No, OpenAI’s AgentKit didn’t kill AI agent builders. Here’s why.

_{OpenAI’s new toolkit is big news. But not every business should build its future inside someone else’s walls.}

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If you’ve been on tech Twitter or in any AI builder forum this week, you’ve seen the headlines:

“AgentKit is the end of Zapier.”
“AgentKit replaces every workflow platform.”
“Goodbye, no-code agent tools.”

It's a familiar cycle. OpenAI drops something big, and suddenly, the internet declares half the ecosystem obsolete.

AgentKit is a major step for developer infrastructure, but it’s not magic.

And it’s not replacing automation platforms, orchestration tools, or plug-and-play AI builders any time soon.

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What AgentKit actually is

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For startups building AI products on tight budgets and timelines, it's a fast way to get started.

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AgentKit is elegant and focused. It's a developer toolkit designed for AI workflows, combining several components:

Agent Builder: a drag-and-drop tool to design AI workflows
Connector Registry: prebuilt connections to common tools like Google Drive, SharePoint, and Microsoft Teams
ChatKit: a chat interface you can add to your website or app
Evals and reinforcement fine-tuning: tools to check agent performance

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The toolkit is built for exploration. Its visual workflows and testing tools help engineers see how language models reason through decisions, call functions, and complete tasks. For startups building AI-first products with tight budgets and fast timelines, it's a strong starting point.

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The trade-off: Convenience vs. control

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AgentKit's seamless setup hides an important trade-off: you're locked into OpenAI's models.

You can't use Claude when it's better for complex tasks. You can't switch to Gemini for cost savings. You can't use open-source models for self-hosting.

When a single provider controls your entire AI stack, you lose negotiating power. You have no hedge against outages, policy changes, or price increases. If OpenAI sunsets a model your agents depend on, you rebuild or accept whatever path they choose.

Many platforms like Kaily, Boltic, Make, and n8n explicitly maintain multi-model strategies (they support multiple AI models like GPT, Claude, Gemini, etc.) to avoid this. They let you route different tasks to different models based on what works best.

Even OpenAI's enterprise products don't fully solve this. Your agents still run on their servers under their rules. That's fine for simple use cases, but not when you're in healthcare, finance, or any regulated industry.

When your workflows, chat interfaces, and logic all depend on a single vendor, switching becomes painful.

Your AI stack should be your leverage, not your liability.

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Why independent platforms still matter

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AgentKit is capable but not universal. Independent platforms continue to thrive because they solve what AgentKit doesn't.

Agent builder vs. Orchestration platforms

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Agent Builder focuses on one thing: designing AI workflows within OpenAI's environment.

But most businesses need more than that. They need systems that actually connect to their tools, move data around, and work with the applications they already use. You know, the boring stuff that keeps companies running.

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Consider an ecommerce company handling 50,000+ support tickets monthly. They need agents that can:

Check order status in their OMS (Order Management System)
Process refunds through Stripe (Payment processor)
Update shipping via their logistics API
Log everything in Zendesk (Customer service platform)
Maintain context across chat, email, and SMS

Agent Builder can design the conversation logic, but it can't connect to those systems or operate across those channels.

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That's where orchestration platforms come in

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Tools like Boltic, Zapier, Make, and n8n are full automation platforms, not just agentic AI layers.

Take Boltic: it gives you visual workflow builders, AI agents that connect to your systems, serverless functions for custom code, API gateways, data storage, and the ability to use any AI model you want.

Agent Builder is a feature. Platforms like Boltic are complete automation systems that include AI as one capability among many.

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ChatKit vs. Conversational platforms

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ChatKit is well-built for teams building conversational prototypes or embedding AI chat into existing applications.

But here's the fundamental difference: ChatKit is built for developers. Kaily is built for business users.

Kaily lets non-technical teams launch production-ready agents in hours, not weeks. Marketing managers, support directors, and operations leads can configure agents hemselves. No coding, no developer dependencies, no waiting.

A healthcare network managing patient communications across 15 clinics needs agents that:

Integrate with EHR (Electronic Health Record) systems
Handle HIPAA-compliant data
Coordinate with insurance verification APIs
Work across SMS, email, and voice

With ChatKit, that's a 3-month engineering project. With Kaily, business users can configure integrations through a UI and launch within days.

Beyond the technical gap, there's the operational one. Kaily provides:

Multi-channel communication that maintains context across chat, voice, email, Slack, WhatsApp, etc.
Pre-built templates for support, sales, booking, and common workflows
Plug-and-play integrations with your entire business stack: Salesforce, HubSpot, Zendesk, ERPs, payment processors, and custom APIs
Business-user configuration: Marketing and support teams manage their own agents without engineering help
Data ownership and compliance by connecting directly to enterprise systems, giving companies full control over storage and access

ChatKit is a developer SDK for embedding AI chat. Kaily is a complete platform that lets business teams deploy and manage customer-facing agents without any technical help.

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How to know which approach fits your needs

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Choose AgentKit if you:

Are a startup with engineering resources
Are already heavily invested in OpenAI's ecosystem
Need to prototype AI agent workflows quickly without complexity
Operate in industries with minimal compliance requirements
Don't need multi-channel support or complex system integrations

Basically: you're technical, you're experimenting, and you don't mind living inside OpenAI's walls, this is probably your fastest path to market.

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Choose orchestration platforms (Boltic, Zapier, n8n) if you:

Need to connect AI logic to dozens of business systems
Require model flexibility across multiple providers
Must maintain strict data governance and audit trails
Want to automate workflows that mix AI and traditional logic
Need deployment control and self-hosting options

In other words: you're integrating AI into existing operations, not building everything from scratch.

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Choose experience platforms (Kaily) if you:

Support customers across multiple channels (chat, voice, email, messaging)
Need chat agents that take actions in your CRM, ticketing, or order systems
Operate in regulated industries with specific compliance needs
Require full data ownership and control over where information is processed
Want production-ready agents that scale with your business

Translation: you're running a real operation where uptime, compliance, and customer experience actually matter.

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The real question

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It's not whether AgentKit is good; it is. It's whether it's good for your specific requirements.

AgentKit raises the floor, not the ceiling. It proves that AI agents need infrastructure and makes prototyping dramatically faster. But rather than replacing independent platforms, it highlights why they matter.

The future of automation won't belong to one provider. It will belong to an open ecosystem where organizations choose tools that fit their needs, not their vendor's roadmap. I’ll leave you with my favourite takes so far.

Happy building!

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