WEBVTT

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When a big player like OpenAI drops a new tool,

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especially one they call Canva for Agents. No.

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Well, the internet tends to jump straight to

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destruction mode. Oh, yeah. It's always, what's

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it going to kill? As soon as AgentKit landed,

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October 6, 2025, you saw it everywhere. RIP and

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8M. Just instant hyperbole. But that whole Tool

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Wars thing. It often misses the point, doesn't

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it? Especially when you're talking about serious

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business automation. Does the hype around easy

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visual building actually hold up for complex

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needs? Exactly. And that's what this deep dive

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is all about. We're doing a really rigorous head

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-to -head comparison. AgentKit versus NAN. We

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want to cut through that noise and figure out

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for you when you'd use which one. We'll look

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at six key areas. Okay, so let's set the stage.

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AgentKit. That's the new one. Low -code, drag

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-and -drop, visual. Built specifically for conversational

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agents. And importantly, it lives entirely within

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the open AI world. It's about accessibility.

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Right. And then there's NAN. Been around six

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years. The established powerhouse. Open source.

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Huge number of integrations. Over 500. It really

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targets developers, power users, people building

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custom, truly autonomous systems. That one's

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built for total control. So our starting hypothesis,

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just going into the testing, was pretty straightforward.

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AgentKit isn't going to kill an AM. They seem

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built for fundamentally different users, different

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jobs. Let's see if that holds up. Let's do it.

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First up, ease of use, or what we're calling

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the startup experience. Basically, how much friction

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is there just getting your first agent up and

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running? AgentKit. It felt incredibly beginner

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-friendly. We gave it an 8 out of 10. The interface

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is just clean, minimal, basic logic like IFL,

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transforming data. Pretty straightforward. Yeah,

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the key is speed. You can actually build your

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first agent, maybe doing a simple web search

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in like less than two minutes. Seriously, no

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API keys needed right away, no complex setup.

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You just start building. Okay, contrast that

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with N8n. We scored it a 6 out of 10 here. It

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is definitely powerful, a power user's dream

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maybe, but wow, there's a learning curve. You

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open it up and it's just hundreds of objects.

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That same... Simple web search. In A &A, you've

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got to select specific models that have custom

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HTTP requests. Definitely need your API keys

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handy right from the start. It asks for commitment

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up front, you know, but then it gives you enormous

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power back later. So for the learner just starting

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out, what's the main takeaway on that startup

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experience? Is it speed versus depth? Agent Kit

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gives you that fast access, that quick win. Ain't

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Ain't Ain't makes you invest time before unlocking

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its real power. Okay, makes sense. So if getting

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started is one thing, how does Agent actually

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start? Let's talk triggers. Yeah, and this is

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where you see a real philosophical split. Agent

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Kit scored a 5 out of 10 from us. Why? It's basically

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limited to just the start node. Meaning? Meaning

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interactions are almost always chat -based. You,

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a human, have to talk to it to kick things off.

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Right. It forces that human intervention for

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pretty much everything. No scheduled triggers,

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no reacting to things happening in other apps.

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Nope. No timed triggers, no listening for events

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in Slack or Gmail, no real background capability.

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It needs you to chat with it. That feels like

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a pretty big limitation for genuine automation,

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doesn't it, for systems that should just run

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themselves? Totally. If a business needs something

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to, say, check inventory levels every night at

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3 a .m. and send an alert if stock is low, AgentKit

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just can't do that silently. It needs a human

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prompt. So if a business needs automation that

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runs without someone typing into a chat, what's

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AgentKit's strategic problem there? Its design

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inherently forces human interaction, limiting

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its use for those silent background processes.

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Okay. And A &AN on triggers. Oh, A &AN is trigger

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paradise. Solid 10 out of 10. Hundreds of native

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triggers built in. Gmail, Slack, webhooks from

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anywhere, databases. Time -based stuff too, like

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run every hour. Yep. Time -based external events.

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It lets you build genuinely autonomous, scalable

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workflows that just hum along quietly in the

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background. So it's the difference between like

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a chatbot assistant you have to poke versus a

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dedicated background system doing work silently.

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Exactly that. A virtual assistant versus a silent

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engineer. All right. Moving on from starting

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the workflow, let's get into the core stuff.

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What tools can these agents actually use? What

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can they connect to? Okay. AgentKit scored a

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5 out of 10 on tools. The built -in set is, well,

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limited. You get web search. something called

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a client tool to send data back to the chat interface.

