Dependencies add complexity because they often handle many, many different use cases. Your app probably only needs a specific one.
If you replace dependencies with your own code, it's far easier to maintain because the complexity goes away. You only have the features you need.
Our customer support doesn't just answer tickets. We dig in, understand the problem, and see it through to a fix.
Jake Duchesne said it well: "If you want a deployment platform where someone genuinely has your back, Hatchbox is it."
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Opus produced the best output with Ruby in this shoot-out between a bunch of different languages. Fewest tokens, fewest LOCs, fastest completion. Maybe one day, AI will just be writing straight machine code, but until then, Ruby is a superb target. https://t.co/6eFuCUXGWh
You build it. We ship it. Stop worrying about servers, configs, and deployments — Hatchbox handles all of it so you can focus on what actually matters: your app.
Hey @hatchboxio Do you have a recommended cheapest way to setup and host a new app?
My previous go-to is DO droplets with managed postgres but wondering if you have a cheaper suggested alternative?
What if deploying your app was the easy part? With us, it is. We handle the servers, the deployments, and everything in between — so you can stay in your zone and keep building.
I find it very funny when anyone feels confident that they've figured out agentic programming, even funnier when they're trying to teach others how to do it. I've been working on OpenCode since May of last year and I still have days (like yesterday) where I'm not even sure any of this is a good idea lol
I end up landing on "yes, these models are an incredible tool" but it's still all very confusing, lots of tangled thoughts and emotions and realities.
I badly miss the mundane coding tasks that broke up my days/weeks, the ones where you put on the headphones and just bang out 600 lines of code. But, no question, replacing those hours of my time with a few minutes of waiting on an agent is a boost and worth being excited about, despite the mixed emotions.
Then there's the distance that can creep in between you and the codebase if you start getting apathetic. I think it's pretty common at this point to make even small changes by prompting the models. It's less friction than finding the relevant code and making the change yourself. And less friction seems to win, must be some law of the universe or some shit. When most or all of your interactions with a codebase start flowing through the models, you start to lose track of where things live, which abstractions/components are carrying the weight, etc. It's a scary feeling to wake up and realizing you can't even reliably @<mention> a precise file for a change you want to make, and you have to get more vague, leaning harder on the model.
It all creeps up on you, there's an undeniable dopamine hit from using these things, and the resulting come down is predictable, like coming off a sugar high. On the positive side, it's really nice seeing other devs go through the same cycles, knowing we're all in this together and we'll ultimately figure it out.
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@opencode Hmm, I take it back.
Dug into the issues that KimiK thought it had found and 4/5 of them were false positives.
Opus comes out as the clear winner overall.
Did a little race this evening with the help of @opencode
Same branch, same custom review skill (prompt)
Kimi K2.5 - 2m4s
Gemini 3 Pro - 2m14s
MiniMax M2.5 - 3m1s
Opus 4.6 High - 6m27s
GPT 5.2 Codex High - 6m31s
GLM 5 (Free) - 10m19s
@opencode I gave them all a second chance. Prompt: Please can you carefully check all the changes on this branch again
Similar results overall, but Kimi K improved subjective quality to 8/10