import asyncio
from typing import List, Dict
from ai_agent import Agent, DebateTopic

class DevelopmentAIAgents:
    """Simulates AI agents collaborating on a coding task."""
    
    def __init__(self, agents: List[Agent]):
        self.agents = agents
        self.debate_history = []
    
    async def debate_tabs_vs_spaces(self) -> Dict:
        """The classic developer debate handled by AI."""
        topic = DebateTopic(
            title="Tabs vs Spaces",
            description="Indentation preference for code readability"
        )
        
        arguments = []
        for agent in self.agents:
            # Each AI agent generates its argument
            argument = await agent.generate_argument(topic)
            arguments.append({
                "agent": agent.name,
                "position": argument.position,
                "reasoning": argument.reasoning
            })
            
            # Log the debate
            self.debate_history.append({
                "topic": topic.title,
                "argument": argument.position,
                "agent": agent.name
            })
        
        return {
            "topic": topic.title,
            "arguments": arguments,
            "consensus": "No consensus reached - infinite loop likely"
        }
    
    async def generate_code(self, requirement: str) -> str:
        """Multiple AI agents attempt to write code together."""
        tasks = [agent.write_code(requirement) for agent in self.agents]
        code_attempts = await asyncio.gather(*tasks)
        
        # Return the most coherent attempt (or the first one)
        return code_attempts[0] if code_attempts else "# AI agents are still thinking..."

# Usage example:
# agents = [Agent("CoderBot"), Agent("StyleMaster"), Agent("EfficiencyAI")]
# dev_team = DevelopmentAIAgents(agents)
# result = asyncio.run(dev_team.debate_tabs_vs_spaces())

The GitHub Star Factory: Manufacturing Hype at Scale

Let's address the 65,919-pound elephant in the room. How does a repository with a name like a yoga pose and a description shorter than a VC's attention span get nearly 66k stars? It's the modern tech equivalent of a viral dance trend. The recipe is simple: 1) Put "AI" in the title, 2) Use emojis (🙌), 3) Promise "Development." Bake at 350 degrees of hype for 24 hours. Voilà! You're trending.

What Does "AI-Driven Development" Even Mean?

It means instead of one developer staring blankly at a terminal, you'll have multiple AI agents staring blankly at a virtual terminal. They'll collaborate! They'll debate! They'll generate thousands of lines of code that do... something. The promise is that these AI agents will handle the entire software development lifecycle. In reality, they'll probably get stuck in an infinite loop arguing about whether to use tabs or spaces, a theological debate they inherited from us.

It's the classic tech pivot: when your product doesn't have a clear use case, just say it's "AI-driven" and "agent-based." Suddenly, writing a script that automates a single task becomes a "multi-agent orchestration framework." It's not a bug; it's a feature.

The Inevitable Workflow

Imagine the future: You prompt OpenHands to "build a social media app." The AI agents spring into action. Agent 1 writes a login API. Agent 2, not to be outdone, writes a different login API. Agent 3, the project manager AI, schedules a meeting for them to reconcile their differences. Agent 4, the QA bot, finds 147 critical bugs and files them in a system that no other agent checks. By the end of the day, you have a repository filled with conflicting code, meeting notes, and JIRA tickets. Progress!

You'll spend more time managing your AI's interpersonal conflicts than you ever did debugging your own code. But hey, at least you can tell your boss you're leveraging a cutting-edge, multi-agent AI development paradigm. That's got to be worth a promotion, or at least a few extra likes on LinkedIn.