Microsoft just dropped an open-source agent framework.
OpenAI fired back with Agent Kit at DevDay.
This is the biggest AI battle of 2025.
I’m going to show you both platforms live in this comparison.
Real demos with actual code.
Which one wins for your use case.
By the end, you’ll know exactly which one to use.
I’m saving you weeks of research.
Watch the video tutorial below.
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Understanding AI Agents
What even is an AI agent?
An agent is basically an LLM with superpowers.
It’s not just answering questions.
It can take actions.
It can use tools.
It has memory.
ChatGPT answers your question.
An agent books your meeting, sends the email, and updates your calendar.
That’s the difference.
The Two Different Philosophies
Microsoft’s agent framework is open source.
It’s an SDK and runtime.
Python or .NET built for multi-agent orchestration.
Multiple agents working together.
One researches, one writes, one fact checks.
It integrates with VS Code and Azure.
You host it yourself.
You control everything.
This is for developers who want power and flexibility.
OpenAI’s Agent Kit is the opposite.
Visual toolkit with drag and drop agent builder.
ChatKit for embedding agents.
Connector registry for Gmail, calendars, databases.
It’s managed, hosted, and turnkey.
This is for product teams who need to move fast without infrastructure hassle.
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Side-by-Side Comparison
Microsoft Agent Framework offers:
Open source code.
Python and .NET support.
Multi-agent orchestration.
VS Code integration.
Local or container deployment.
No vendor lock-in.
For developers who want control.
OpenAI Agent Kit offers:
Visual builder interface.
Drag and drop functionality.
ChatKit embedding.
Pre-built connectors.
Hosted runtime.
ChatGPT integration.
For product teams who want speed.
Microsoft Agent Framework Technical Deep Dive
Microsoft’s framework has three main pieces.
The SDK on GitHub.
The runtime engine.
The orchestration system.
You install it with pip or NuGet.
Define agents, tools, and workflows.
The orchestration is powerful.
Sequential workflows run step by step.
Group chat where agents debate solutions.
Agentic workflows that adapt dynamically.
This is teams of agents working together.
VS Code Integration
The VS Code integration is killer.
Build, test, and debug right in your editor.
Graph visualization shows connections.
See agent connections visually.
Step through calls like debugging code.
Quick Start Example
The quick start from Microsoft Learn shows a research agent.
Clone the repo.
Install dependencies.
Write Python code.
Create agent objects.
Define tools.
It searches, reads, and summarizes content.
Chain multiple agents together.
One researches, one writes, one fact checks.
All happening locally.
No platform lock-in because it’s open source.
You customize everything.
Swap LLMs easily.
Add custom tools.
Deploy anywhere you want.
That’s the power.
But it comes with complexity.
You’re writing code and managing infrastructure.
This is not for everyone.
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OpenAI Agent Kit Technical Deep Dive
OpenAI announced Agent Kit at DevDay.
The agent builder is visual.
Drag and drop tools easily.
Configure prompts visually.
Test in real time.
Ship to production without much code.
ChatKit Feature
ChatKit is an SDK for embedding agents in your app.
Add a few lines of code.
Users get an AI agent instantly.
Connector Registry
The connector registry has Gmail.
Google Calendar connectors.
Slack integration.
Database connectors.
Just plug them in.
The idea is speed.
Product teams don’t want weeks building infrastructure.
They want to ship fast.
Example Workflow
Open agent builder.
Create new agent.
Name your agent.
Add tools from registry.
Building customer support?
Add Gmail connector so agent reads and sends emails.
Add calendar connector so it schedules meetings automatically.
Add knowledge base so it answers from your docs.
All drag and drop.
Test live immediately.
Deploy with one click.
OpenAI hosts it for you.
Embed with ChatKit.
Done.
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Security Deep Dive
Let’s talk security.
Agents are powerful but risky.
They access tools, read emails, execute code, and move data.
Massive attack surface.
First Issue: Connectors
Every tool is a vulnerability.
Agent accesses Gmail and could leak emails.
Need permissions control.
Audit logs required.
Sandboxing necessary.
Second Issue: Tool Execution
Agents call APIs.
Misconfigured API could delete data or expose secrets.
Need rate limits.
Error handling critical.
Third Issue: Data Flows
Where’s data stored?
