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November 20, 2024

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1,174 potpie.ai

Overview

Potpie is an AI-driven tool designed to create task-oriented custom agents for your codebase, enabling high precision performance on a range of engineering tasks.

The tool leverages the context from your data and can be used for various use-cases, including system design, debugging, integration testing, and onboarding.

It allows building custom agents using simple prompts tailored to your codebase for seamless task execution. The agents demonstrate a context-driven approach, offering a high degree of precision in their operations.

This tool incorporates an easy chat interface as well as features agents that can learn a specific skill to perform given engineering tasks. Potpie turns your codebase into a detailed knowledge graph, which fuels each agent's decision-making process.

These agents have the capability to understand when to use which tool to achieve the desired goal, providing an autonomous, streamlined, and effortless integration within your workflow.

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Initial release

November 20, 2024

Aditi Kothari

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Initial release of Potpie.

Aditi Kothari

@aditikothari-1

CEO at Potpie AI

potpie.ai

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Pros and Cons

Pros

Task-oriented custom agents

High precision performance

Multiple use-cases

Simple prompts for customization

Context-driven operation

Chat interface

Skill learning capability

Detailed knowledge graph

Context-dependent decision making

Seamless workflow integration

Quick agent creation

Personalized codebase management

Advanced debugging support

Integration testing functions

Effective onboarding methods

Custom agent for every use-case

Autonomous learning

Task execution efficiency

Effortless regeneration of agents

Autonomous tool selection

Codebase turns to knowledge graph

Precise operations

Debugging with knowledge graph

Coachable agents

One-to-one codebase Q&A

Generates integration test plans

Multiple language support

Custom agents creation

Open source version available

Affordable pricing plans

Agents inheriting intelligence from code

High precision in operations

Agents can be shared

Automate tedious tasks

Pair programming assistant

Generates test suites

Skilled at multiple engineering use-cases

Code retrieval

Node neighbor analysis

Tag-based Retrieval

Code analysis tools

Pre-built agents available

Trustworthy solution for engineers

Language agnostic

Supports big data

Interactive application

Perfect for developers

View 42 more pros

Cons

Limited language optimization

Dependence on codebase knowledge

Not fully autonomous

Requires setup for prompts

Hosted version costs

No data handling assurance

Agent sharing unspecified

Learning curve for new users

Limited pre-built agents

Unclear support system

View 5 more cons

Q&A

What is Potpie?

Potpie is an AI-driven tool that enables the creation of custom, task-oriented agents for codebases. These agents can perform a variety of engineering tasks with high precision, powered by the context derived from the user's data. Potpie is instrumental in different use-cases like system design, debugging, integration testing and onboarding, making it a versatile tool for codebase management.

What are the key features of Potpie?

Key features of Potpie include the creation of AI agents for your codebase, tailored to perform specific engineering tasks. It has a workflow integration, autonomous learning capabilities, a chat interface, and uses a detailed knowledge graph built on your codebase to guide the decision-making process of the agents. Potpie can be used for system design, debugging, onboarding and integration testing.

How easy is it to setup and use Potpie?

Potpie is designed for easy setup and use. Custom agents can be built using simplified prompts that are specifically tailored to your codebase. The platform also features an easy-to-use chat interface, allowing for seamless interaction while task execution.

What tasks can Potpie custom agents perform?

Potpie’s custom agents are versatile and can perform a wide range of engineering tasks. These tasks include system design, debugging, integration testing, onboarding, and code reviews. They can also respond to specific prompts, effectively making them expert problem solvers for your codebase.

Can Potpie agents be tailored specifically to my codebase?

Absolutely, Potpie’s agents can be tailored according to the specifics of your codebase. By using simple prompts, you are able to set up custom agents that are capable of conducting high-precision operations related to your data.

How does the knowledge graph feature in Potpie work and what data does it use?

Potpie uses a knowledge graph, which is a detailed image of your codebase, to fuel the decision-making process of each of its agents. The knowledge graph provides agents with valuable context, coaching them on how to use various tools in the codebase to achieve desired goals. This context-driven approach enhances the precision of their operations.

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What kind of skills can Potpie agents learn?

Potpie's agents are capable of learning specific skills needed to perform given engineering tasks. This skill-based learning is driven by the in-depth context provided by the tool, using resources such as the codebase and documentation, to build an intelligence layer.

How does Potpie integrate into existing workflows?

Potpie maintains a seamless integration within your current workflow. The AI agents built through Potpie understand when to use which tool for achieving the set goal, making the whole process autonomous, streamlined, and effortless.

How does Potpie aid in system design and testing?

Regarding system design and testing, Potpie proves to be quite useful. Its agents are exceptionally competent in generating integration test plans and test code for code snippets derived from the knowledge graph based on given function names of entry points.

Can Potpie assist with the onboarding process?

Potpie can efficiently aid in the onboarding process. Its codebase Q&A agent specializes in answering questions about the codebase using the knowledge graph and code analysis tools. This could aid greatly in familiarizing a new developer with the existing codebase.

How does Potpie use agents for efficient debugging?

For efficient debugging, Potpie has specialized agents that understand stacktraces and errors related to your codebase. These agents can guide developers in troubleshooting by providing directions, adding print debugging statements, and helping them get to the root of the problem iteratively.

Does Potpie come with a user-friendly chat interface?

Yes, Potpie comes with an easy chat interface. This interface helps in the process of building and using agents, making the whole interaction simplified for developers.

Can Potpie be used for codebase management and how does it achieve this?

Potpie can be used for efficient codebase management. Its agents are codebase-aware, which means they understand your codebase and transform it into a comprehensive knowledge graph. This helps them to autonomously perform different tasks while keeping an overview of the whole codebase.

What type of data does Potpie use for precision in task execution?

Potpie uses the context derived from your data for high-precision task execution. The specific details and structure of your codebase are taken into account, resulting in a more accurate performance of engineering tasks by the agents.

How do Potpie agents decide which tool to use to achieve a desired goal?

Potpie's agents decide on which tool to use based on their goal and tools available. The decision is autonomous and is fueled by a comprehensive knowledge graph created from your codebase. Each agent is coached to determine the appropriate tool to utilize in order to achieve its goal.

Does Potpie offer autonomous learning capabilities?

Yes, Potpie offers autonomous learning capabilities. Its AI agents can learn a specific skill-set to carry out given engineering tasks. This autonomous learning takes into account the context from your codebase, allowing each agent to improve their performance over time.

Are there limitations on the number and type of agents I can create with Potpie?

There are no specific limits mentioned on the number and type of agents you can create with Potpie. The platform allows you to create custom agents tailored to your particular codebase and engineering tasks. However, the performance may vary for different programming languages, with optimum performance observed for TypeScript, Python, Java, and JavaScript.

Is there a free trial for Potpie?

Potpie offers a first month free trial for all of their paid plans. During this period, you can access all the functions of the tool without needing to provide any credit card information.

How does Potpie's pricing structure work?

Potpie offers both an open-source version that can be used free of charge and a hosted version with plans starting at $20/month. More detailed information about the pricing structure can be found on the Potpie website in the pricing section.

How is my data and codebase secured while using Potpie?

When using Potpie, your data and codebase are secure. Potpie does not store any code from your codebase. Moreover, if you prefer self-hosted models, you can do so through the open-source version of Potpie.

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