Vibe Coding Just Hit the Hype Wall

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📉 Lovable & the Vibe Coding Chill — Fade or Reset?

Multiple web analytics services (e.g. SimilarWeb, Trovo, ChartBeat) have tracked a 30–50% drop in domain visits to major vibe coding platforms over the summer. Lovable, in particular, is often cited in social media posts as “dying” or losing relevance. One snapshot from August 2025 shows Lovable’s U.S. traffic slide from ~350K sessions/week to ~180K.

👉 Lovable traffic decline

But Lovable’s founder Anton Osika responded publicly, sharing internal data showing monthly growth in paying users, not visits. He claimed every few months someone says Lovable is dead—but core metrics like D30 retention and gross margin continue rising. He published a chart showing ~15% net new paid user growth even while traffic dipped.

👉 Osika’s response

But some people claim it is comulative adn growth flattened on net new users and not showing real churn publicly.

What’s Probably Happening

• Casual traffic fatigue is normal — early hype draws many curious visitors; over time, the interest curve cools. But paying, sticky users remain or grow.

• Mix shifts mask health — when a product moves from “free / discovery” mode to “paying / retention” mode, you expect front-door clicks to drop while funnel depth and ARPU rise.

• Comparative benchmarks show alignment — similar patterns on platforms like Cursor, Replit, and Codeium: early traffic spikes followed by steady paying adoption in multiple quarters.

• Analytics noise matters — unverified charts get viral vieing. Unless you see churn, LTV contraction, or drop in paying cohorts, a traffic dip is far from death.

The early clicks hype is fading — that was predictable. The real test is whether the paying base is growing. A traffic dip is not death. It’s a checkpoint.

🧩 The Agent Workflow Shake-Up — Old Maps, New Roads

It’s been a noisy few weeks in the agent-building world. OpenAI rolled out its long-awaited Agent Builder — a clean, drag-and-drop interface for chaining tasks, tools, and logic into custom agents. ElevenLabs followed with Agent Workflows, letting users visually route voice and text through modular agents.

At first, everyone called it the Zapier moment for agents — until builders actually tried it. The sentiment flipped: powerful, yes — but manual. You still have to wire every step, label nodes, and debug paths. It feels more like automation 1.0 than the next leap in agentic AI.

n8n entered the scene and shifted the tone.

Its new AI Workflow Builder (Beta) takes the opposite approach: type a prompt like “create a workflow that checks new leads in Airtable and summarizes them in Slack,” and it generates the logic, nodes, and connections for you. You can tweak it later — but it starts with your intent, not your flowchart.

👉 n8n: “Introducing AI Workflow Builder (Beta)”
👉 OpenAI’s Agent Builder
👉 ElevenLabs: Agent Workflows launch post

The Bigger Picture

What’s happening isn’t just tool churn — it’s a philosophical split in how we build with AI:

• Manual-first workflows (OpenAI, ElevenLabs) still think in boxes and arrows.

• Intent-first automation (n8n, emerging startups) starts with language → structure.

The next generation of agentic workflows will likely merge both — AI generating 90% of your flow from a prompt, while humans refine the edge cases visually. Think of it as prompt-to-production pipelines.

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