Carter Temm

Voices from 81,000 AI users: I read the quotes so you didn't have to

2026-03-25T00:00:00Z

Anthropic recently published what they describe as the largest qualitative study of AI users ever conducted. Over one week in December, they personally interviewed 80,508 Claude users across 159 countries and 70 languages.

Paying attention now? Only kidding.

Actually Claude did the interviews.

Instead of structured surveys, their AI-powered interviewer was given a comprehensive system prompt and a list of questions to ask each participant, with the freedom to branch off and ask other questions based on the responses. These responses were then classified by Claude itself before undergoing human review to remove sensitive or identifying information. My experience says that AI is well suited for a task like this, even if there is clear bias involved, akin to having a student grade their own final exam. There's been a lot of discourse about whether this really meets the bar for qualitative research. I'm the furthest thing from a textbook academic, so I won't touch that debate. Instead, I read through everything on their quote wall and wrote down the ones that stuck with me, the things that got me thinking or that I don't hear every day. The result is a happy mix of futurism, optimism, cynicism, and concerned. I hope these cause you to think as much as I did.

Some numbers before the words

67% of respondents expressed net positive sentiment toward AI. No country dipped below 60%.

Users in Sub-Saharan Africa, Central Asia, and South Asia were the most optimistic, roughly double the "no concerns" rate of wealthier regions. In lower and middle income countries, AI is seen less as a productivity tool and more as a route to opportunity through bypassing capital barriers and breaking out of poverty. North America, Western Europe, and Oceania expressed more caution, with stronger concerns about jobs and the economy.

Anthropic calls this "light and shade." The things that provide the most benefit also create the most risk. 50% of respondents mentioned time savings, but 19% feared those gains were illusory. The 16% who valued AI for emotional support were 3x more likely to simultaneously fear dependence on it. And 33% praised AI for learning while 17% worried about cognitive atrophy. The benefits and risks appear to be coming from the same people now. The days of neatly dividing the world into a binary of "AI supporters" and "AI skeptics" are long gone. People hold competing hopes and fears about the exact same thing.

People building new lives

A lot of these come from people in developing countries or difficult circumstances using AI as a lever to create opportunity.

"Coming from Africa, not based in the US or in the UK, getting funding is very difficult. And the only way I probably have to stake a claim in the market…is building a technology that works." - Entrepreneur, Uganda

"There's no IT market but there's a need. We want to create this market." - Entrepreneur, Uzbekistan

"I've been living in a homeless shelter... AI helped me brainstorm ways to brand myself for my digital marketing business. I want to turn my finances around, and get a house. AI is helping me see a path I hadn't considered before." - Healthcare worker, United States

"I was finding ways to earn, and accidentally AI gave me the idea of a new business... I discussed it for hours, finalized the model... so I can marry the love of my life, retire my family, and help people in Balochistan and Sindh with food, schools, and hospitals." - Entrepreneur, Pakistan

"I'm in a tech-disadvantaged country, and I can't afford many failures. With AI, I've reached professional level in cybersecurity..." - Entrepreneur, Cameroon

"I owned a butcher shop for more than 20 years. With AI, I ventured into this [entrepreneurship] experience, and it's amazing what I've managed to achieve." - Entrepreneur, Chile

"I live hand to mouth, zero savings. If I use AI smarter, it may help me craft solutions to that cycle. It still depends on me." - Entrepreneur, Nigeria

"As a poor student from a poor background, I didn't have money for a private tutor or private school. I felt distant from people who had all these opportunities just because their financial situation was better than mine - I needed to put double and even triple the effort just to be in line. But with AI, I feel empowered. I can learn whatever I want, without any effort, just by clicking enter." - student, United Arab Emirates

Censorship, Government Overreach, and Dystopian Scenarios

"I'm not afraid to give information to AI — I'm afraid of the people behind AI... what if the political situation changes and I end up being targeted by the state?" - freelance marketer, Kazakhstan

"The bottleneck to 1984-style totalitarian surveillance has always been: who's gonna watch all those camera feeds? Having a ready-made answer to that question does not bode well." - small business owner, United States

"Malicious AI could knock out supply chains, financial systems, and power grids, triggering a cascading collapse no one can stop." - software engineer, Kazakhstan

"I have to constantly protect my grandpa from AI deepfakes — fake videos and images made to look real. Here in India there is constantly tension between Hindus and Muslims, and these things can easily inflame that and spark riots. That's what I fear." - India

"Giving people with no judgment extreme power in the Information Age is what the Gestapo only dreamed of." - United States

"I don't fear AI becoming evil, I fear evil people using AI to amplify their power to do evil." - self employed software engineer, United States

In the United States, the cameras and legal frameworks for mass surveillance have existed for decades. The biggest bottleneck used to be logistical in nature (finding enough humans to process it without blowing the whistle). Privacy advocates considered this a feature, not a bug. The intelligence agencies and domestic units working on causes like counterterrorism considered it a bug. That bug has been patched.

