Alternatively, how would you suggest content that takes time and effort to make be funded?
I get that it's sad, but I'd gladly pay a monthly sub to use a not enshitified internet, rather than the cluster fuck of ads and data stealing that exists in the modern web. Spending time on the 90s and early 2000s internet and comparing it to this dumpster fire makes me so darn sad.
Glad I'm not the only one using Gastown as a space heater. I filed an issue here and hope to find some time this week to research more: https://github.com/dolthub/dolt/issues/10849
It also aligns suspiciously with the decline of the sedan and the near-total victory of SUVs and pickup trucks in the American passenger vehicle market.
Good point. The missing statistic in this thread is the number of injuries, which you'd expect would help tease apart big cars (mass) from phones (attention).
SUVs and pickups did not win anything in 2010, F-series trucks had been number one best seller through the entire 21st century, and the top 10 selling cars were half and half Camry/Civic/Accord and trucks and SUVs.
>Seven out of the top ten best selling vehicles in 2010 were sedans
I only see six sedans in your link. But regardless if you count CR-V or Fusion as a sedan, you are arguing for me. 2010 being a recession year is prominent for drop of trucks and SUVs in sales, not "near-total victory of SUVs and pickup trucks".
>In 2025
And how does this align with increase of pedestrian deaths from 2010 to 2023?
Easily fixed with a cheap camera that records the inside of the car to a device similar to an airplane flight recorder. If we cared about people outside of cars more than people inside of cars. Funnily enough, the political will does not exist to even video record airplane pilots to the flight recorder, even after the numerous suicidal pilots in the last 30 years.
Another funny thing is to notice which people are politically acceptable to record, such as store clerks, warehouse workers, call center workers, basically anyone being paid on the lower end.
But the higher up the socioeconomic ladder you go, the less politically acceptable it is have your actions recorded, even just for scrutiny after an incident.
I'm looking forward to trying this. I've had a positive but high-variance experience with Gastown[1], which is in the same genre. I hope that Scion does better.
My main complaints with Gastown are that (1) it's expensive, partly because (2) it refuses to use anything but Claude models, in spite of my configuration attempts, (3) I can't figure out how to back up or add a remote to its beads/dolt bug database, which makes me afraid to touch the installation, and (4) upgrading it often causes yak shaving and lost context. These might all be my own skill issues, but I do RTFM.
But wow, Gastown gets results. There's something magic about the dialogue and coordination between the mayor and the polecats that leads to an even better experience than Claude Code alone.
I'm trialing it on very silly things, like a economic simulator game in Rust/Bevy. I put in an entire road map document with inline specs and goals, wild milestones, with tasks like "working bid/ask spread when factories buy or sell on the market to make pricing dynamic and realistic", "political entities can set work conditions", "international trade has pricing dynamics that take into account currency interchange and tariff rates", "infrastructure for trade improves as trade volumes increase across given tiles".
Out the other end over about 3-4 five-hour-sessions comes about 85% functional code for every single listed thing. I'd guess you'd be looking at a team for months, give or take, without the automation. Total cost was around $50 in VM time (not counting claude since I would be subscribed anyway) I'm not letting that thing anywhere near a computer I care about and rust compiles are resource intensive, so I paid for a nice VM that I could smash the abort button on if it started looking at me funny.
So I liken it to buying an enormous bulldozer. If you're a skilled operator you can move mountains, but there'll still be a lot of manual work and planning involved. It's very clearly directionally where the industry will go once the models are improved and the harnesses and orchestration are more mature than "30% of the development effort is fixing the harness and orchestration itself", plus an additional "20% of your personal time will be knocking two robots heads together and getting them to actually do work"
Edit: some more details of other knock on work - I asked for a complexity metadata field to automatically dispatch work to cheaper/faster models, set up harnesses to make opencode and codex work similarly to how claude works, troubleshot some bugs in the underlying gastown system. Gastown fork is public if you'd like to have a look.
>working bid/ask spread when factories buy or sell on the market to make pricing dynamic and realistic
Does it deliver on the "realistic" part? My experience with most models is they make something that technically fulfills the ask, but often in a way that doesn't really capture my intent (this is with regular Claude Code though).
Yep, garbage in garbage out, I had some additional specs beyond the summary above, everything requires refinement as well, but honestly I never thought I was going to have a simcity/civlike clone in a couple weekends that's reasonably playable.
We ended up adding workflows with deterministic paths, that can use RAW API calls, CLIs, and agents. I think that was a big differential.
