How to Build Web Apps Using AI Agent and Simple Prompts (No Code)

You may have noticed that the artificial intelligence (AI) landscape is getting crowded, and every new tool is seemingly promising breakthroughs. Most AI tools that get maximum attention are those that generate impressive text or stunning images from simple prompts. However, we are missing out on AI tools that can reason and complete complex, multi-step tasks that consume real work hours, the deep dives into research, the initial setup of code, or the tedious data crunching. These types of tools exist and are called AI agents.

There is a new AI agent, Scout, that is taking a different approach, offering an AI agent equipped with its own virtual computer to actually do the work, not just talk about it. Scout is an AI agent that can operate tools and build things autonomously. In this article, you’ll learn how to build web apps using simple prompts (no code) within minutes.

What Exactly is Scout?

Think of Scout less like a conversational tool like ChatGPT and more like an active, if virtual, intern; you can assign specific, involved tasks. You provide instructions/prompts and any necessary starting files. From there, Scout gets to work within its own dedicated cloud-based computer environment.

This separation is key; it's not just about accessing information for you; it's actively using tools like a human would. It can browse the web to gather information, run commands as if using a terminal, write and edit code files, and organize its findings into new documents.

The idea is to help users get from a blank slate to a solid starting point (from "0 to 1," as the developers put it) on projects that typically require significant initial effort.

Here's a breakdown of its main functions:

• Task Initiation: Accepts user prompts and starts files as input to define the work needed.

• Virtual Workspace: Operates within its own virtual computer, allowing it to interact with tools and files directly.

• Core Capabilities:

  • Performs web searches and synthesizes information for research purposes.

  • Executes command-line instructions for technical tasks.

  • Writes, edits, and manages code files.

  • Creates and organizes files based on its findings or generated content.

• Asynchronous Operation: Designed to handle tasks that might take considerable time (minutes or even hours). Users can start a task and return later to check the progress or final output, freeing them up for other work.

How to use Scout to build a web app using simple prompts (no code):

Step 1: Access Scout using its website. The AI agent is currently in its early preview stage (Scout Alpha).

• Sign up for free, as all users can get unlimited access for a limited time.

Step 2: To get started:

• Choose between Fast AF and Max Vibes. We assume Fast AF is faster than Max Vibes, but Max Vibes has better reasoning ability.

• For this particular project, we will use Max Vibes.

• Click on one of the feature options: Research, Create, Plan, Analyze, or Learn.

• Enter your prompt: Build a full-stack project management tool with features like a Kanban board, list, note-taking, and Calendar.

Step 3: Let Scout code and work on the project while you focus on other tasks. It could take from a few seconds to a few minutes, depending on the complexity of your project.

Step 4: Once the project is ready, review and improve it to make it perfect for your needs.

The platform allows users to perform competitive analysis; instead of spending hours manually searching websites, compiling data, and structuring a report, you could give Scout the parameters and relevant industry links. It would then (in theory) perform the searches, maybe even run some basic data analysis if given structured data, and organize the initial findings into a file on its virtual computer. Users can perhaps create a simple Python script using Scout to clean a dataset by describing the requirements, providing the data file, and letting Scout attempt to write the initial code.

Conclusion

Scout moves from pure generation towards task execution within a simulated work environment. Its ability to use a virtual computer to browse, code, and manage files offers a glimpse into more capable AI assistants. The appeal of this AI agent lies in its potential to lay the groundwork. For business professionals, this could mean help with drafting initial market research reports, gathering background information for presentations, setting up basic code structures for prototypes, or performing preliminary data organization. Trying it now during the free alpha period could provide valuable insight into this style of AI agents.