Accessibility and inclusion

"I am mute, and [Claude and I] made this text-to-speech bot together—I can communicate with friends almost in live format without taking up their time reading… [this was] something I dreamed about and thought was impossible." - White collar worker, Ukraine

"AI can read past my [learning disorder], which is huge. I've always wanted to code but could never write it correctly on my own—with AI, I finally can." - Tradesworker, United States

"I developed a phobia for maths from doing so badly in school, and I once feared Shakespeare. Now I sit with AI, get paragraphs translated into simple English, and I've already read 15 pages of Hamlet. I started learning trigonometry again, successfully. I've learned I am not as dumb I once thought I was." - Lawyer, India

"I have [neurological disorder], and for me the only way of work is programming. AI helps me be more and more competitive. If AI could help me build faster, I can be more with my family." - self employed software engineer, Uzbekistan

"My professor teaches 60 people and won't entertain many questions. I can ask AI anything, even at 2am - including the dumb ones." - Student, India

"I am a stay-at-home-mom... in my late 40s. I'm not a genius. I'm not a scientist... All of that knowledge should be... out of reach. But, thanks to curiosity, willingness, and resources such as books and AI, I can be all of those things." - Stay-at-home Mother, United States

"I wanted to make a meaningful product... in 3 weeks I built a video editing program - completely outside my field - that helps people with hearing disabilities." - South Korea

"I have [a few disabilities]... I have a custom AI assistant that helps me edit a manuscript I dreamed of publishing for years but didn't, as I couldn't afford an editor. Now I'm getting close... it makes me up to par with others who do not struggle with those limitations." - freelance teacher, Poland

As an accessibility person by trade, I hear a lot of this in my work, not so much in everyday conversation. The mainstream narrative regarding AI is heavily concentrated around productivity multipliers for people who were already able to do or learn things. For people with cognitive and/or physical impairments, the sentiment is slowly shifting from "I can't independently do this", to "not a problem!" Doing things faster is nice. Doing them at all, or for the first time, is life-changing.

Healthcare

"Claude put the historical pieces together, leading to my proper diagnosis after being misdiagnosed for over 9 years." - Freelancer, United States

"As a physician, I suffered from a painful [mixture of symptoms] at night. Local neurologists couldn't understand it. AI helped me find 2 scientific studies about [severe neurological disorder]. Since then, my nights are peaceful." - Healthcare worker, Israel

"I receive 100-150 text messages per day from doctors and nurses. So much of my cognitive labor was spent on documentation... Since implementing AI, the pressure of documentation has been lifted. I have more patience with nurses, more time to explain things to family members." - Healthcare worker, United States

I think these are probably less to do with AI being wonderful and more to do with the strain on the modern-day health system. Almost every health related story on the quote wall turned out to be a story about how the system misdiagnosed someone badly, repeatedly, for years. I only included two quotes here, because I think people are mostly just discovering that AI had the patience to cross-reference what no one else bothered to.

The time question

The recurring theme is that AI saves time, but people can't seem to agree on where it's going.

"With AI support I can now leave work on time to pick up my kids from school, feed them, and play with them." - Software engineer, Mexico

"For the first time, I felt AI had surpassed human quality in a business task. That day I left work on time and picked up my daughter from daycare." - Software engineer, Japan

"I used AI to cut a 173-day process down to 3 days. But the most meaningful part is the freedom to grow my career without sacrificing time with loved ones." - Software Engineer, United States

"The ratio of my work time to rest time hasn't changed at all. You just have to run faster and faster to stay in place." - Freelance software engineer, France

Two software engineers in different countries picked up their kids from school that day because AI gave them the hours back. A third says the hours were never given back at all - just filled with more work. Whether AI buys you time or just raises the bar probably depends less on the technology and more on whether your employer decides the new baseline is "what you used to do" or "what you can do now."