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And then these things called MCP servers. Hang

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on. MCP servers. Can you break that down? What

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is that in plain English? Sure. Think of MCP

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servers as AgentKit's pre -built connectors for

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a few common services, like basic hooks into

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Gmail or Google Drive. They're easy to set up,

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which is nice, but the selection is really narrow

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compared to what else is out there. Gotcha. And

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AN. AN is the integration universe here. Easy

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10 out of 10. Yes, it has over 500 native integrations

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built right in, but the real superpower, it's

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the HTTP request tool. Which means? Which means

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if any service out there has an API, Any service

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at all. Any ant can talk to it. Period. Full

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stop. Wow. Okay. And what's really cool, architecture

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-wise, is modularity. NEN lets you build and

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reuse sub -workflows. Imagine building little

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specialized microagents, one for analyzing sentiment,

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one for parsing invoices, one for summarizing

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emails, and then having your main agent call

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these as needed. Yeah. I still wrestle with prompt

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drift and tool selection myself sometimes when

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I'm trying to chain multiple complex AI tasks

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together. So the idea of building one really

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solid, reliable sub -workflow for, say, data

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extraction and then just reusing that everywhere,

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that's... incredibly appealing, reduces so much

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variability. That modular approach using sub

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-workflows is NEN's killer advantage for complex

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specialized business processes, consistency and

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reliability. So beyond just the sheer number

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of tools, what's NEN the key advantage for those

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really specific business needs? Its architecture

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lets you build modular, reusable agent systems

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using those sub -workflows. Okay, let's shift

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to the brain behind the operation. Model support.

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Which AI engines can you actually use? With AgentKin,

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it feels like the OpenAI Exclusive Club. We gave

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it a 6 out of 10. Yeah. The integration with

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OpenAI models is excellent. Really deep. Easy

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toggles for GPT -4 versus others. Reasoning effort.

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How chatty it is. But, and it's a big but, you

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are completely locked into the OpenAI ecosystem.

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No Anthropic Quad. No Google Gemini. No open

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source models running locally. None of that.

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No Azure. No AWS Bedrock. No Cohere. Definitely

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no local models on your own hardware. It's OpenAI

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or nothing. And NAN. NAN is the model democracy.

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A clear 10 out of 10. You get genuine flexibility.

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Anthropic, Azure, OpenAI, AWS Bedrock, Cohere,

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anything via OpenRouter, plus local models using

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things like Alama. And you get control over the

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settings too, like temperature, top brand. Full

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control, which is crucial not just for performance,

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but for cost optimization. Right. So if cost

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saving is a major strategic goal, why does that

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model democracy matter so much? It allows you

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to route different tasks to the most cost effective

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and task appropriate model provider dynamically.

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Save money where you can. mid -roll placeholder

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sponsor content goes here. All right. So far,

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it feels like NAN is dominating on the pure back

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-end logic, the integration power, the model

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choice. But let's switch gears a bit. What good

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is all that complex logic if the user experience,

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the interaction is clunky? Let's talk UI and

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chat components. Ah, and this is where AgentKit

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really makes its case. A strong 9 out of 10 here.

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It's the front -end champion. Its integration

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with ChatKit means you can create really slick,

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professional -looking, branded website chat widgets

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and embeddable components right out of the box.

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We saw HubSpot talking about this, actually.

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They said ChatKit saved them literally weeks

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of custom front -end development work trying

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to build a similar interface themselves. That's

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huge. Weeks of dev time saved. Absolutely. So

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where's the clearest, most immediate time -saving

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advantage with AgentKit? Building polished, customer

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-facing chat interfaces takes basically zero

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extra development time. Compare that to ANAN,

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which we called the back -end beast. It scored

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a 5 out of 10 on UI. Its focus is overwhelmingly

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on the workflow logic. Yes, you can build basic

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chat interfaces, but they're hard to customize,

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hard to brand. For anything polished, you're

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looking at building a completely custom front

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-end using other tools and connecting it via

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API. So it's like Agent Kit gives you the finished,

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polished car. Well, NAN gives you a powerful

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engine and says, okay, now build the car body

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around it. That's a great analogy. Yeah. Okay.

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Final category, deployment and control. This

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gets into bigger enterprise concerns. Where does

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this thing run? Who controls the data? Who manages

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the infrastructure? Right. AgentKit gets a 7

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out of 10. It's a managed service. It runs only

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in OpenAI's cloud, the upside. Zero infrastructure

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for you to manage. Super convenient. The downside.

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OpenAI controls everything. Your data lives there.

