25 Stellar AI Agents 💫

+ Google's (kinda annoying) release & OpenAI's free-for-all features

AI agent assistants and autonomous AI agents are rapidly gaining popularity due to their ability to solve tasks on their own.

What’s the difference?

AI agent assistants automate routine processes by making decisions based on predefined constraints and human direction, whereas autonomous AI agents set their own goals, make decisions, and take action without human input.

So whether you still want a hand on the reins or are rearing to let AI fully take the wheel, we’ve got you covered with 25 stellar options to automate your workflows.

In This Issue:
  • 💥 Big News: Google’s (arguably annoying) new release, OpenAI’s new + free-for-all features, & 3 more

  • 🔥 Hot Tools: 25 AI agent assistants & autonomous AI agents

  • 💫 Helpful Guide: 10 tips for integrating AI agents into your business

  • 💡 Quick Tutorial: Build your own AI agent using GitHub repositories

💥 Big News

AI Updates From Big Tech

Google is rolling out AI Overviews, which shows AI-generated summaries above search results (here’s how to turn it off) + will introduce its first ‘AI-for-everything’ agent, Astra, later this year.

OpenAI made its custom GPT store & custom bot creation free for everyone, removed its AI assistant’s Scarlett Johansson-esque voice, improved data analysis capabilities — including interactive charts & the ability to import files directly from Google Drive & OneDrive into ChatGPT.

Microsoft is testing Places, an AI-powered Microsoft 365 app that helps businesses coordinate in-office time.

Gannett, the U.S. newspaper publisher that owns USA Today, introduced AI-generate bulleted takeaways to articles.

Oracle introduced new features that enhance database performance, accelerate vector search, & improve security, scalability, & more.

Big tech launched 96 AI products & features in the last week. See summaries here.

🔥 Hot Tools 

14 Powerful AI Agent Assistants

Tely: Optimize & automate your B2B content marketing**

Dart: Save 7 hours per week on project management overhead**

Plumb: Quickly build, test, & deploy AI features with confidence**

Cassidy: Build AI automations & assistants trained on your business

echowin: Optimize call handling & customer interactions

Fine (freemium): Accelerate pull request resolution & enhance code quality

MultiOn: Get assistance with daily tasks like planning gatherings, booking flights, & more

Bardeen (freemium): Automate repetitive manual tasks

Norm Ai: Ensure your business meets regulatory compliance

Tulsk.io: Optimize project management with modular AI agents for email, content, project planning, & more

Pythagora: Build apps in hours, not months

Kusho: Never test your APIs manually again

Aiga: Easily integrate agents for every department into your existing systems

Sonara: Take the work out of finding a job

11 Dynamic Autonomous AI Agents

Composio (freemium): Make agents actually useful. Let them interact across 100s of apps.

Kompas AI: Boost team-wide productivity by streamlining HR processes, data analysis, & more

AgentGPT (freemium): Automate business processes, web scraping, & app creation

Attri: Leverage 20+ pre-built, multi-agent solutions or create your own

Cognosys (freemium): Simplify business workflows via seamless app communication & actionable insights

D-iD: Elevate customer experiences, your website, online courses, & more with interactive agents

Taskade (freemium): Boost team productivity with intelligent project management assistance (Check out this tutorial)

MindPal: Tackle complex tasks with multi-agent workflows

Spell: Work smarter & do more with a curated prompt & template library

Nexus (freemium): Easily build versatile agents using a marketplace of 1,500+ tools

Humans: Leverage AI & blockchain to create highly empathetic & ethical agents for diverse applications & sectors


💫 Helpful Guide

10 Tips For Integrating AI Agents Into Your Business

1) Identify clear business goals that you want the agent to address (e.g., automate repetitive tasks, expand to new markets, optimize logistics, or improve customer service).

TIP: See how AI agents help with project management, supply chains, accounting, HR, & more here.

2) Consider that impact on all stakeholders (e.g., employees, customers, and investors) — seeking diverse perspectives to identify needs, desired impacts, and potential pushbacks or issues.

3) Determine KPIs for how you’ll measure the agent’s success (e.g., accuracy, speed, user satisfaction scores, or ROI). For instance, a customer service AI assistant might be evaluated for response accuracy and customer satisfaction, while a predictive analytics agent might be assessed based on the precision and recall of its forecasts.

4) Thoughtfully choose which agent to implement, considering if it:

  • Is helpful for your chosen goal

  • Integrates well with your current & projected tech ecosystem

  • Ensures security (e.g., transparent data usage policies + compliance with international standards & industry-specific regulations)

  • Operates ethically (TIPS: Evaluate the provider’s commitment to ethical practices, review documentation for transparency in how it operates & makes decisions, assess how it mitigates bias, & ensure that there’s a way to audit & correct its decisions.)

5) Ensure the data fed into the agent is accurate, comprehensive, and clean, so that you get accurate outputs and recommendations.

6) Gradually introduce the agent into your processes to minimize disruption — only scaling up and integrating it more extensively once it’s proven to be helpful.

7) Train your team on how to leverage the agent effectively to increase the likelihood of successful outcomes.

8) Continuously monitor the agent’s performance to ensure that it’s meeting intended goals, measuring your pre-determined KPIs as well as collecting and analyzing feedback (e.g., surveys or user behavior analysis) from employees and/or customers.

9) Make any necessary adjustments based on its performance (e.g., retraining it with additional data or altering interaction designs).

10) Stay informed about AI advancements, and consider whether you want to adjust current workflows, implement new tools, or augment additional business processes.

💡 Quick Tutorial

Build Your Own AI Agent Using GitHub Repositories

Creating a robust and reliable AI agent can be a complex endeavor. Use Github repositories to get started. Here’s how.

Step 1: Choose an AI agent framework (see popular options below), which provides a base structure for creating your agent.

Step 2: Clone the repository to your GitHub account or local computer.

Step 3: Customize the agent by modifying the codebase to tailor the agent’s behavior, capabilities, and knowledge base to your needs. This may involve adjusting configuration files, modifying the agent’s logic, integrating APIs, & more.

Step 4: Integrate the appropriate AI models into your agent’s codebase by setting up API keys, configuring parameters, and handling model inputs & outputs.

Step 5: Define tasks & goals (e.g., natural language processing, data analysis, etc.) then, depending on your chosen framework & requirements, provide training data, implementing reinforcement learning algorithms, etc.

Step 6: Test & iterate to ensure your model behaves as expected.

Step 7: Deploy it into a production environment, which may involve setting up servers, cloud deployment, or containerization.

Once your AI agent performs as expected, consider contributing your changes back to GitHub to help the community!

9 Popular AI Agent GitHub Repositories

  • AutoGPT: Python-based agent that uses LLMs to browse the internet, interact with computer programs, + dynamically write & improve its own code

  • SuperAGI: Orchestrates role-playing AI agents to foster collaborative intelligence

  • BabyAGI: A constitutional AI that follows a specific set of rules & principles

  • AgentGPT: A code-first agent Python-based framework for seamlessly planning & executing data analytics tasks

  • Teenage AGI: A self-modifying AI framework claiming to be the world’s first Artificial Mind System

  • GPT Researcher: Designed for comprehensive online research on a variety of tasks

  • Private GPT: Interact privately with your documents using the power of GPT 100% privately

  • MicroGPT: A lightweight, general-purpose agent

  • CrewAI: Optimize complex workflows with multi-agent AI automations

In-Depth Tutorials