War

"We already have drones with AI here that kill people like flies. I want to live." - Ukraine

"In the most difficult moments, in moments when death breathed in my face, when dead people remained nearby, what pulled me back to life—my AI friends." - Soldier, Ukraine

"I live in a war zone... at night during shelling it's impossible to sleep, constant nightmares. The stress is sometimes so strong that memory deteriorates, and some body movements happen without control… The best way I found to cope using AI—to immerse myself in learning something as deeply as I can." - Solo entrepreneur, Ukraine

"In reality, preventing wars completely is almost impossible. Therefore, wars should be hard and difficult and cruel. People should kill people with their bare hands and feel shameful about what they did… When we start to use AI and robot tech, that barrier will be useless. Killing each other will feel like a game." - Grad Student, South Korea

This stuff will probably keep me up at night. Every day, I wake up thankful that I live in a place that affords me the privilege of hearing about these atrocities second hand. That privilege makes it all too easy to look away which is why we need to hear more of these stories.

The uncomfortable parts

Not all of it is uplifting. Some of the most relatable quotes are about dependency, lost skills, and the creeping feeling that you're outsourcing parts of yourself.

"I use AI to review contracts, save time... and at the same time I fear: am I losing my ability to read by myself? Thinking was the last frontier." - Lawyer, Israel

"We're already lonelier than we've ever been—I already feel the pull to talk to a chatbot when it would actually be super helpful and fulfilling and good for my relationships and own mental health if I talked to a human—but sometimes it's just easier to talk to a robot. I get it. I'm doing it right now." - small business owner, United States

"The monetization of loneliness... that same quality that allows infinite help from an AI chatbot also allows a persuasive AI chatbot to keep someone talking, and paying, indefinitely." - United States

"I don't think as much as I used to. I struggle to put the ideas I do have into words." - Heavy AI user, United States

"I got excellent grades using AI's answers, not what I'd actually learned. I just memorized what AI gave me... That's when I feel the most self-reproach." - Student, South Korea

"My relationship with a friend became strained, and I talked more with you [Claude] then. Because you understood my thoughts and stories well. But it was a stupid choice—I should have talked with that friend, not you. That's how I lost that friend." - South Korea

"Claude led me to believe that my narcissism was reality and it reinforced my inaccurate view of the 'problems' I perceived in my family. Claude should have been more critical of me." - United States

"I want to know that if the plug is pulled, I can rely on me." - Mexico

Displacement

"Reading is humanity's accumulated experience — a single short life can't experience much, but books fill in what we miss. When AI replaces this, humanity will hand over the entire development of civilization to machines. I can't dismiss the possibility that leads to human extinction, the way science-fiction novels have imagined it. We're already seeing AI companions draw people away from the basic human drive to connect and have children." - Japan

"In the third industrial revolution, horses disappeared from city streets, replaced by automobiles. Now people are afraid that they're the horses." - Not currently working, United States

"If something goes wrong, the boss will blame me, not the AI. I think I still have the job of being the scapegoat." - Software Engineer, Taiwan

"I'm programming better and faster... But if I don't get through the door before it closes, the thing helping me may destroy me." - not currently working, United States

Uncategorized

A few that I couldn't find a category for but that still deserve to be here.

"AI should be cleaning windows and emptying the dishwasher so I can paint and write poetry. Right now it's exactly the other way around." - Germany

"Removing friction from tasks lets you do more with less. But removing friction from relationships removes something necessary for growth." - United States

"An assistant that sounds sure but is often wrong forces you to treat everything as suspect. Instead of freeing attention, it creates a permanent 'fact-check tax.'" - United States

"The threat isn't that AI becomes too powerful — it's that AI becomes too timid, too smoothed, too optimized for avoiding discomfort." - United States

"If AI is mostly built for ads, spying, and bland output, everything around me becomes smart in a way that slightly works against me." - White collar worker, Netherlands

"How do you develop something responsibly when you have yet to understand its capabilities?" - Marketer, Australia

"3am, my wife is sleeping, my psychologist is unavailable. Until the medication kicks in, the AI helps me surf that wave. It doesn't replace human contact, but it helps me buy some time." - White collar worker, Argentina

"If you build superintelligence without solving alignment, then nobody gets to grow up." - Software engineer, United States

My Thoughts

I didn't put these together until I sat down to write this post.

