diff --git a/DOCS/Corp/DEMO_IDEAS.md b/DOCS/Corp/DEMO_IDEAS.md
index d4cc1a0b..e1a27f51 100644
--- a/DOCS/Corp/DEMO_IDEAS.md
+++ b/DOCS/Corp/DEMO_IDEAS.md
@@ -3,3 +3,5 @@
 * We could also try to create an AI influencer run by a swarm, let it create a whole identity and generate images, memes, and other content for Twitter, Reddit, etc.
 
 * had a thought that we should have either a more general one of these or a swarm or both -- need something connecting all the calendars, events, and initiatives of all the AI communities, langchain, laion, eluther, lesswrong, gato, rob miles, chatgpt hackers, etc etc
+
+* Swarm of AI influencers to spread marketing
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diff --git a/DOCS/ideas/aug13.md b/DOCS/ideas/aug13.md
new file mode 100644
index 00000000..e14c36da
--- /dev/null
+++ b/DOCS/ideas/aug13.md
@@ -0,0 +1,78 @@
+## **Product Feature Document: Multi-Agent Distributed Collaboration Framework**
+
+---
+
+**Introduction**:  
+In a world increasingly leaning towards automation, we present a framework to enable multi-agent distributed collaboration. This revolutionary approach, integrating millions of GPT-3 nodes, is set to redefine real-world task automation. This document outlines and prioritizes features based on their potential value to early adopters.
+
+---
+
+### **1. Learning Enhancements**
+
+- **Private Learning**: Safeguard data and learn without transmitting sensitive information.  
+  *Value Proposition*: Guarantees data security for enterprises dealing with sensitive information.
+  
+- **Task Decomposition**: Algorithms to efficiently break down complex tasks into simpler sub-tasks for agent distribution.  
+  *Value Proposition*: Simplifies problem-solving and ensures efficient task distribution among agents.
+
+---
+
+### **2. Swarm Management & Performance**
+
+- **Swarm Benchmarks**: Establish performance benchmarks for swarms, providing users with expected efficiency and accuracy metrics.  
+  *Value Proposition*: Allows users to anticipate swarm performance and adjust strategies accordingly.
+
+- **Swarm Classes & Modularity**: Create diverse classes of swarms based on task type, ensuring a high level of usability and flexibility.  
+  *Value Proposition*: Customizable swarms tailored to specific problem sets, enhancing solution accuracy.
+
+- **Dictator Swarm Mode**: Centralized control for swarms for tasks that require uniformity and synchronization.  
+  *Value Proposition*: Streamlines processes where coordination is key.
+
+---
+
+### **3. Communication & Progress Tracking**
+
+- **Progress Posting Tool**: Equip agents with a tool to post their progress to a swarm-wide vector store.  
+  *Value Proposition*: Real-time tracking of task progress and agent efficiency.
+
+- **Observer Agent**: A supervisory agent dedicated to preventing others from entering non-productive loops.  
+  *Value Proposition*: Ensures optimal agent performance and minimizes wastage of computational resources.
+
+---
+
+### **4. Tool Integration & Modularity**
+
+- **Easy Tool Integration**: Simplified interfaces to add or modify tools within the swarm.  
+  *Value Proposition*: Augment swarm capabilities on-the-go, adapting to diverse tasks with ease.
+
+- **Vector Database for Tools**: Maintain a comprehensive database of tools, allowing agents to query and utilize as needed.  
+  *Value Proposition*: Provides agents with a vast arsenal of tools to tackle various challenges, enhancing problem-solving capacity.
+
+---
+
+### **5. Data Input & Multimodality**
+
+- **Multimodal Data Intake**: Enable swarms to process varied data types – text, images, sounds, and more.  
+  *Value Proposition*: Broadens the range of tasks swarms can handle, from simple text-based queries to complex multimedia projects.
+
+---
+
+### **Feature Priority (for early adopters)**:
+
+1. **Private Learning**: Data privacy remains paramount.
+2. **Task Decomposition**: Efficient problem-solving is foundational.
+3. **Swarm Benchmarks**: Understanding potential performance is essential for user trust.
+4. **Progress Posting Tool**: Real-time updates increase confidence and allow for timely interventions.
+5. **Multimodal Data Intake**: Increases the range and depth of tasks the framework can handle.
+6. **Observer Agent**: Minimizing wastage is key to cost efficiency.
+7. **Easy Tool Integration**: Enhancing adaptability for varied challenges.
+8. **Swarm Classes & Modularity**: Customization ensures relevance to specific user needs.
+9. **Dictator Swarm Mode**: Essential for tasks demanding synchronization.
+10. **Vector Database for Tools**: Augments the swarms' problem-solving arsenal.
+
+---
+
+**Conclusion**:  
+With these prioritized features, our framework promises not only to revolutionize task automation but also to deliver unmatched value to its earliest users. This is the dawn of a new era in AI collaboration, and we invite you to be a part of this journey.
+
+**Join the future of AI automation. Step into the swarm.**
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diff --git a/swarms/swarms/base.py b/swarms/swarms/base.py
new file mode 100644
index 00000000..8630baae
--- /dev/null
+++ b/swarms/swarms/base.py
@@ -0,0 +1,24 @@
+from abc import ABC, abstractmethod
+
+class AbstractSwarm(ABC):
+
+    def __init__(self, agents, vectorstore, tools):
+        self.agents = agents
+        self.vectorstore = vectorstore
+        self.tools = tools
+
+    @abstractmethod
+    def initialize(self):
+        pass
+
+    @abstractmethod
+    def communicate(self):
+        pass
+
+    @abstractmethod
+    def process(self):
+        pass
+
+    @abstractmethod
+    def solve(self):
+        pass
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