criley2

You can do basically the same thing as cloudflare except as a skill you run in your local harness. If you're going through the motions with PRs and are familiar with actions, you can have it run in a github action instead. But this is basically just a skill. The Claude code review skill is a simple version of exactly this.

I've come to realize that folks are including "ai-slop" in their ~public use of AI to intentionally signal to others that they're using AI. To some, that signal results in revulsion. To others, that signal results in approval. In my opinion, the approval signal comes from investors, board members, c-suite, and now management. They want us to use AI? Let's make sure they know we are.

Every abstraction is leaky but is ignorance truly bliss?

In my humble opinion, most of the code I've ever touched was slop, and I think I left it in a better state than I found it. What more can you do?

Brother, I don't care who writes the specs as long as they sign the checks on time. And yes, I do care about my work even if upstream is slop. In a relay race, you can lower your performance to weakest leg, or you can be the strongest leg. And maybe I just like to run.

There is no way to facilitate untrained users in the healthcare space to vibe code real applications touching patient data. There is no magic policy, firewall, or "facilitation technique" which can make vibe coded software reliably meet contractual and regulatory obligations with a high degree of security in the healthcare space.

If you care about data privacy, especially your own protected health information, that sentence should give you a lot of comfort.

In a HIPAA environment, people who are sufficiently trained on how to develop regulated software securely are called "software engineers".

In my opinion, agents will replace the majority of the rest of businesses before they are good enough at agentic engineering to be able to autonomously develop software that safely and reliably can manage PHI without a single mistake.

It goes without saying: never trust your PHI to any company who is vibe coding in production.

Claude Code uses Ink, a react library in javascript for UI. The upswing is probably stuff like this making it super easy to write a TUI.

Technology is on a generational 10,000 year run of non-stop successfully solving human problems.

I actually think "just asking ChatGPT" is fine, because A) the data in these apps is suspect at best and B) the data behind calories is also pretty suspect (but we all play along because we can adjust other variables to make it all "work" well enough).

Once or twice a year I spend a few weeks meticulously measuring ingredients/cooked foods and recording calories and on complex recipes apps are next to useless at getting accurate data. You're trying to input five or ten relevant ingredients, and then weighing your cooked outcome to try and divide the ingredients by proportion. Frankly it's a mess and most people aren't doing it for home cooked meals, and are getting very lossy outcomes (weighing cooked chicken and marking it as raw chicken, etc)

With reasoning and tool calling (combined with me meticulously weighing before and after), it's producing fine data for my purposes.

Feels like a pretty wildly misleading graph. What do they say about lies, damned lies and statistics?

This graph is literally designed to abuse correlation =/= causation by attaching the arbitrary label "microsoft acquires github" so that the reader will apply causation to the uptime.

Now let's overlay ontop of the uptime graph a few lines of: # of monthly active users, # of monthly commits, size of PRs, action minutes per PR (whatever demonstrates scaling)

Something tells me that the uptime issues follow scale more than they do ownership... but that's not the narrative that this chart was designed for...

Are you referring to the one (1) study that showed that when cheaper LLM's auto-generated an AGENTS.md, it performed more poorly than human editted AGENTS.md? https://arxiv.org/abs/2602.11988

I'd love to see other sources that seek to academically understand how LLM's use context, specifically ones using modern frontier models.

My takeaway from these CLAUDE.md/AGENTS.md efforts isn't that agents can't maintain any form of context at all, rather, that bloated CLAUDE.md files filled with data that agents can gather on the spot very quickly are counter-productive.

For information which cannot be gathered on the spot quickly, clearly (to me) context helps improve quality, and in my experience, having AI summarize some key information in a thread and write to a file, and organize that, has been helpful and useful.

Even more than validating ideas, I think my personal AI use falls into two categories:

- Exploration: I am "vibe coding" to explore a domain, add many features, refactor the app over and over, as a real time exploration of the domain to see what works and what doesn't

- Specific Execution: I have a full design, a full idea, I've thought about architecture, we're making a plan and we're executing this extremely coherent vision

I've enjoyed using AI for both cases.

Whenever a new one comes out, there's a good chance they're free for a week on Zen, so I try out any free ones. For example, MiniMax M2.5 and Qwen 3.6+ are free right now.

Personally, I've had a lot of good results in my little personal projects with Kimi K2.5, GLM 5 and 5.1, and MiniMax M2.5.

I haven't tried $20 claude code recently, but I've used OpenCode Zen primarily so I can play with opensource/chinese models which are very inexpensive. I'd spend $0.50-$1.00 on a single claude opus 4.6 plan mode run, then have a chinese model execute the plan for like $0.10-$0.15 total. I'd keep context short, constantly start new threads, and get laser focused markdown plans and knowledgebase to be token efficient.

If I just let opencode zen run claude opus to plan and execute, I'd spend $20 in like 5 minutes lol

For as rigorous of a Turing test as you present, I believe many (or even most) humans would also fail it.

How many humans seriously have the attention span to have a million "token" conversation with someone else and get every detail perfect without misremembering a single thing?

The philosophy still works, you just have to change your view. Instead of trying to work side by side with the agent on every turn (inside of your IDE), instead the agent performs a unit of work and then you review it. You can use your IDE to view the diff, or another diffing tool.

If you've dug in sufficiently on plan mode, then what the agent is executing is not a surprise and shouldn't need input. If it does, the plan was insufficient and/or the context around the request (agents.md, lessons.md, or whatever tools and documents you use ) weren't sufficient.

EDIT: Maybe it doesn't work in cursor, but I continue to use vscode to review diffs and dig in on changes.