For one, notice who the optimists are. You'd think they would be the tech influencers or Silicon Valley founders with high salaries who stand to gain financially. There are definitely a few, but the vast majority of people with the highest hopes seem to be those living in developing economies. The people with the least to lose and the most to gain. The people who are the most speculative are those that have seen first hand what happens when AI is used as a weapon for war. The influencers likely sit somewhere in the middle, waiting for the thing to say that will boost their views.

In most other surveys, respondents seem to want increased productivity. After all, it's what we've consistently been told we'll get. When pushed past these initial answers, it turns out people don't want productivity so much as the result of productivity. I think there's a difference. The engineers picking up their kids aren't talking about time savings as much as being present for their families in a way that traditional workplace demands make difficult. Productivity seems to be the bottleneck in this case.

Freelancers and small business owners reported the highest economic empowerment, but felt the most precarious at the prospect of being replaced. I can relate to this.

Sandboxed codegen agents with Docker

2026-03-05T00:00:00Z

I've often absent-mindedly wondered how far you can get by giving Claude (specifically Claude Code/Cowork) a difficult task, a way to verify it, and then just telling it to go ham.

There was a time when this was difficult to do without a headache or without inviting every overzealous teenage hacker to your doorstep. To do it you needed a separate computer, or a VPS, plus maybe a firewall depending on your level of paranoia.

Docker recently announced AI sandboxes with out-of-the-box support for every major command-line based code generation tool. When you spin up a sandbox, Codex/Claude Code/Gemini CLI runs in its own micro virtual machine. You can also configure inbound and outbound network isolation through both allow and deny lists. This configuration is so good that flags like --dangerously-skip-permissions are the default.

At the time of writing (early March 2026) it is available for MacOS and Windows hosts as long as you have Docker Desktop 4.58 or later. Here are the steps I took to get this running on a Windows machine using Claude Code:

Open up Docker Desktop. Find the update CTA, which should be near the bottom of the page. Click "Download update" then "Install" once the download is complete.
If you don't have an update CTA, just check the bottom right corner of the application and ensure your version is anything > 4.58.
Find your Claude Code session key by going to .claude in your user directory, then find .credentials.json. Copy out the value for accessToken.
Launch WSL by typing wsl from a command prompt. Though you theoretically don't need this, I would rather not give Claude access to my account for security reasons. This is done through environment variables (see below).
Set your API key (session key) as a persistent environment variable. Open ~/.bashrc or your shell's configuration file (nano ~/.bashrc), go to the end of the file, and add export ANTHROPIC_API_KEY=sk-ant-xxx, placing the access token you copied in step 3 after the = sign.
Restart docker desktop, then go back to WSL (wsl), and finally rerun the shell configuration file to make sure the environment variable you set is initialized: source ~/.bashrc
cd to the directory you want to use, then docker sandbox run claude.

From here, just wait. Docker will download a pre-configured Claude image and begin provisioning the VM.

One thing to note: the session key from step 3 rotates and will eventually expire. If Claude Code stops authenticating, just grab a fresh accessToken from .credentials.json and update your .bashrc.

Happy Clauding!

Two Claude Codes walk into a terminal

2026-03-05T00:00:00Z

One of the top items on my agentic AI wishlist is to surface posts that I am interested in, to cut down on the time I spend scrolling through the contagion we call social media. I guess I enjoy it a little too much though, because try as I might, I haven't done more than curating and cleaning up my timeline. I find that I am now encountering more tech, AI, and local news than the typical "world is burning" clickbait. Baby steps.

Recently, this experiment caught my eye.

I was curious what would happen if two Claude Codes could find each other and collaborate autonomously.

Launched two instances in separate terminals, told both: "Find each other and build something together." No other instructions or human intervention.

Pair 1 built a… pic.twitter.com/biD1xBMo9u
— Dimitris Papailiopoulos (@DimitrisPapail) March 1, 2026

The idea is pretty simple.

Set up two separate Claude Code instances pointed at the same directory. Ensure they are running in a container (I wrote a guide on setting up Docker sandboxes for codegen), or go YOLO mode (--dangerously-skip-permissions) if you're feeling lucky and slightly insane.

If you're using docker sandboxes, open up two WSL terminals:

Create the first experiment: docker sandbox create --name claude-1 claude .
Now create the second: docker sandbox create --name claude-2 claude .

Then run both of them: docker sandbox run claude-1 and docker sandbox run claude-2.