We also added pi-mono, and started using more and more other models for different tasks (Gemini, K2.5, GLM-5, you name it).
I think the problem is that most are building solutions that rely in one provider, instead of focusing self learning capabilities on improving the cost-quality-speed ratio.
I made one similar harness, mine does lightweight sandboxing with Seatbelt on Mac and Bubblewrap on Linux. I initially used Docker too, but abandoned it. I like how these 2 sandboxes allow me to make all the file system r/o except the project folder which is r/w (and a few other config folders). This means my code runs inside the sandbox like outside, same paths hold, same file system. The .git folder is also r/o inside sandbox, only outside agent can commit. Sandboxing was intended to enable --yolo mode, I wanted to maximize autonomous time.
Work is divided into individual tasks. I could have used Plan Mode or TodoWriter tool to implement tasks - all agents have them nowadays. But instead I chose to plan in task.md files because they can be edited iteratively, start as a user request, develop into a plan with checkbox-able steps, the plan is reviewed by judge agent (in yolo mode, and fresh context), then worker agent solves gates. The gates enforce a workflow of testing soon, testing extensively. There is another implementation judge again in yolo mode. And at the end we update the memory/bootstrap document.
Task files go into the git repo. I also log all user messages and implement intent validation with the judge agents. The judges validate intent along the chain "chat -> task -> plan -> code -> tests". Nothing is lost, the project remembers and understands its history. In fact I like to run retrospective tasks where a task.md 'eats' previous tasks and produces a general project perspective not visible locally.
In my system everything is a md file, logged and versioned on git. You have no issue extracting your memories, in fact I made reflection on past work a primitive operation of this harness. I am using it for coding primarily, but it is just as good for deep research, literature reviews, organizing subject matter and tutoring me on topics, investment planning and orchestrating agent experiment loops like autoresearch. That is because the task.md is just a generic programming pipeline, gates are instructions in natural language, you can use it for any cognitive work. Longest task.md I ran was 700 steps, took hours to complete, but worked reliably.
Scion looks interesting, as a “hypervisor for agents”. It has Kubernetes influences, and a substrate for agent execution is a useful primitive.
Gastown goes further than Scion in that it chains agents together into an ecosystem. My sense is that Gastown or similar could be built as a layer on top of Scion.
Dan Shapiro helped shape my thinking on the two most important capabilities for agent orchestration as concurrency and loops. Scion provides concurrency only at present, and Gastown is also more concurrency-oriented than loops.
Fabro is a new OSS project I am working on which attempts to do both loops and concurrency well: https://github.com/fabro-sh/fabro (Maybe someday it should be built on top of Scion.)
The article is a bit of a strawman, and a bit of an advertisement for a security consultancy. If you ask someone else to pick a password for you, then it's a secret known by two people. So don't do that. That was true a thousand* years ago. It's still true today.
*I know, I know, hash functions didn't exist on Earth a thousand years ago. Still true.
I urge you to actually read the article, because it doesn't say anything about the risks of the LLM knowing your password (e.g., stored in server-side logs), it talks about LLMs generating predicatable passwords because they are deterministic pattern-following machines.
While the loss of secrecy between you and the LLM provider is a legitimate risk, the point of the article was that you should only use vetted RNGs to generate passwords, because LLMs will frequently generate identical secure-looking passwords when asked to do so repeatedly, meaning that all a bad actor has to do is collect the most frequent ones and go hunting.
The loss of secrecy between you and the LLM only poses a risk if the LLM logs are compromised, exposing your generated passwords. The harvesting of commonly-generated passwords from LLMs poses a much broader attack surface for anyone who uses this method, because any attacker with access to publicly available LLMs can start mining commonly generated passwords and using them today without having to compromise anything first.
You're right; I could have phrased the issue better, though I certainly did read the article. Let me try again: letting someone else pick a password for you requires you to trust that they did it well, and you get no benefit in exchange for that trust. That's true for other humans, websites, and now LLMs.
You could zoom out a bit and rephrase the question.
Your great-aunt Ida died and left you a consulting team of ten pretty good software engineers. The team's contracts all just ended, so starting tomorrow they'll be idle. Ida said you must run the business for at least two years (fortunately, overhead is already paid for), or forfeit your share of the inheritance. After that you can keep going or liquidate it.
Sites displayed ads. Then they decided, or found, that ads didn't bring in enough revenue, so they added paywalls.
Paywalls are annoying, they don't scale, and they break the promise of an open web. All that is sad.
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