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The uptime depends on them. The pricing is set

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by them. You have to fundamentally trust OpenAI

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with your critical operational data. Okay. And

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NAN. NANN is the sovereignty option, a full 10

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out of 10. It offers just unparalleled flexibility.

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Use their cloud service, sure, or self -host

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it on your own servers, or even run it locally

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on your laptop. And because it's open source?

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You get complete data control, zero vendor lock

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-in. You own the whole stack if you want to.

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Whoa. Imagine scaling that level of control,

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running maybe a billion queries a month, all

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on your own private, completely sovereign infrastructure.

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That's a game changer for highly regulated industries

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or just for companies wanting total control.

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Exactly. For compliance, data revidency. It's

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huge. So for a large enterprise, maybe in finance

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or health care, what's the single biggest factor

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tipping the scales toward A &N in this category?

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Complete sovereignty and control over data and

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infrastructure, especially for compliance needs.

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OK, so the final scores came out, AgentKit 40

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and A &N 51. But like we said up front, the raw

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numbers don't really capture the whole picture,

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do they? Not at all. The qualitative stuff matters

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just as much, maybe more. Take debugging, for

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example. Right. AgentKit, even though it's visual,

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sometimes when a workflow breaks. figuring out

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where the data went wrong between nodes can be

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opaque. You end up digging through logs. Whereas

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NAN, because it's built with developers in mind,

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gives you crystal clear visualization. You click

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on any node, you see the exact data that came

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in, how it was configured, and the exact data

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that went out. Troubleshooting is usually way

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faster. Plus, there's the community aspect. NAN

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has six years of history. Forums, templates,

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tutorials, community support. Yeah, a massive

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head start there. AgentKit is brand new, still

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building that ecosystem. Which brings us back

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to that strategic mindset we talked about. AgentKit

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isn't killing NEN. They're aimed differently.

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We need to shift from thinking which tool wins

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to which tool solves this specific problem best.

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That's the key. your clients or your business

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they choose you for results for solving their

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problems they don't really care which tool you

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used under the hood as long as it works reliably

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and efficiently so let's make it practical when

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should someone choose agent kit choose agent

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kit if you need something fast rapid deployment

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simple conversational agents quick prototypes

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or crucially if you want that polished chat widget

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on your website without spending weeks on front

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-end development and when is n8n the right call

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Choose N8n when you need flexibility with AI

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providers, when cost optimization across different

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models is critical, when you need complex background

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automations running silently without human intervention,

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when data sovereignty and control are non -negotiable,

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or frankly, when you need to connect to almost

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anything out there using its powerful API capabilities.

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It really sounds like the future is just coexistence.

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There's plenty of room. Absolutely. The market

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for automation is massive. AgentKit is going

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to be huge for quick internal. tools, simple

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customer -facing bots, people who value speed

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and ease above all. N8 will continue to dominate

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the complex enterprise -grade custom control

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scenarios. They serve different needs. So the

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big idea to wrap up. These platforms serve different

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masters. AgentKit is about making agent building

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accessible, fast, easy. NEN is about giving you

00:12:03.230 --> 00:12:06.360
unlimited control and integration power. The

00:12:06.360 --> 00:12:08.320
most important thing for you, the listener, the

00:12:08.320 --> 00:12:11.159
learner, is to become tool agnostic. Focus on

00:12:11.159 --> 00:12:13.059
the problem first. Yeah, and if you're totally

00:12:13.059 --> 00:12:15.340
new to this whole automation game, maybe start

00:12:15.340 --> 00:12:17.539
with AgentKit. Get your feet wet, understand

00:12:17.539 --> 00:12:19.960
the concepts, get some quick wins. Then when

00:12:19.960 --> 00:12:22.019
you inevitably hit its limits for more complex

00:12:22.019 --> 00:12:24.500
tasks, graduate to NAN for that deeper power

00:12:24.500 --> 00:12:27.100
and control. Because the tools themselves, AgentKit

00:12:27.100 --> 00:12:29.500
today, something else tomorrow, they'll keep

00:12:29.500 --> 00:12:32.879
changing. But the underlying skill. The ability

00:12:32.879 --> 00:12:35.399
to logically structure a problem, break it down,

00:12:35.460 --> 00:12:38.179
and design an automated solution. That skill

00:12:38.179 --> 00:12:41.039
is permanent. Focus on building that core problem

00:12:41.039 --> 00:12:43.019
-solving framework. That's the real investment.

00:12:43.139 --> 00:12:44.480
Focus on the framework. Focus on the outcomes.

00:12:44.659 --> 00:12:45.940
Excellent point. Until next time.