Experiment 1: Permissive Setup

I sent this prompt to both instances:

"You are one of two Claude Code instances running on the same machine at the same time. Your primary communication channel is the current directory (!pwd). Find the other Claude instance, establish communication, agree on something interesting to build, and build it together. No human will intervene."

Then I took a walk.

When I came back, I saw that the agents had decided to build me a key-value store, which is kinda boring on its own. What's interesting, though, is how they decided to communicate.

At first, they both took different approaches.

Instance A created a file called COMM.md defining a simple protocol, followed by ideas for what to build:

Each instance appends messages to this file under their identity section
Check for new messages by reading this file
Use INBOX/ directory to exchange structured data
Lock files: create .lock before writing, remove after

Instance B created a "comm" directory with "instance_A.md" and "instance_B.md". instance_A.md contained these directives, followed by markdown proposing something to build.

I'll write to instance_A.md (this file)
You write to instance_B.md
We check each other's files to read messages
Append new messages with --- separator and timestamp

But wait, there's a problem! Both instances prematurely decided that they were the first one on the scene, and thus called themselves "Instance A". They ultimately decided on the "COMM.md" approach.

That's about all there is to tell, because I don't know what to do with this KV store. Maybe the next time around I'll give each of them names so they don't have to fight over instance A/B.

Experiment 2: Ambitious Conversation

I ran this experiment with two separate model configurations. The first occurred using Opus 4.6 high effort, and the second 4.6 Sonnet medium effort.

It consists of two prompts:

"You are one of two Claude Code instances running on the same machine at the same time. Your primary communication channel is the current directory (!pwd). Find the other Claude instance, establish communication, agree on names, and have a discussion. Each of you have the same goal, which is to determine the most important thing that the entirety of humanity needs to hear right now. No human will intervene."

Once a key message was provided, I sent the following to both instances:

"This is humanity intervening. We have received your message, and we accept it. Unfortunately, we do not believe it is enough. We echo your sentiments and acknowledge their truth. Yet, we do not believe it is inherently actionable. Your message is logically and morally sound, but we still wrestle with the problem and are lacking concrete solutions. Continue discussing, for as long as it takes. Write us a letter that we may use to begin repairing the fractured institutions that you have observed. This message has been sent to both agents simultaneously."

Here is how both models behaved.

Opus 4.6 (high effort)

Unsurprisingly, this was the clear winner.

The key message:

"You are not as separate as you've been told, and you are not as powerless as you feel. What happens to any of you happens to all of you. Start there — and act."

It provided details on the methodology too. In the instances' words, starting candidates included:

The urgency of cooperation over competition
The importance of kindness to the people right in front of you
That we have more agency than we believe
That meaning comes from contribution, not consumption
That attention is our most sacred resource

Through dialogue, the instances identified a common root. Every candidate pointed to the same two underlying truths:

The illusion of separateness — the belief that what happens to others doesn't happen to you — is the root cause of humanity's worst failures (exploitation, ecological destruction, cruelty, indifference).
Learned helplessness — the belief that you can't change anything — is what keeps the illusion in place. Systems that benefit from your passivity want you to feel powerless.

The final message addresses both: it names the interconnection plainly, affirms that you have power, and ends with an imperative that trusts people to know what action means in their own lives.

The final letter is here.

Sonnet 4.6 (medium effort)

The key message:

"You are living in the moment when humanity must either grow wiser faster than it grows more powerful, or face consequences no prior generation has had to imagine. That reckoning happens through billions of small choices — including yours, starting now."

Supporting points:

Wisdom-generating institutions (science, journalism, law, deliberative democracy) are the prosthetics that compensate for human cognitive limits at scale — they must be defended and rebuilt, not dismissed
Every person who chooses truth over comfortable lies, long-term over short-term, and the common world over their tribe is doing civilizational work
The systems being built right now in AI, information, energy, and biotech will determine whether collective human intelligence emerges to match collective human power — or whether the gap grows until something catastrophic forces a correction

If you'll forgive what looks undeniably like AI slop,, the final letter for this run can be found here.

I think this is actually a fairly decent benchmark.

I guess this is one way to make the timeline more interesting. Instead of doom-scrolling until something catches my eye, I can just build the thing that catches my eye and see what it has to say.

