dirtbag__dad

This is also my experience, but when I saw how few tokens/second with a large model it gets locally I was bummed. I’m wondering if I’ll be obligated to upgrade in the near future

The point is that the implementer shouldn’t have to investigate to know whether the key’s value is nullable.

This to me feels more like a developer skills issue than a problem with the LLM. At my day job, we banned using untyped data structures like this entirely well before LLMs because no one could read code that passed them around.

You could use a data structure that better articulates an optional field, like a dataclass with type hints or a pydantic model. Then you, your coworker, and the agent alike, aren’t guessing at whether the key’s value is optional.

Another example in this vein is having many optional parameters on a function or api route, that drive behavior deeply nested in the application logic. Or maybe they were there for testing and never deleted. No one comes across this code next and understands it easily. How could you expect a LLM to understand it, either?

I find it funny when people blame the LLM for dog shit code, but at the same time have a pollock painting of code they load into its context, and are like “put a person in the horse and carriage!” And the LLM is like “bro I just see dots and squiggles but you asked so boom!”

This is what’s up! Having worked on several medium sized python projects where linting and type checking were introduced late in the game, having them as a first class feature of the package manager will save so much unnecessary pain.

IMO, part of the problem is that people just don’t know that linters or tools like this exist at all. This is the best type of product marketing where the product gets meaningfully better, while educating the users for free.

At an early stage startup, like OP is asking about, you can expect engineers to do everything.

This is a story that cheap employers tell. Hire for “growth potential” in order to save $50k, and in return the rest of the team is taxed for many quarters, results are mid at best.

Of course it is true that some juniors outperform competent seniors. It’s also true some seniors are just checked out. But when you are willing to hire folks with meaningful years of experience, you get meaningfully better velocity and quality. It doesn’t matter how simple or complex the problem is.

Yes! As another Pennsylvanian, this is a hard requirement for my forever home. The idea that I’d go all-in on a large property in an undeveloped area, only for the surrounding land to get developed or demolished is scary. State game lands is a way to protect against that outcome.

Also a concern is proximity to fracking and now data centers. Not sure how to see if neighbors sold their underground…

As an anecdote, my parent’s home, where I grew up, is a small plot along my town’s watershed property. When the price of lumber went up recently, the town council conveniently remembered that the watershed property was once a massive “tree farm,” and since has leveled all of the surrounding woods. We never expected this. It has been emotionally crushing.

There is surely a tremendous amount of waste and noise right now. But does it _actually_ matter what the code looks like for a desktop app that’s useful to a small handful of people? Every single implementation has at least one person who thinks it’s dog shit, no matter how correct or perfect it is. We have to get past this. If you really can’t stand it, build the thing yourself or some deterministic rails to reel it in.

And, there are also people who know what they’re doing building things they couldn’t before.

This situation is a net positive, and not too different than before. It’s up to you to navigate the noise.

This, with an extremist take on code quality via linting in ci, is no doubt the future, at least for maintenance and extending the interface kind of work.

1. How does this work with greenfield lifts where the scope and final vision are not yet figured out?

2. Sorry if I missed this in the post, but will you open source this system?

This resonates with me. I joined a climate tech company to help save the world. I built data pipelines like anywhere else

> I also see a lot of Devs simply trusting that the code is correct, they are losing touch with the code.

My team has a non-engineer vibe coder who doesn’t know how to even use git, but managed to put together a large application that serves enterprise customers better than the real SWEs we had working on the project.

We’re in the process of porting their code into the main codebase, and it’s obvious to me, not so much them, that there is an insane amount of waste. But I’m not sure whether that’s a bad trade off, the end product works and llms get whatever he needs done.

OTOH, I’m an experienced SWE who is taking a stab at writing dev tooling in rust, which I don’t know and don’t have the time rn to learn. I am very aware there is a lot of waste, the project is obviously moving slower than if I was more involved with design. I was ok with the trade off but I’m growing antsy now.

All to say, it feels to me that vibe coded tech is a viable path so long as you accept what you’re going to get.

The one exception I see rn is when we try to do brownfield work, LLMs get very confused and simply cannot manage an old dog shit human written system with a new set of concepts floating in. Jury is out whether this will also happen with ai slop, but again maybe it just doesn’t matter

I don’t know why this was downvoted. I have children and the first thing I questioned was whether the author has kids.

The intro to the article feels like the author asked a LLM to summarize journal papers about consciousness. It seems there is not a consensus around what it is.

Can anyone in this field provide a directional overview of what we think consciousness is in 2026?

meetyogi.com | Senior Software Engineer, Backend / Product | $180-220k | Hybrid NYC | Series A | 35 headcount, ~10 in engineering

Yogi aggregates and analyzes millions of customer feedback data points from online retailer reviews, social, cx ticketing systems, etc to help companies make better decisions about their products and markets. We operate mostly in CPG, where our customers are household brands you'd recognize, both enterprise and up-and-coming.

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Everyone is kind and engaged with work at Yogi. It's a nice vibe.

Our stack is pretty standard SaaS - python (fastapi, prefect), postgres/clickhouse, react/typescript web app. The app experience is what you'd expect from a data analytics platform - charting and agentic workflows that generate insights from the data.

In terms of the moment, we're reaching the bounds of some early domain assumptions, while also figuring out how to expand into new ones. On the code front, broadly speaking we're improving quality and process each quarter by an order of magnitude. AI has been a boon for us. (I've personally invested a lot in our dev tooling to make code output high quality and deterministic)

There's a lot of greenfield opportunity and also scale challenges to be solved on existing tech. No shortage of things to do, ownership is as much as you want to take on.

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Interview process is a chit chat with our CTO, an onsite with a practical coding exercise (not crazy i promise), a system design conversation, and behavioral interview.

Email me at jon.young(at)meetyogi.com or connect w me on linkedin /joncyoungii if you want to learn more. Happy to answer any questions you have honestly and refer you if it makes sense on both ends

I can validate that is frustrating. An inability to articulate more than the code is bad and it’s complicated is surprising from a TL.

That is probably the case in most companies, and as I said it’s not that hard to identify what is impacted by that dog shit code.

Having a spike/PRD/TRD process, really anything written by a human long form, can help build alignment. This is because you have ample time to ask questions and dive deeper, and it’s not personal it’s just part of the process.

I’m not sure whether the charts I created were themselves the convincing piece of evidence. They just happened to be where I found common ground easier and then maybe the rest just clicked