ChatGPT Just Pulled the Rug Out from under n8n, Make, and Zapier

 

Copyright: Sanjay Basu

Here’s Why AgentKit Kills the Middleman

A single update just vaporized an entire swath of startups. Zapier, Make, n8n. All the automation glue tools you once trusted, got a black swan-sized threat when OpenAI dropped AgentKit. Overnight, the promise of drag-and-drop agent creation turned from a clever thought exercise into a working, production-grade system. The era of stitching APIs by hand feels suddenly archaic.

Yes, I’m claiming that ChatGPT just made startups obsolete. Or, at least, drastically reshaped which ones survive. My opinion, of course!

The timing is uncanny. We’ve long lived in an era of “no-code” and “low-code” optimism. Anyone can build your integration, pipeline, or workflow without touching lines of code. Tools like Zapier, Integromat (now Make), and n8n democratized automating tasks. They bridged silos, mapped data flows, and let you chain triggers and actions across apps. But they were never built for the era of autonomous, agentic AI. They lacked the reasoning layers, versioning, agent orchestration, and robustness needed for real-world agents.

Meanwhile, AI exploded. The shift from static integrations to reasoning agents, systems that decide, plan, self-correct, was always inevitable. But until now, building an agent meant weeks of engineering: prompt tuning, custom connectors, debugging broken workflows, wrangling frontends, managing versioning. It was as if you had to invent your own Zapier-like engine just to get started.

AgentKit changes that. It collapses the complexity of agent building into a visual, no-code (or minimal-code) environment. It gives you all the plumbing, connectors, logic, UI embedding, evaluation, in one platform. In one stroke, OpenAI ate the middlemen.

Let me walk through how it unravels the current ecosystem.

What AgentKit Does, and Why It Kills

The Old Way: Engineering Frankenstein

To build a useful AI assistant, you had to:

1. Wire together prompts and logic.
2. Build (or find) connectors to Dropbox, Google Drive, Salesforce, Slack, etc.
3. Create guardrails, constraints, validation, error handling.
4. Build a front-end chat interface or embed UI.
5. Deploy, version, monitor, iterate.
6. Handle evaluation, performance metrics, feedback loops.

Any misstep, like broken workflow, prompt drift, or connector failure, would spoil the user experience.

Meanwhile, startups like Zapier, Make, and n8n evolved to stitch apps. “When this happens, do that.” They shined in business automation before AI took off. If you needed “when a new Google Sheet row appears, send Slack message,” they were gold. But they never were built to reason, to chain agents, to evaluate responses, to self-correct.

Now AgentKit is layering AI on top of that kind of plumbing. And then swallowing it.

AgentKit’s Four Pillars

1. Agent Builder

Visual canvas. You drag nodes, craft logic, version flows. But this isn’t just “if A then B.” You can define multi-agent workflows. One agent delegates to another, branches logic, applies guardrails. You can preview runs, collaborate, and roll back versions. All the scaffolding you used to code by hand is now built in.

2. Connector Registry

You don’t have to worry whether Dropbox, SharePoint, or some obscure API has a wrapper. They’re all managed from one hub, with data governance baked in. Need to plug in an internal REST endpoint or a legacy database? You do it once, register it, reuse it. Every connector goes through the same controls, audit logs, schemas. The “glue” is built-in.

3. ChatKit

You embed full chat agents, with streaming replies, brand UI, custom theming. No more building the chat UI from scratch or using back-of-envelope workarounds. Your agent becomes a first-class part of your app or site in minutes.

4. Evals 2.0

It’s not enough to ship an agent — you must measure it, refine it. AgentKit gives you evaluation datasets, automated grading, reinforcement fine-tuning loops. You see where your agent fails, where it’s hallucinating, and then iterate. The feedback loop is first-class.

In sum, prompt logic, connectors, UI embedding, and evaluation. All in one system. No need to hop across ten tools, maintain multiple subsystems, or stitch things in a dozen languages.

Why That Means Zapier, Make, n8n Are in Trouble

Let’s compare.

• Zapier is great at “if this then that.” Trigger–action pairs. But it doesn’t reason. It doesn’t evaluate, self-correct, or craft responses. It’s an automation bus, not an agent fabric.
• Make (formerly Integromat) has more complexity: iterators, branching, error handling. But still, it’s wiring, not cognition.
• n8n gives you open-source control; you can code custom logic. But it’s still plumbing-first, not agent-first.

What AgentKit does is absorb the use cases of those tools and layer on the intelligence those tools never had. So the value proposition for building startups around workflow automation is flattened: instead of stitching APIs and hoping logic holds, you get agentic systems out of the box.

That kills differentiation. If your startup was “make AI workflows easier,” you now face a platform that offers that natively. The cost of building your own connectors, error-handling logic, evaluation loops. That barrier just collapsed. Why pay a startup to do what OpenAI now offers for free (or lower cost, integrated)?

Darwinism in SaaS

AgentKit isn’t just a product launch. It’s a strategic pivot. OpenAI is playing chess with the SaaS stack. Let’s consider. Who survives when the platform shifts?

1. Commodity disruption

What once required months of engineering is now table stakes. Startups whose entire value rested on “simplifying agent design and deployment” will see their moat evaporate. Your “secret sauce” is now an optional layer from the platform itself.

2. Focus moves upward

If everyone uses AgentKit for basic orchestration, the next frontier is domain expertise. Think industry-specific agents, vertical compliance, deep domain modeling. So the startups that survive will stand on domain specialization, not rudimentary agent plumbing.