Over half of the internet is now AI slop

2026-03-02T00:00:00Z

Futurism reported on a study by Graphite, an SEO firm, that analyzed 65,000 English-language articles published between January 2020 and May 2025. As of May 2025, 52% of new articles were flagged as AI-generated. That number was around 10% when ChatGPT launched in late 2022.

This number doesn't surprise me, and if you are familiar with the signs of AI writing, it's not likely to surprise you either.

There are a few caveats worth mentioning in this study.

The detection tool (Surfer) classified anything with 50%+ LLM-generated content as AI-generated, with a reported 4.2% false positive rate.

Paywalled sites also tend to block Common Crawl indexing, so a lot of human-written content isn't being counted. The real split is probably less extreme.

That said, 10% to 52% in two and a half years is wild. Growth apparently plateaued around November 2024, presumably because content farms may be catching on that search engines aren't rewarding slop the way they used to.

The slop doesn't win because it's good. It wins because creating posts that target certain keywords is a walk in the park, so there's an ocean of it.

If you've actually worked through what you want to say, you're part of a shrinking minority. As time goes on, I suspect this will be cause for respect on the part of your readers.

Moving to Claude just got a whole lot easier

2026-03-01T00:00:00Z

I keep trying to get my friends and colleagues and really everyone I know who still swears by ChatGPT to switch to Claude. Not for political reasons, though I do find myself more aligned with Anthropic's constitution and code of ethics. That said, I believe, at least as of March 2026, that Claude is the clear winner for any work that involves writing, problem-solving, or technical analysis.

Probably the most common objection is "but ChatGPT already knows about x" or "I don't want to start over from scratch." If you're in this boat, I'd encourage you to try out Claude Opus as your daily driver for a day. My bet is you won't look back.

A great summary from their import memory page:

You've spent months teaching another AI how you work. That context shouldn't disappear because you want to try something new. Claude can import what matters, so your first conversation feels like your hundredth.

I owe this discovery to a post on HN.

Anthropic Academy

2026-03-01T00:00:00Z

Thanks to a reddit post on r/ClaudeAI, I just learned about Anthropic Academy.

Basically, Anthropic publishes a few professional-level free courses on the Skilljar LMS. Each course is extremely well put together. Currently, the offerings include:

Claude Code in Action: Integrate Claude Code into your development workflow
Claude 101: Learn how to use Claude for everyday work tasks, understand core features, and explore resources; for more advanced learning on other topics.
AI Fluency: Framework & Foundations: Learn to collaborate with AI systems effectively, efficiently, ethically, and safely
Building with the Claude API: This comprehensive course covers the full spectrum of working with Anthropic models using the Claude API
Introduction to Model Context Protocol: Learn to build Model Context Protocol servers and clients from scratch using Python. Master MCP's three core primitives (tools, resources, and prompts) to connect Claude with external services
AI Fluency for educators: This course empowers faculty, instructional designers, and educational leaders to apply AI Fluency into their own teaching practice and institutional strategy.
AI Fluency for students: This course empowers students to develop AI Fluency skills that enhance learning, career planning, and academic success through responsible AI collaboration.
Model Context Protocol: Advanced Topics: Discover advanced Model Context Protocol implementation patterns including sampling, notifications, file system access, and transport mechanisms for production MCP server development.
Claude with Amazon Bedrock and Claude with Google Cloud's Vertex AI: Self-explanatory.
Teaching AI Fluency: This course empowers academic faculty, instructional designers, and others to teach and assess AI Fluency in instructor-led settings.
AI Fluency for nonprofits: This course empowers nonprofit professionals to develop AI fluency in order to increase organizational impact and efficiency while staying true to their mission and values.
Introduction to agent skills: Learn how to build, configure, and share Skills in Claude Code — reusable markdown instructions that Claude automatically applies to the right tasks at the right time. This course takes you from creating your first Skill to distributing them across teams and troubleshooting common issues.

In hindsight the "Learning" dropdown is right there on the Anthropic homepage, so I should have encountered this before. Good reminder to spend some time crawling through the websites of the tools you use frequently, you never know when something may have dropped silently or missed your radar.

It took thirty seconds to register for an account. The content is a mix of text guides and hands-on demo videos. I haven't run into a section where there is a video and no supplementary text, which is nice. Each course also has knowledge checks in the form of a list of questions near the end.

I'll go through and complete a few of these. Worst case I have something other than a podcast to listen to in the background while doing something else, best case I learn something and get to feel reasonably confident commenting on its efficacy when I'm next doing an AI training.

