Bolt burns your budget in hours. Lovable drains credits per debug session. Devin completes 15% of complex tasks. Here's the honest breakdown — and what actually works.
8 dimensions that matter for getting your product into production. No marketing fluff — just what each platform can and can't do.
| Category | ✦ Prodcraft | Bolt.new | Lovable | Replit Agent | Devin |
|---|---|---|---|---|---|
| Pricing model | From $199 flat fee | Token-based | Credit-based | Opaque cycles | $500/mo+ |
| Cost predictability | 100% predictable | Burns fast | One debug = drained | Hard to estimate | Unpredictable |
| Full workflow | Brief → Launch | Frontend only | Frontend heavy | Dev environment | Code tasks only |
| Production readiness | Live on day 1 | Manual deploy | Basic hosting | Replit infra only | Code only |
| Backend support | Full stack | Limited | Supabase only | Yes | Yes |
| Mobile support | Responsive web | Web only | Web only | Web only | Web only |
| Domain logic | Research-backed | Prompt-driven | Prompt-driven | Prompt-driven | Task-specific |
| Agency experience | 20yr track record | No | No | No | No |
The marketing hides the real cost. Here's what actually happens when you try to ship a production product with each platform.
Bolt's $25/mo plan sounds reasonable — until you hit the token wall 4 hours into your first serious build. Every render, every debug, every "just fix this one thing" burns through your monthly budget before lunch.
Lovable's credit model feels manageable until you hit your first bug. One session chasing a broken form validation or API integration can drain your entire monthly allocation. Then you pay again or wait.
Replit's pricing is opaque enough that most developers can't estimate costs upfront. "Checkpoints" and "cycles" make planning impossible. Great for prototypes — not for production products with real deadlines.
Devin impressed everyone on release. Then the independent benchmarks landed: 13.86% task completion on complex real-world software tasks. For $500+/mo, you're paying enterprise prices for a tool that completes 1 in 7 hard problems.
Our analysis of every major AI builder found 7 gaps that consistently block AI-generated code from becoming a real, working product.
Code generators produce demos that pass visual inspection but fail under real load, real auth flows, and real edge cases. "Works in preview" ≠ ships.
Token and credit pricing models turn every revision into a gambling decision. You can't plan a product sprint when costs are unknowable until the bill arrives.
Most AI builders stop at the frontend. You still need to wire up databases, APIs, authentication, payments, and hosting — the hard parts remain your problem.
Business logic, complex data models, multi-tenant architectures, and custom integrations exceed the capability of prompt-to-code tools. They generate structure, not systems.
AI builders don't understand your industry, your users, or your competitive context. The code might be technically correct but strategically wrong — and no one will tell you.
Products don't emerge fully-formed from a single prompt. Every tool that charges per token or credit penalizes the iteration that makes products good. The best work is the most expensive.
20 years of software delivery patterns — architecture, scope control, technical debt management, launch checklists — can't be replicated by an LLM that has never shipped a product in production.
No token traps. No credit cliffs. One flat fee — brief to production-ready product, with 20 years of agency experience behind every line.
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