I asked a rhetorical question to get the reader to think about a topic. I was not looking for a rote recitation of a well-known textbook answer. Maybe you should not be on the comment section of an engineering website if you find discussion so offensive.

The history of programming is also each generation writing far less performant code than the one before it. The history of programming is each generation bemoaning the abstractions, waste and lack of performance of the code of the next generation.

It turns out that there is a tradeoff in code between velocity and quality that smart businesses consider relative to hardware cost/quality. The businesses that are outcompeting others are rarely those who have the highest quality code, but rather those that are shipping quickly at a quality level that is satisfactory for current hardware.

Honest question: Why does it matter? They got the product shipped and got millions of paying customers and totally revolutionized their business and our industry.

Engineers using LOC as a measure of quality is the inverse of managers using LOC as a measure of productivity.

There's this fallacy with AI generation that people think that all you have to do is type "i lik musik pls remake favrite song but better" and you get amazing results.

This is patently untrue.

It's like how if a junior engineer and a principal engineer use claude opus 4.6 they get radically different results. The junior doesn't have the taste or knowledge to know good from bad so the AI oversteers and slop is made. The principal has finely tuned sense of taste and deep knowledge, so they aggressively steer the AI at every step. This is also true in other AI domains.

To be absolutely clear: you can't make good AI music. Try all you want. Try the prompt you just wrote. Show and tell. It's not something you're going to be able to do.

How much of your super-awesome bandcamp music is topping charts, selling millions, packing mega stadiums, and is penetrating the zeitgeist so deeply that people around the world are addicted to it?

Maybe, just maybe, I'm not talking about "my" music tastes, but offering commentary on the state of music at a global scale. Weird that this point was so hard to follow!

I'm talking about modern music. Just because a couple of dweebs on hackernews have "totally amazing underground music" doesn't mean the overall zeitgeist agrees. Regardless of your esoteric music tastes, music by sales and music by charting tells a very different story. And that story is one of replaceable slop.

It's not that a leader is capable of long-term planning, it's that a system is. I am a big proponent for democracy, but the fact is simple that when you do a massive regime change every ~4 years, nothing big will get done. You have about 2 good years to do something, and most big projects simply require more time than that.

China, unlike the US, can look 10 years into the future and consistently execute towards a goal. That's not because of leaders, it's because the systems are fundamentally designed this way.

It's like the two party system in the US. It's because of first past the post in the Constitution. The system is designed to do this, so it does it. The US is designed to be unable to plan or execute long term vision.

Modern music has done this to itself. When the human product is already pure corporate slop, it's not hard for AI to compete.

Hopefully AI outcompeting humans at slop sparks a renaissance of humans creating truly beautiful human artwork. And if it doesn't, then was anything of value truly lost?

Kagi is a for-profit corporation.

The analogy works fine! You're just being obtuse.

- Outsourcing

False. If you "outsource your code" to a compiler and just write higher level language, you're not an engineer. You literally don't own any of your own code, just an abstraction of it written in human language. See how that works? An engineer can delegate -- period.

- "I wouldn't call myself a software engineer if I got AI to write all the code for me"

If all you do is write code you're not an engineer. I think you fundamentally don't know what engineering is. In a very real sense engineering is what you do when you're not coding. The civil engineer doesn't construct the bridge personally.

- "Secondly, it's not just about "enjoying the journey of construction", it's also about caring about the quality of the end results".

Codemonkeys DON'T CARE about the quality of the end result. They only care about their little corner of the zen garden. Writing real software for real users is by far the worst part of a codemonkeys job.

- "Getting vibe coded software that is as stable as a "bridge that is safe and lasts for a century" is not a matter of careful engineering decisions, it's mostly a matter of luck"

Nonsense. The engineer who spends 90% of his time architecting systems and testing them at a high level is making safer and more stable software than the codemonkey who spends 90% of his time tinkering with the details. Forest for the trees.

- "unless you're doing extensive reviews of the generated code, at which point you greatly diminish the time you're supposedly saving."

Who said anything about "saving time"? We're engineering high quality systems. Some of us spend our time at a higher level, thinking holistically about the system, testing multiple concepts and rapidly iterating. Others demand bespoke handwritten code and in the time allowed can barely finish a single concept with a questionable amount of polish. Whatever their first idea is will ship, and they'll have no real ability to justify the architecture other than vibes.

>Would you currently trust a bridge designed by a civil engineer using AI for all of their calculations ?

Of course. I've seen how sloppy and lazy humans are, and I already use the bridge, and if the safety truly came down to the output of single person, then the risk is already significant.

I must say, I got a chuckle at "using AI to do their calculations". Oh no, my agent is going to write a python script to do basic maths, and check their work against a series of automated tests, the sky is falling!

>AI has just exposed that many "engineers" are "temporarily embarrassed project managers", which is fine in the sense that it makes it clearer who actually enjoys making things and who just wants the end result regardless of how it's made.

AI has also exposed that many "engineers" are just "people who like fiddling with code" and that's fine in the sense that it makes it clear who are the actual engineers who are engineering solutions to real human problems and who just want to tinker with code.

Like imagine slandering a civil engineer "you just want a bridge that is safe and lasts for a century, you don't care about enjoying the journey of construction".

I'm convinced that most programmers largely hate making software and solving user problems. They just like fiddling with code. And honestly it explains so much.

What a utopia, where code quality matters in all domains!

In my opinion nearly the opposite is true: modern business solves for the "minimum viable quality". What is the absolute lowest quality the software can be and not tank the business.