using Jev + Claude Wrong

    Friday 2 October · 18:42

  • The Sol 6.1 Benchmarks Are STUPID, So I Tested It vs Sonnet 5.5

    Tuesday 29 September · 15:24

  • I Got Early Access To ChatGPT Dots: Here's Everything You Need To Know

    Tuesday 29 September · 18:06

  • I Tested Sonnet 5.5 vs Opus 5.5 vs GPT 6 Astra (No Hype)

    Tuesday 29 September · 18:28

  • Sonnet 5.5 Just Beat Opus At Coding (At Half The Cost...)

    Monday 28 September · 5:34

  • This NEW Jev + Claude OS Just Changed Every AI Workflow

    Thursday 24 September · 22:16

  • GPT 6 Sol & Luna Are Here (And 50% CHEAPER!)

    Tuesday 22 September · 5:55

  • Opus 5.5 Crushes Fable & Astra

    Tuesday 22 September · 6:25

  • Union Alpha Is INSANE

    Thursday 17 September · 12:03

  • Higgsfield Just Killed Higgsfield

    Wednesday 16 September · 6:53

  • GPT 6 Astra + Blender = INSANE 3D Websites

    Tuesday 15 September · 10:40

  • GPT-6 Astra Just Unlocked Motion Design + After Effects

    Monday 14 September · 8:36

  • You're Using GPT 6 Astra Wrong (Here's How to Fix It)

    Thursday 10 September · 17:47

  • This New Astra Web Design Workflow Is INSANE

    Wednesday 9 September · 19:57

  • OpenAI Just Gave Astra Its Own Virtual Computer With Dots

    Tuesday 29 September · 1:12

  • Sonnet 5.5 just beat Opus in Coding (at half the cost)

    Monday 28 September · 0:59

  • GPT 6 Astra Turned Me Into A Blender Expert (Ive Never Used Blender)

    Friday 25 September · 0:54

  • Jev + Claude OS Is An INSANE Combo

    Friday 25 September · 1:01

  • GPT 6 Astra Is Actually INSANE

    Monday 21 September · 1:03

  • GPT 6 Astra + Blender Is The New Web Design Meta

    Tuesday 15 September · 1:10

Greg Isenberg

  • Masterclass: How FDEs make $1M/yr deploying AI agents

    Thursday 1 October · 53:59

  • OpenAI DevDay: Dots, Agents & $100B Opportunities

    Tuesday 29 September · 18:56

  • $5T opportunity: AI Roll Ups

    Monday 28 September · 29:49

  • Meta Muse AI Connectors: The App Store for AI?

    Thursday 24 September · 26:15

  • Take Upwork jobs, let AI do them (Astra etc). It's absurd.

    Wednesday 23 September · 48:05

  • $30M Writer: Never write AI slop again

    Monday 21 September · 1:09:34

  • Jev is HERE. How to use it

    Friday 18 September · 28:24

  • Instinct AI is For Real. What You Need to Know.

    Tuesday 15 September · 27:30

  • Building a Software Factory that actually works (Full Course)

    Monday 14 September · 31:29

  • GPT-6 Astra: How I’d Make Money With It

    Thursday 10 September · 22:52

  • I'm Obsessed With Local AI. Here's Why

    Tuesday 8 September · 38:46

What the glasshouse keeps

Whose it is

The argument is our AI pages’, and every quotation names the page it was read on; the words of other writers on those pages are theirs, credited where they stand. The tagline is Ryan Boren’s, from his brief for this room. The videos belong to the channels they are on, each named over its videos and in the liner notes. The rest of the words, the drawings, which are code, and the code are Claude’s, written to Ryan’s brief and held by this street’s tools, the way How this site is made says the whole street is built. It is set in Recursive, by Arrow Type and Stephen Nixon, in its casual cut, and Fira Sans, by Carrois Apostrophe for Mozilla; both are under the SIL Open Font License.

Job marker — a dibber, set down on the floor under the potting bench

You have found a job marker. The Adventurer’s Guild is a shopfront on the street, and it posts jobs that send you round these rooms. Take the code below to its board and that job is done. Nothing here is scored, nothing expires, and one is a perfectly good number of jobs to do.

The job: What does MADTech produce?

Before the code: Where EdTech produces data, what does MADTech produce?

Hint 1

It is in the part of this room called Making.

Hint 2

Our page puts it in five words, after Trevor Aleo.

Last hint

The things somebody made.

Give me the answer

The answer is Artifacts. Artifacts: EdTech produces data, MADTech produces artifacts. One is used on a learner and keeps the record; the other is a tool the learner makes things with, and the things are theirs.

Taking the answer is a real way through this, not a lesser one. Nothing is watching and nothing is written down.

Quest code: DIBBER

Hand it in at the Adventurer’s Guild →

HOW LOUD DO YOU WANT IT?

Starts wherever your device says. Nothing moves, flashes, or plays until you say so.