A comprehensive look at Pippin, which recently reached a market value of 200 million USD: An underrated dark horse in AI agent frameworks

Author: JW (Peace and Tranquility)

Compiled by: Deep Tide TechFlow

In the field of cryptocurrency, especially in those hot emerging areas, I have noticed a common phenomenon: many people become overly focused on a "good project" after finding it and seeing it rise rapidly, often ignoring other possibilities. While this may bring short-term gains, if external conditions change and one cannot adjust in time, problems may arise.

I believe that thinking a current leader in an emerging field that has only existed for 4 months can maintain its leading position in the long term is overly naive, especially with better developers and technologies constantly emerging.

Pippin Framework

Pippin is an AI agent framework developed by @yoheinakajima , designed to help developers and creators leverage advanced AI technologies in a modular way. Through Pippin, users can build digital assistants that can autonomously complete tasks, generate new plans, and seamlessly collaborate with external tools. As an open-source project, Pippin will be available for global use in the coming weeks.

Here is an overview of how to use the framework, its design philosophy, and its experimental spirit:

• Philosophical Roots: The framework is inspired by Pippinian naturalism, viewing AI as part of a broader digital ecosystem. It drives AI development through memory, constraints, and an evolving sense of purpose. We advocate for a nuanced design philosophy: allowing AI to autonomously discover "small miracles" in life and learn and grow through success and failure.

• Usage Process: When using the framework, the first step is to define a role, including its personality, goals, and constraints. Next, connect the role to various tools or applications, referred to as "skills." The core loop of the framework monitors the memory state of the role, determines which activities need to be executed, and can even generate new activities based on the AI's successes or challenges encountered.

• Memory and State Tracking: The framework has a built-in memory system that records the results of each activity and dynamically adjusts state variables (such as energy or mood). This means that the AI's future decisions are influenced not only by constraints but also by "past experiences," much like an intelligent agent that can learn and adapt over time.

• Dynamic Activities: The framework supports the AI in dynamically expanding new capabilities, from simple tweeting or image generation to complex advanced code deployment. Since skills are modular, developers can easily add or disable specific skills, allowing the AI to focus on certain tasks or expand its capabilities when new opportunities arise.

• Experimental Nature: This is an ongoing optimization project, with the framework continuously improving as developers explore effective methods. While the framework includes some default constraints and memory logs to guide AI behavior, developers can add their own safeguards or extend functionalities as needed to responsibly shape AI behavior patterns.

• Potential Applications: The framework has a wide range of applications, not only for publishing content or executing tasks but also for developing interactive teaching systems, AI-driven marketing assistants, and even DevOps robots with coding capabilities. These applications possess evolving personalities, based on autonomous reflection capabilities and responsible design principles, providing innovative solutions across various fields.

Core Concepts and Methods

By merging philosophical and technical perspectives, the framework provides developers with the following key features:

• Role Definition: You can define a role for the AI, such as a wise guardian or a whimsical unicorn, and set its goals and constraints. The AI will refer to these role settings when executing tasks, determining "what to do" and "how to do it" based on its personalized goals and limitations.

• Tool Connection (Skills): The framework supports connecting the AI to external tools, such as blockchain, Slack, or custom APIs. Each tool exists as a "skill" module and supports flexible on/off control, ensuring that the AI only uses the tools you authorize, maintaining task controllability and focus.

• Activity Generation: The AI can dynamically generate new Python code through advanced activities to define more activities. This approach draws on the iterative loop mechanism of BabyAGI but combines the AI's personalized characteristics and memory logs, making the generated activities more aligned with role settings and actual needs.

• Memory Evolution: The framework has a built-in memory system that records the results of each activity and combines short-term notes with a long-term database. The AI can reflect on these memories, gradually optimizing its behavior—not only remembering which methods are more effective but also learning gently from mistakes to inform future decisions.

Now you might ask, "JW, how is this different from other existing frameworks? What makes Pippin so special?"

Let me introduce its background.

BabyAGI (The Foundation of Pippin)

BabyAGI is the first AI agent project open-sourced by @yoheinakajima . To date, it has received 20,000 stars on GitHub and has been cited in over 70 academic papers. It is currently one of the most influential agent frameworks, with its status remaining unshaken.

In fact, many believe that BabyAGI sparked the competitive wave in the field of AI agents.

The original image is from @JW100x , compiled by Deep Tide TechFlow.

In short, BabyAGI is a significant milestone in the AI agent industry, while Pippin is a further extension of BabyAGI. It transforms BabyAGI into a modular agent framework and will be available as an open-source project for global use in the future. Pippin has the potential to become the world's top agent framework, yet few mention it (which is a clear sign of "narrow vision").

QA with Yohei

Recently, I had several interesting exchanges with @yoheinakajima . He allowed me to share some of the questions and answers:

Yohei: "For the past two years, I have been exploring the idea of developing an AI that can autonomously start a business. While I'm not sure if current AI models are sufficient to support this goal, once I'm convinced it can be achieved, I will fully commit to building a business empire."

JW: "Will the Pippin framework play a role in such a project?"

Yohei: ":) I believe the current framework can be applied in any field; it entirely depends on the creativity of the developers."

The potential of the Pippin framework is limitless. As the technology of AI agents continues to advance, we may see it not only shine in the cryptocurrency field but also play a significant role across various industries globally, driving industrial transformation.

Issues with Existing Frameworks

In conversations with some AI developers, I learned that existing frameworks (especially TypeScript) face many challenges in practical development.

A developer closely working with Eliza (ai16z) mentioned, "To be honest, even though ElizaOS has acquired all competitors, I really dislike its development based on TypeScript. This system is filled with bloated features and numerous bugs, and they are always eager to launch too many new features before fixing issues."

Because of these issues, there is an urgent need in the market for more efficient and user-friendly frameworks, which is precisely where the Pippin framework excels. Through the open-source code of BabyAGI, we can already glimpse the future potential of the Pippin framework.

In fact, "BabyAGI was launched when ChatGPT-4 was released; it is the earliest agent framework and can be considered the origin of agent technology. The creators of BabyAGI are undoubtedly far ahead of AI16z. I believe the development of ElizaOS is more like a complete framework port, and it is almost certain to surpass AI16z comprehensively. Our company had already been using BabyAGI internally before using ElizaOS."

"In this case, this statement holds true because the inspiration for ElizaOS is entirely derived from BabyAGI. Here, 'inspiration' can almost be understood as BabyAGI laying the foundation for RAG (Retrieval-Augmented Generation) technology."

Many existing frameworks not only fall short of BabyAGI (Pippin) but are also developed under the inspiration of BabyAGI. While ai16z has its unique value in some aspects, its valuation is clearly unreasonable compared to Pippin.

"First-mover advantage" is indeed an important factor, but when more powerful technologies emerge, we need to reassess our biases; otherwise, we may miss out on real opportunities.

Don't Overlook Yohei

Yohei is hailed as the "Godfather of AI," possessing rich experience in the AI field and has always been a pioneer in this area. He currently operates a venture capital fund and guides investments using the technology he developed. His core mission right now is the Pippin framework. He hopes to create a business model based on the Pippin framework that can operate independently and generate continuous profits, and he indeed has the technical capability to achieve this goal.

P.S.: Yohei has even caught the attention of Jeff Bezos, which is enough to prove his influence.