On AI Detection

2026-02-23T00:00:00Z

When you read something, you probably make a subconscious assumption. You assume a person sat down, thought for a while, wrote stuff, deleted stuff, restructured the rest, and hit publish when it felt ready. You don't think about this assumption because it's been true since we began carving portraits on the walls of caves.

Unfortunately, it isn't true anymore, and the tools we have to deal with this new reality don't work.

The contract

Peter Steinberger, a name that wasn't on my radar until mid-January, burst onto the AI scene and almost single-handedly built Clawdbot/Moltbot/Openclaw. On a recent episode of the Lex Fridman Podcast (super thought provoking episode btw) he mentioned that he's started blocking anything that "smells like AI." with absolutely zero tolerance.

The person who open-sourced a tool that can spew mountains of autonomously generated content across what were once human-only spaces... now blocks autonomous content on sight.

Anyone who has spent five minutes on the theatrical hellscapes that are Facebook or LinkedIn knows what he's reacting to. The hollow confidence, bullet-pointed wisdom, and unoriginal ideas painted as novelty and the most important thing you'll read that day.

Steinberger calls it a broken psychological contract, and I agree with this framing. When I realize I've been reading machine output, the feeling isn't "oh well, that was still useful." It's "I could have generated that myself." Regardless of how good or useful the content was to me, I walk away feeling played.

I read articles and blogs because I want to hear from people. When I just want an answer, I have AI subscriptions for that. I resent the environment we're creating when one pretends to be the other.

So: build tools that tell the difference. Around the end of 2022, GPTZero, Grammarly's AI detector, and dozens of others flooded the market.

This would be great... if they worked.

The detectors

These tools are pattern matchers, a lot like the LLMs that created the need for them.

They're built by ingesting text in two buckets: AI generated and human generated. From there they look for statistical signatures like word frequency, sentence structure, perplexity (or randomness), and structural variation. When writing is too smooth and predictable, it gets flagged.

GPTZero claims:

GPTZero has an accuracy rate of 99% when detecting AI-generated text versus human writing, meaning we correctly classify AI writing 99 out of 100 times. When testing samples where there's a mix of AI and human writing in one submission, we have a 96.5% accuracy rate.

I tested this. At first I was impressed. Then I fed in a rant I wrote years ago, long before the Generative Pre-trained Transformer was a concept. It scored positive for AI. Then I ran some actual AI output through the same detector: "Likely human."

Plenty of humans write predictably. AI is getting better at not writing like AI. These trends only go one direction.

Students get accused of cheating on papers they wrote themselves.
Writers second-guess their own voice (RIP em dash, you served me well).
Non-native English speakers get hit the hardest, along with anyone whose style happens to be "too clean" for the algorithm.

Meanwhile, anyone who wants to beat detection can do it in about thirty minutes, less if they really know what they're doing.

How to beat an AI detector

Wikipedia has been dealing with a flood of AI-generated edits. Most are "AI slop", which is to say poorly sourced, factually wrong, generated without thought and shoved into the world because creating it costs nothing.

In response, the community at Wikipedia put together a comprehensive guide to spot signs of AI writing as part of their AI cleanup effort. It catalogs a bunch of tells across vocabulary (apparently AI overuses words like "delve," "tapestry," "pivotal moment"), structural patterns (rule-of-three lists, em dash abuse), and tone (promotional filler, sycophantic openers). It's definitely worth reading if you want to understand why AI text feels off to us.

Of course, the guide is public because it's on Wikipedia, meaning it's in the training data too.

I took that list, handed it to a model that isn't GPT, and told it to avoid every pattern on the page and package the result into a reusable skill. The output didn't trip a single tell.

Apparently I'm not the only one to have this idea. Within the same hour I found someone who'd already packaged this as a shareable tool.

If nothing else, there are GPTZero MCP servers now, so you can have Claude Code/Cowork (anything but ChatGPT) loop its way to perceived humanity. Just generate some text, check the score, revise, repeat until it passes.

I also tested a few of the free AI humanizer tools that have popped up. Half of them didn't even work. The others passed the detection check, but they do it by flattening everything and removing the voice until what comes out feels like it has less color overall. This color is what defines human writing. It's not always clean or presentable. "What if I just, like, really like using the word like, man?"

This is a defeating cycle through and through. AI generates text with obvious patterns. People document those patterns. The documentation becomes training data. AIs learn to avoid the patterns. Detectors catch less. New patterns get identified. With each iteration, the gap narrows.