3. Embedded flare

Companies that embed agents as part of their core product (e.g. CRM, analytics, vertical systems) can benefit. They’ll become competitive faster, because their AI layer no longer has to be hand-built. The edge shifts toward domain incumbents that embrace AgentKit, not point-tool startups that don’t.

4. Platform consolidation

It’s possible OpenAI will open AgentKit to third-party marketplace connectors, plug-ins, vertical modules. Think “AgentKit app store.” Some of those modules may be provided by former workflow startups. But they’ll be addons, not core. They’ll compete inside the OpenAI universe, not outside it.

So the future isn’t bleak for all automation startups — just for those whose only value was gluing. The future is fiercely vertical. The future is domain. The future is specialization, not general plumbing.

What Would I Build If I Had Full AgentKit Access Today?

If I woke up tomorrow, unlocked to AgentKit, here’s what I’d build, not the obvious “assistant” or “chatbot,” but something that would make the shift visible.

A Compliance Agent for SMB Legal Workflows

Small law firms, small businesses struggle with compliance: contracts, NDAs, regulatory filings, invoicing. What if you could build an agent that reads your contract, flags risky clauses, drafts suggestions, tracks filing deadlines, connects to DocuSign, Slack, your document storage, and surfaces summarizations to your dashboard? All wrapped as a plugin inside your business tool.

Using Agent Builder, I’d design a multi-agent system:

• Agent A reads documents and surfaces red flags.
• Agent B drafts new clauses via guided templates.
• Agent C interacts with external services: storage, signature, email.
• Agent D monitors deadlines and nudges users.

Connector Registry handles DocuSign, Dropbox, law APIs. ChatKit gives your users a clean interface in-app. Evals 2.0 ensures the agent’s suggestions stay consistent, safe, and on-brand.

Before AgentKit, that would’ve been 6 engineers, 3 months, many bugs. With AgentKit, you could ship a minimal agent in a week. And now your startup isn’t “workflow glue,” it’s a smarter, domain-driven assistant that non-experts can use, tweak, fund, adopt.

A Sales Ops Agent for B2B Deals

Imagine an agent that monitors prospects, pulls in LinkedIn signals, scrapes public filings, drafts personalized outreach, logs interactions in your CRM, nudges reps, and tracks deal flow. That’s several systems talking now, but with AgentKit, you tie them into one intelligent orchestration.

The interesting twist: you can replace ad-hoc Zapier workflows (e.g. “when deal stage changes, send email, update record”) with an agent that reasons: “Don’t spam this lead; wait two days; personalize message based on recent public news.” You embed that directly into your CRM and product. That’s where the value lives — not in the plumbing.

I’d start there. You’ll instantly beat 90% of sales tools that still are rigid workflow engines.

A Knowledge Ops Agent for Teams

Companies have enormous latent knowledge. Documents, playbooks, strategy memos, Slack chats, past projects. What if an agent could answer internal questions, propose workflows, generate summaries, suggest next steps? You plug it into knowledge bases, Slack, ticketing, Confluence. And your agent becomes your team’s assistant.

By layering agent logic with connector registry and embedded chat, you can build that knowledge ops assistant in days. That’s exponentially more valuable than a rigid workflow engine.

So those are three launches I’d try, if I were building on AgentKit from Day One: compliance, sales ops, team knowledge. All of them are higher-order problems, not integration plumbing.

Unexpected Turns & Provocations

Let me toss out a few provocations, things I don’t have full proof of, but that the AgentKit moment suggests.

1. Do we reach agent monoculture?

If everyone builds on AgentKit, do all agents begin to resemble each other? API chaining logic may converge, connectors may converge. The differentiator will then be in datasets, domain tweaks, or branding. That threatens creativity in the mid-tier.

2. Will OpenAI become the new operating system?

With AgentKit, OpenAI steps into the role of pipeline OS: the runtime that internal tools and startups rely on. That’s a locus of power shift. Your agent startup is now dependent infrastructure on OpenAI. You trade flexibility for reach.

3. Is this good or bad for decentralized systems?

n8n’s open, self-hosted appeal was sovereignty. But AgentKit is centralized (for now). Will this lead to a backlash or alternative decentralized agent platforms? There’s room for an “agent runtime you host yourself,” open source, privacy-first. That could push back.

4. Do we massively overshoot expectations?

Will people expect agents built in hours to be flawless? Will the “agent-first” hype crash into reality when connectors fail, reasoning disasters happen? How well AgentKit handles edge cases, hallucinations, security, governance, that will determine if it kills or nukes.

5. Does this sharpen the AI arms race?

Now the winner in automation is whichever agent you can iterate faster, test more, catch errors. That raises the bar on evaluation, on safety, on UX. Competence matters more. So startups now might not be gluing; they must innovate faster, smarter.

Closing Reflection

The autonomy of agents doesn’t just automate work. It reshapes how work gets done. AgentKit is less a product than a tectonic nudge. It realigns where value lies in the stack. The old value, in wiring APIs, is being downgraded. The new value lies in domain thinking, in risk handling, in vertical insight, in feedback loops, in emergent intelligence.

If Zapier was king of tying apps, AgentKit is becoming king of tying intent, reason, and action. And in that redefinition, many existing startups find themselves in a brutal landscape, either evolve upward, find a niche, or dissolve.

If I had a time machine, I’d whisper to those automation builders. Don’t build another “just glue” tool. Build the next wave. Agents that think, care, model, correct, evolve. Because the world in which Zapier was king is already being recast.

What would you build first on AgentKit? A clever agent for HR? For project management? For your personal life? The tools await. You just need to pick your domain and stake your claim before everyone else floods in.