Who accesses it?
Is it encrypted?
Microsoft’s Approach:
Microsoft gives you full control.
You host the runtime.
Configure permissions yourself.
Set up audit logs.
You’re responsible.
OpenAI’s Approach:
OpenAI offers managed security.
They handle hosting.
Built-in rate limits and logging.
But you’re trusting their platform.
Best Practices
Least privilege access for all agents.
Audit logs for every tool call.
Sandboxing environments.
Rate limits on all actions.
Both platforms support these.
But you implement them.
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Real-World Use Cases
Microsoft is perfect for:
Multi-agent pipelines where agents search, read, summarize, and generate reports.
Group chat orchestration where agents collaborate.
Enterprise automation pulling data from internal systems.
You control everything with no vendor lock-in.
OpenAI is perfect for:
Product embedded agents like SaaS app with AI assistant for users.
Rapid prototyping to test ideas fast.
Build, test, deploy in a day with no code and no infrastructure.
The Hybrid Strategy
Here’s the hybrid approach.
Use Microsoft’s framework for orchestration.
Call OpenAI models as tools.
Control of Microsoft plus power of OpenAI’s LLMs.
Define agents in Python.
Use orchestration features.
LLM backend is GPT-4.
Best of both worlds.
That’s what I’d recommend for serious projects.
Decision Framework
Choose Microsoft if:
You need open-source control.
You want multi-agent orchestration.
You need full customization.
You’re okay managing infrastructure.
You’re building complex enterprise automation.
You want no vendor lock-in.
Choose OpenAI if:
You need product velocity.
You want managed connectors.
You want to prototype fast.
You want to ship without infrastructure.
You’re a product team.
You’re embedding agents in consumer app.
Both are powerful with different use cases.
Why This Battle Defines the Future
This battle matters.
Agents are the next wave.
Moving from chat to autonomous systems.
Agents do work for you, automate tasks, and make decisions.
Whoever wins controls the developer ecosystem.
Microsoft bets on open source and control.
OpenAI bets on managed platforms and speed.
Both will succeed.
There’s room for both.
But pick the right tool for your needs.
Getting Started Resources
Microsoft’s agent framework is on GitHub.
Docs on Microsoft Learn.
Quick start samples use Azure.
OpenAI’s Agent Kit announcement covers:
Agent builder features.
ChatKit SDK.
Connector registry.
Security considerations.
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Frequently Asked Questions
What’s the biggest difference between these platforms?
Microsoft is open source for multi-agent orchestration. OpenAI is managed with visual builders. Choose based on your needs.
Which is easier for beginners?
OpenAI Agent Kit is easier with drag-and-drop. Microsoft requires coding knowledge.
Can I use both together?
Yes, the hybrid approach uses Microsoft for orchestration and OpenAI models as tools.
Which has better security?
Microsoft gives full control over security. OpenAI offers managed security. Both support best practices.
What languages work with each platform?
Microsoft uses Python or .NET. OpenAI uses minimal code with visual builders.
Can I self-host?
Yes with Microsoft. No with OpenAI (OpenAI hosted).
Which is better for startups?
OpenAI is better for startups needing fast prototyping without infrastructure.
Which is better for enterprises?
Microsoft is better for enterprises needing full control and no vendor lock-in.
What are connectors?
Connectors integrate tools like Gmail, Calendar, Slack into agents.
Can multiple agents collaborate?
Yes, Microsoft excels at multi-agent orchestration. OpenAI focuses on single agents.
What’s the cost?
Microsoft is open source (free). OpenAI pricing depends on usage.
Which has better developer tools?
Microsoft has excellent VS Code integration. OpenAI uses web-based builders.
Can I deploy anywhere?
Yes with Microsoft. OpenAI deploys on OpenAI’s platform only.
Which should I choose as a developer?
Developers wanting control choose Microsoft. Developers wanting speed choose OpenAI.
Where can I learn more?
Learn more at AI Profit Boardroom for complete AI agent training.
Your Next Steps
Now you know which to pick.
Need control and orchestration? Choose Microsoft.
Need speed and managed platform? Choose OpenAI.
Hybrid approach works too – use both tools to get best of both worlds.
Let me know in comments which you’ll try.
Drop your thoughts below.
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