10 min
The State of Vibe Coding: Insider Trends, Hacks, and Hard Lessons
Vibe coding—the act of building apps through natural language and AI rather than traditional coding—is no longer a quirky demo. It’s a fast-moving battleground with 130+ competing tools, millions in VC dollars, and entire communities forming overnight.
After sitting inside the early chaos at Lovable (born from GPT Engineer) and watching competitors like V0, Emergent, Orchid, Bolt, and Base44, here’s the unvarnished reality of where the industry is, what’s broken, and what might survive.
From GPT Engineer to Lovable: How Timing Made the Trend
When GPT Engineer first launched, it failed twice. The AI simply couldn’t generate valid code; models weren’t ready. It wasn’t until GPT-4 that a leap in model quality made the idea viable. By then, rebranding to Lovable gave the product the identity and virality it needed—something “GPT Engineer” never could.
The early bet paid off. By October, Lovable launched alongside V0, Replit’s new push, and Bolt. The wave was undeniable: vibe coding had become the obvious “next thing” in AI.
But this came with brutal costs. At its peak, Lovable was burning $1.2 million a week just on LLM calls, with 80% of infrastructure costs going to model usage. That expense drove many of the most creative growth hacks the team pulled off.
Use Cases: Simple, Internal, and Fun
Despite the hype, most builds fall into three categories:
- Simple apps: CRMs, portfolios, to-do lists, clone sites.
- Internal B2B tools: sales enrichers, KPI dashboards, meeting-note systems.
- Creative/fun: mini-games, interactive sites, experimental playgrounds.
The mass-market dream—“a farmer or restaurant owner can build their own tools”—remains largely unrealized. For now, vibe coding thrives more in PM, designer, and indie hacker circles than with true mainstream adoption.
The Education Problem: Why Retention Collapses
The number one blocker isn’t tech—it’s users not knowing how to use it. Three problems dominate:
- No clear idea: people default to “make me a website.”
- Poor prompting: they can’t describe what they want.
- No code literacy: they can’t debug the AI’s output, so projects break.
This creates a vicious loop: no idea → no prompt → no code understanding → churn.
Tools like DataButton (roadmap/PRD before code) and Tempo Labs (visual PRD diagrams) are tackling this education layer. Chat-based prompting loops, roadmap-first building, and visual representations are quickly becoming the missing bridge between casual users and serious builders.
Shifts Reshaping the Space
- Full-stack pivot
- Multi-LLM era
- Distribution > product
- No-code incumbents adapting
- Invisible agents
- Vertical LLM apps
Tools are moving away from just frontend MVPs. Lovable, Emergent, Base44, and Bolt are all racing to own the backend layer, where recurring revenue lives. Supabase/Firebase reliance won’t last; proprietary backends are the new battleground.
No single LLM is enough. The smartest tools now rotate between Anthropic, OpenAI, Grok, and Mistral depending on task. Lovable even staged public bake-offs between models—users tested outputs, and the data doubled as leverage in contract negotiations.
The product is rarely the differentiator—distribution is. Lovable’s growth was 80% paid (ads, influencer deals, hackathons, affiliates). The other 20% was pure virality from stunts, branding, and community.
Figma, Bubble, Webflow, Wix, Miro—everyone is adding conversational interfaces. Expect consolidation: today’s 130+ vibe coding tools will collapse into a handful of dominant players.
Behind-the-scenes automation—PR review bots, auto-bug fixers, code summarizers—are emerging fast. They’re not visible features, but they’re sticky infrastructure.
Even Anthropic and OpenAI are now releasing vertical products (e.g. Anthropic’s Artifacts, OpenAI’s GPTs with Canvas, xAI’s Grok). Vibe coding tools risk being undercut directly by the model providers themselves.
Growth Hacks That Defined Lovable
Lovable’s virality wasn’t an accident. It was built on scrappy, sometimes desperate, stunts:
- GitHub outage flip: when GitHub shut off API access, 200,000 apps broke overnight. Instead of apologizing, Lovable announced a “Free Unlimited Weekend.” Outrage turned into hype.
- Model competitions: rather than quietly negotiating contracts, they let users pit Anthropic vs OpenAI vs Grok in public challenges. This created hundreds of viral videos, gave negotiating leverage, and cost almost nothing in marketing spend.
- Hackathons at scale: instead of hosting hackathons, they handed out credits and promo codes, letting anyone run Lovable-branded events. Reach exploded without draining internal resources.
- Discord community: 200,000+ builders filled the Lovable Discord, but the magic was that users self-organized. Moderators, champions, and support staff emerged without being hired, making community a free distribution engine.
Retention: The Eternal Struggle
Despite the hype, retention was fragile:
- The 10-prompt rule: if a user made 10 meaningful prompts (adding features, not just fixing bugs), they were likely building something real and would stick.
- Ship fast, break often: Lovable’s edge was speed. They shipped features constantly—even if half-broken—because curiosity and first-mover buzz outweighed polish. Competitors copied GitHub integration, changelogs, templates, and visual editing after Lovable shipped first.
- Churn reality: almost nobody talks about it, but churn is catastrophic across AI apps. Users pay for a month, test, then vanish to try one of 129 alternatives. Retention depends less on product stability and more on FOMO and viral content.
Positioning Plays
Positioning is everything in a crowded field:
- Spawn pivoted hard into gaming, building multiplayer worlds instead of generic apps. It saved them.
- Orchid launched “clone Netflix/Airbnb in one click.” Simple, clear, viral.
- Lovable began as B2C (99% of the world should be able to build), but pivoted toward B2B internal tools. Many inside saw that as killing the original vision.
The lesson: broad “build anything” positioning doesn’t work. Clear verticals—gaming, website cloning, education-first building—win attention and stickiness.
Where the Future Points
- Voice-first
- Education as moat
- Verticalization
- Community-led growth
- Experimentation > strategy
Typing prompts is slow. Voice interfaces (Whisper Flow, Eleven Labs) are the obvious next layer. At Lovable, the absence of voice prompting was a top complaint.
Users need structured guidance: idea → PRD → prompts → code literacy. Whoever solves this retention loop wins.
Generic builders will lose. Niche plays (games, clones, B2B internal tools) have stronger traction.
Champions, influencers, and Discords matter more than ad spend long term. Community is both support and distribution.
The market is unpredictable. Some predict Figma will absorb everything; others expect a single AI OS to wipe out the fragmented tools. The only safe strategy is constant experimentation and speed.
Final Take
Vibe coding is both overhyped and inevitable. Most of today’s 130+ tools won’t survive. The space is littered with churn, sameness, and unsolved education problems. But the impact is undeniable: it’s changing who gets to build software, how fast ideas turn into products, and what distribution looks like in an AI-native world.
The winners won’t just let you “build an app in minutes.” They’ll:
- educate users,
- own a clear vertical,
- ship first and often,
- go voice-first,
- and turn community + distribution into their real moat.
Because in vibe coding, the product is never the product. The distribution is.