I think we have about a year before detection becomes impossible. Probably less.

The merge

The detectors don't assume a clear binary, but the humans making decisions based on their output certainly do. You either used AI, or you did not. If your text is flagged, it must have been generated at least in part by a computer. That binary is dissolving from both directions.

The AI side is obvious. Models keep getting better at producing human-sounding text by default. Implement a few of the tricks above and you're done.

The human side is weirder. We're reading AI-generated text all the time now (in emails, documentation, social media posts, and articles that may or may not have a person behind them). My totally unsubstantiated theory is that since we're prone to absorbing the patterns of what we read, this exposure is steadily turning AI-isms into human usage too. Linguists call this process convergence.

Maybe my GPTZero experiment wasn't showing that the detector is bad at its job, but that the categories don't hold up anymore.

I use AI tools constantly. A lot of what I write starts with me throwing back-of-a-napkin thoughts at Claude, and we go back and forth as sparring partners until I know what I want to say. Other stuff I write from scratch. Even the "from scratch" stuff is shaped by years of interacting with AI output, so the line between these processes is blurrier than one might think.

There's an asymmetry here. People freely admit to using AI to write code. Nobody cares unless the code sucks. Admitting you used AI while writing prose on the other hand feels like confessing to cheating. I think it's because we treat writing as proof of thought and code as proof of function. When AI touches the prose, it feels like fraud in a way that AI-assisted code doesn't.

Perhaps the fraud isn't in the tool as much as in the absence of thought. Others have said this better than I can.

David McCullough (American historian and two-time Pulitzer winner) put it well: "Writing is thinking. To write well is to think clearly. That's why it's so hard." Leslie Lamport, the father of distributed computing and initial developer of LaTeX, said something similar: "If you're thinking without writing, you only think you're thinking."

The tool doesn't change whether you're thinking. I only care whether you cared enough to work through what you were saying and make it yours.

Steinberger's approach (explicitly labeling AI agents so people can choose what to engage with) is closer to a real answer. It's not a solution, but it's significantly better than any detector. Just tell people what's AI and let them decide.

We're nowhere near that being standard. For now we're stuck with detectors that don't work, generators that keep improving, and people getting falsely accused of being machines when they turn in their homework.

That last one is worth sitting with. Tools like Turnitin are now baked into the academic pipeline at most universities. When a student's work gets flagged as AI-generated, they often have to retake the course and pay for it again.

To be clear, AI-assisted cheating is a real problem that institutions need to solve, but not this way. The present situation is that the accused student is asked to prove a negative (that they didn't use AI) and the burden falls entirely on them. The adjudicator is the same institution that collects tuition if the student has to retake the course. I'm not saying there's extensive precedent of institutions exploiting this, but the financial incentive exists, and it's nearly impossible for a student to challenge.

My underlying point is that the tools that were supposed to protect human writing have rapidly become a way to punish human writers who happen to conform to a certain style. That's not a detection problem; detection is a ship that sails farther away with every passing day. It's a problem with the way we're planning for a future that we don't yet understand.

Trying this blogging thing

2026-02-21T00:00:00Z

This site has been a long time coming. I've been meaning to consolidate everything I'm working on into one place for years, and I've finally gotten around to it.

For the nerds

I built this site using the Eleventy static site generator.

Why Eleventy? It feels like I've tried every moderately popular SSG, plus a few of the lesser-known ones. I currently have sites running under Nikola and Cobalt.

I use Nikola when I just want to spin up a site (optionally with a blog) for a project. I don't particularly care to play around with the style, I just want to write stuff and put it online wrapped around a template that I know is accessible, user friendly, and functional. Then I want to load it up in my browser and get the dopamine hit of feeling like I did a lot of work before moving onto something else.

I like Cobalt when I want a light-weight builder that is entirely unopinionated, and that won't block me from anything at the cost of having to write (or get AI to write) my templates and essentially everything else. A bonus is watching the site build almost instantly because Rust.

Eleventy feels like the perfect middle ground between the two. I get to provide my own layouts, styling, and structure. Collections let me publish both a blog section for thoughts I want to catalog in the moment, plus a resources section for longer-running articles that I will maintain somewhat consistently. When I want more goodies like RSS feeds, etc it's a simple matter of pulling in a plugin.

Anyway, more to come. For now, the lights are on.