We can all agree that these chatbots are really good. But when integrated into software, they're practically dogshit. Same can be said to emerging technologies in the past like shareware games, the true web (Web 2.0), and Linux.
atp, people are still experimenting over what makes these models tick. You have people working on agents, multimodal AI, RAG systems, fine-tuning, prompt engineering, and novel architectures. At scale, these are unreliable as hell. The more control you give to AI, the more prone you are to errors. None of it is reliable at scale. Thus, the same pattern is repeated for these LLMs: early adopters wrestle with janky interfaces, inconsistent outputs, and fragile integrations. Then, slowly, tooling improves. Standards emerge. Best practices crystallize. The "dogshit" phase is not a bug, it’s a feature of innovation. It’s the messy sandbox where the real breakthroughs are prototyped.
Right now, LLMs in production feel like duct-taping a jet engine to a bicycle. Sometimes, it flies. Often, it explodes. But each explosion teaches us how to build a chassis that can handle the thrust.
The winners won’t be the ones who waited for perfection. They’ll be the ones who shipped the janky MVP, learned from the dumpster fires, and iterated like hell while everyone else was complaining about token limits or JSON formatting errors.
Let's keep innovating, people.
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