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What is workshop-demo?

future-agi/workshop-demo — explained in plain English

Analysis updated 2026-07-30 · repo last pushed 2026-04-10

1PythonAudience · developerComplexity · 3/5MaintainedSetup · moderate

In one sentence

A hands-on workshop demo showing how to improve AI assistants using FutureAGI. It compares basic chatbots against versions refined through automated testing and prompt optimization.

Mindmap

mindmap
  root((repo))
    What it does
      Tests and evaluates AI
      Optimizes AI prompts
      Compares basic vs improved
    Example assistants
      Simple chatbot
      Bike rental bot
      Voice hotel receptionist
    Tech stack
      Python
      FutureAGI platform
      OpenAI Anthropic Groq
    Use cases
      Fix chatbot misunderstandings
      Simulate conversations
      Auto-rewrite instructions
    Audience
      Workshop attendees
      Technical founders
      Developers

Code map

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What do people build with it?

USE CASE 1

Build a bike rental chatbot and automatically fix booking date misunderstandings.

USE CASE 2

Run simulated conversations to find where your AI assistant fails.

USE CASE 3

Compare a basic chatbot against one with automatically optimized prompts.

USE CASE 4

Switch between OpenAI, Anthropic, and Groq models by changing one setting.

What is it built with?

PythonFutureAGIOpenAIAnthropicGroq

How does it compare?

future-agi/workshop-demo0xallam/posthog0xustaz/streamgate
Stars111
LanguagePythonPythonPython
Last pushed2026-04-102026-03-26
MaintenanceMaintainedMaintained
Setup difficultymoderatemoderatehard
Complexity3/53/54/5
Audiencedeveloperpm founderdeveloper

Figures from each repo's GitHub metadata at analysis time.

How do you get it running?

Difficulty · moderate Time to first run · 30min

Requires an API key from OpenAI, Anthropic, or Groq configured in an environment file, plus a FutureAGI account for the optimization features.

So what is it?

This project is a hands-on demo for a Future AGI workshop. It shows how to take a basic AI assistant and make it smarter using a platform called FutureAGI, which helps you test, evaluate, and improve your AI's underlying instructions. The repo walks through three example assistants: a simple chatbot, a bike rental assistant that can book bikes, and a voice-based hotel receptionist. Each of the three assistants has two versions. The first is a basic version with a prompt that is intentionally just "good but not great." The second version connects to FutureAGI to run simulations, evaluate the AI's responses, and automatically optimize the prompt. This setup lets you directly compare a standard AI assistant against one that has been refined through automated testing and improvement. The audience for this project is developers or technical founders attending a Future AGI workshop who want to learn how to systematically improve their AI agents. For example, if you built a bike rental chatbot and customers complain it misunderstands booking dates, this project demonstrates how to simulate conversations, evaluate where the bot fails, and automatically rewrite its instructions to fix those issues. A notable aspect of the project is that it is designed to work with multiple AI providers. You can use models from OpenAI, Anthropic, or Groq by simply changing a setting in an environment file. The README does not go into detail on exactly how the three different optimizers (MetaPrompt, ProTeGi, and GEPA) work, but it makes clear that each of the three assistants relies on a distinct optimization method provided by FutureAGI.

Copy-paste prompts

Prompt 1
Set up this workshop demo repo locally and configure the environment file to use OpenAI as the AI provider. Run the basic bike rental assistant and then the FutureAGI-optimized version.
Prompt 2
Using the FutureAGI integration shown in this repo, simulate conversations for the voice hotel receptionist assistant and evaluate where it fails at understanding guest requests.
Prompt 3
Compare the three prompt optimization methods MetaPrompt, ProTeGi, and GEPA used across the three example assistants in this repo. Explain which assistant uses which optimizer and why.
Prompt 4
Take the basic chatbot example from this repo and connect it to FutureAGI to run automated simulations that evaluate and rewrite the prompt for better responses.

Frequently asked questions

What is workshop-demo?

A hands-on workshop demo showing how to improve AI assistants using FutureAGI. It compares basic chatbots against versions refined through automated testing and prompt optimization.

What language is workshop-demo written in?

Mainly Python. The stack also includes Python, FutureAGI, OpenAI.

Is workshop-demo actively maintained?

Maintained — commit in last 6 months (last push 2026-04-10).

How hard is workshop-demo to set up?

Setup difficulty is rated moderate, with roughly 30min to a first successful run.

Who is workshop-demo for?

Mainly developer.

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