Investor’s Account: My AI Programming Project Lost 50% of Users, the “Vibe Coding” Bubble Is Bursting
🚀 AI and the Promise of “Zero‑Threshold Programming”
In today’s AI‑driven era, “zero‑threshold programming” has emerged as one of the most attractive promises. Platforms from Lovable to Bolt, and V0 to Replit repeat the same message:
> Don’t know how to code? No problem — AI will bring your ideas to life.
But what happens when reality doesn’t match the hype?
Lovable, once boasting 35 million users, lost half its user base in just months. This raises an industry‑wide question:
Where is the “AI programming revolution” going wrong?
To answer this, well‑known developer Theo — an investor in both Lovable and Bolt — published a brutally honest “career self‑sabotage” video. Below is an edited and condensed version of his analysis.
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1. When Investors Question Their Own Projects
On October 14, 2024, I released a video that could cost me dearly.
As an investor in two AI programming companies, Lovable and Bolt, I backed my claims with raw data:
the “vibe programming” boom may already be fading.
This wasn’t marketing spin or clickbait — it was triggered by stark numbers from Crust Data showing Lovable’s drop from 35 million users in June to under 20 million in September.
Surprisingly, Lovable responded not with defensiveness, but with openness:
> “Keep doing it — this helps people understand our situation.”
Such transparency convinced me it’s time to examine vibe programming with data and reason.
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2. The Numbers Tell the Story
Crust Data, fresh out of Y Combinator, estimates service usage via web traffic.
While exact numbers may vary, trends are clear: Lovable’s user base plummeted nearly 50% in three months.
Consider that there are roughly 40–47 million professional developers worldwide.
A Lovable peak of 35 million users means the majority were not professionals.
So we must ask: Who exactly are these tools serving?
Here we’re not talking about Cursor or GitHub Copilot — tools built to boost professional developer productivity —
but about platforms promising: “Build apps without coding knowledge.”
Their target audience? Everyday people with app ideas but zero programming skills.
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3. The GoPro‑Style “Wish Economy” Trap
Analogy time: GoPro.
2015: GoPro’s stock hit $85. Every sports fan seemed to own one.
2024: GoPro stock fell to $0.70 — a 100× drop — turning into a penny‑stock cautionary tale.
Why?
They weren’t selling just cameras — they were selling a dream.
Most GoPro owners never edited, posted, or rewatched their footage.
The camera symbolized professional creator potential, but in reality:
recording is easy; producing good content is hard.
AI programming platforms are making the same mistake:
The dream — “Anyone can make an app, instantly” — ignores the fact that building something useful, maintainable, and desirable is far harder.
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4. When Novelty Fades
The thrill of watching AI crank out a working prototype is real.
But sustaining an app means confronting:
- Maintenance & debugging
- Design refinement
- Integration complexity
- Compliance considerations
- Actual user demand
Without ongoing skills or commitment, projects stagnate — just like unwatched GoPro footage.
A smarter approach recognizes this aspiration gap.
For example, the open‑source platform AiToEarn官网 helps creators:
- Use AI for content generation
- Publish across multiple social ecosystems
- Track analytics & AI model rankings
This turns wishful ideas into market‑ready output — an approach vibe programming tools could learn from.
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Two Motivations for Trying New Tools
- Solve a Real Problem —
- Example: React. Steep learning curve, but solves genuine UI complexity for developers, earning it long‑term adoption.
- Satisfy Curiosity / Novelty —
- Example: Svelte or Solid.js. Fun to try, but with smaller adoption due to lack of necessity.
Social buzz ≠ adoption.
React dominates npm downloads despite fewer Twitter discussions — because it solves real needs.
Vibe coding tools fit the novelty category, but market themselves as need‑solvers — creating churn when reality bites.
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Graduation Dilemma: When Success Means Leaving
These platforms face a paradox:
- Effective users graduate — they either absorb rising costs or move to professional tools like Cursor.
- Ineffective users quit — frustration kills the journey.
Platform Testing Observations:
- Lovable — clean UI, but generated apps often need heavy iteration.
- Bolt — feature‑rich, but Chrome‑only and requires “Web container” know‑how.
- Replit — too many options for those avoiding code.
- V0 — practical component generation, but still demands technical base knowledge.
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5. Why I Still Support This Direction
Even with the drawbacks, I invest here because of impact, not volume.
Like GoPro inspiring future YouTubers, AI coding tools will ignite programming passion for a dedicated few.
For 1% of users, their first “It works!” moment can launch a tech career.
This barrier-lowering matters — it seeds the next generation of developers.
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6. Riding Tech Waves Rationally
Every hype cycle claims: “This time is different.”
But rules of business & human nature rarely change.
- Enduring tools: serve real needs (e.g., professional coding tools).
- Ephemeral booms: sell illusions without solving deep problems.
Platforms like AiToEarn show promise by bridging creation with monetization, offering:
- AI‑powered content generation
- 1‑click multi‑platform publishing (Douyin, Kwai, WeChat, Bilibili, Rednote, Facebook, Instagram, LinkedIn, Threads, YouTube, Pinterest, X/Twitter)
- Analytics & model performance tracking
Learn more:
AiToEarn官网 · AiToEarn博客 · AiToEarn开源地址
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7. Key Takeaways for Builders & Investors
For startups & investors:
- Avoid selling illusions; solve real problems.
- Measure actual adoption, not hype‑driven spikes.
- Know your true target user; unexpected huge user surges may indicate a short‑lived novelty wave.
For users:
- See these tools as gateways into programming.
- If you want to build something meaningful, you’ll need basic coding skills — there’s no shortcut.
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📌 Final Thought
AI will transform programming — but not by turning everyone into a developer overnight.
Its true power lies in making developers more efficient and creative.
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Would you like me to create a concise visual summary infographic of these key points so it’s easier to share on social media? That could condense the lessons from Lovable’s decline into a single, high‑impact visual.
