From: gregisenberg
The current landscape of AI tools allows individuals, regardless of their technical background, to quickly develop sophisticated AI-powered applications, particularly voice character apps [00:00:00]. These “character apps” are considered the new form of applications [00:13:01].
Core Development Tools
Developers can leverage a suite of tools and platforms to streamline the creation of AI apps:
Cursor (Code Editor)
Cursor is a code editor that integrates with large language models (LLMs) to assist with coding [00:03:25].
Daily
Daily is a company that provides tools for building voice AI applications [00:03:47]. It handles much of the heavy lifting for voice and backend processes [00:03:39], including the complexities of speech-to-text (STT) and text-to-speech (TTS) conversions, performance, and error handling [00:11:14].
- Daily Bots: A specific library within Daily that simplifies the process by handling LLM calls directly, allowing developers to focus on configuring bot behavior [00:04:16], [00:08:43]. To use Daily Bots, users sign up, obtain an API key, and integrate it into their project’s
.env.localfile [00:04:31], [00:05:00]. - Pip Cat: Another library provided by Daily, more focused on developers, offering greater control over interfacing with AI and building voice assistants [00:04:00], [00:34:46]. This is suitable for those who understand how these systems work and desire more customization [00:34:56].
Together AI
Together AI is a provider of AI models, such as Llama 3.1 70B, which can be specified for use within Daily’s backend for AI responses [00:08:20], [00:08:28].
Next.js (Web Framework)
Next.js is a framework that utilizes React to build websites and allows for setting up servers to run code through specific routes [00:20:21].
Vercel (Deployment Platform)
Vercel, the creator of Next.js, provides a platform to host Next.js applications online [00:29:19]. Deployment is simplified, often requiring only one command (vercel) after logging in [00:29:38], [00:30:41].
Key Concepts and Processes
Voice Chat Apps
These applications enable audio conversations with AI characters, similar to an “audio ChatGPT” [00:00:50]. Users can create a variety of voice apps, such as a fully working weatherman character app [00:00:21], or even a virtual “FaceTime” call with a Vtuber [00:32:42].
AI Backend Process
The typical flow for a voice AI character app involves:
- Speech-to-Text (STT): Audio input from a microphone is converted into text [00:10:39].
- LLM Processing: The text is fed into an LLM (AI model) [00:10:50]. The LLM processes the input and outputs its response as text [00:10:54].
- Text-to-Speech (TTS): Daily takes the LLM’s text response and pipes it into a TTS provider to convert it into speech [00:11:00].
- Audio Output: The generated speech is then streamed back to the user’s browser [00:11:07].
Character Configuration
The personality and behavior of the AI bot are configured through a configuration file [00:08:40], [00:09:55]. This includes defining prompts (e.g., “You are an assistant called Example Poot”) and instructions on how to speak [00:10:17]. Pre-set characters are available, but developers can easily create custom characters by editing this file [00:11:46], [00:12:22].
Function Calling and Tool Integration
Function calling allows an LLM to interact with external systems and APIs, enabling it to “do stuff” beyond just outputting text [00:09:15], [00:16:02].
- Mechanism: The LLM, if smart enough, understands instructions to output text in a specific format indicating a function call [00:16:35]. The external system (like Daily’s backend) then takes this structured text output and executes the corresponding code or API call [00:19:06]. The AI itself does not do anything directly; it only outputs text [00:16:55].
- Implementation: This involves defining the tool for the LLM (e.g., a “weather tool” with a specific name like
get_weather) and specifying parameters (e.g.,location) [00:17:43], [00:18:11]. The system then defines what actions happen when the AI “calls” that function, typically by fetching a route that contains the logic for that function [00:19:27].
Tips for Developers Using AI in App Development
- Focus on the “Cool Stuff”: With tools handling the underlying AI complexity, developers can concentrate on configuring personality and behavior [00:02:11], [00:11:38].
- Leverage Documentation and LLMs: It’s crucial to develop the habit of reading documentation [00:15:32]. If something isn’t understood, consult LLMs like ChatGPT or Claude [00:15:42].
- Small, Understandable Changes: When starting out, build off existing demos or repositories and make small, incremental changes. This helps in understanding how different components integrate [00:27:28], [00:28:03].
- Design for Virality: When creating characters, consider adding constraints and unique elements (e.g., “whimsical singing rainbows” for weather) that could create “TikTok moments” and generate free distribution [00:23:01], [00:23:26].
Examples of AI Apps
Weatherman Character App
A fully working weatherman character app was built as a demonstration, capable of providing weather reports, even whimsical ones like “whimsical singing rainbows” or “flying pigs” [00:00:21], [00:21:13], [00:26:02]. This showcases the ease of integrating function calling to fetch external data and have the AI narrate it [00:09:44].
Vtuber FaceTime App (Moji)
An example of a more advanced application is Moji, an app allowing users to have a personal “FaceTime” call with an AI-powered Vtuber [00:32:42]. This app utilizes Daily’s Pip Cat library for greater developer control [00:34:46]. Such applications leverage AI to create highly retentive and engaging consumer experiences [00:14:14].
The development of these applications, once requiring large teams and venture capital, can now be achieved by individuals due to advancements in AI tools [00:37:01].