Chatbots are dead, long live chatbots!
At this point in the AI hype cycle, you probably cringe at the idea of chatbots. We do too. Of course, there are good chat interfaces backed by powerful models, like ChatGPT, Claude, or RunLLM (we’re biased 🙂), but there are also tons of low-quality chat-with-your-docs RAG implementations that cost $12/month and return useless results. No one wants to use those bots — they usually respond with bad answers, they’re easily confused, and they frankly give AI a bad name.
As Joey talked about in his expectations for 2025 on DeepLearning.AI, 2025 is going to be the year where we stop chatting and start doing. We actually had a slightly less developed version of this idea all the way back in February of last year in a post called *There’s more to LLMs than chat.* This is to say that we are big proponents of the idea that language models can and should be used for more than a question-in-answer-out mode of interaction.
This means that calling a product “just a chatbot” is something of an insult today. We might even be tempted to say that chatbots are dead. You might be surprised to hear that we disagree. Chat, when it’s done poorly, is of course a bad experience. But well-designed AI systems have the opportunity to break out of a rigid, question-in-answer-out mode and become proactive agents — all while maintaining the familiar chat veneer.
