I recently had a fascinating conversation with a founder who's built an impressive MVP using a no-code platform. Their tool helps match projects with potential investors through AI-powered data extraction. After several months of development, they were questioning whether their no-code approach could scale to meet their commercial ambitions.
This conversation perfectly illustrates the strategic decisions every company faces when building with no-code tools. Here are the key insights from our discussion.
The No-Code Sweet Spot: Getting to Market Fast
The team made exactly the right call initially. They had an idea for a database-driven tool that would scrape company websites, use AI to extract structured data about potential investors, and provide filtered search results. Rather than spending months on custom development, they chose a no-code platform and got to market quickly.
This is no-code at its best. When you're validating product-market fit, the most dangerous thing you can do is over-engineer. There's a saying in software that if you're not slightly embarrassed by your first MVP, you've waited too long to launch. Their approach embodied this perfectly.
The 80/85% Performance Ceiling
But here's where things get interesting. Like many teams using AI-powered solutions, they're hitting the classic performance plateau. Their web scraping and AI integration works, but the data extraction isn't quite accurate enough for commercial deployment. They're getting 80-85% of the way there, but that last 10-15% is proving elusive.
This pattern is incredibly common with AI implementations. The initial results look promising, but getting from "pretty good" to "production ready" requires fine-tuned control over algorithms, prompt engineering, and data processing pipelines. This is where no-code platforms often show their limitations.
The Flexibility Question: When Customization Becomes Critical
As they described their evolving requirements, I could see the classic no-code tension emerging. They want better UI customization, more sophisticated data visualization, and industry-specific logic. What seems like simple changes ("can we show different charts for different industries?") becomes complex in a rigid no-code environment.
No-code tools excel when you're following well-trodden paths. But once you need custom workflows, specific integrations, or unique user experiences, you start hitting walls. Tasks that would take a developer a day or two become complex multi-component integrations in the no-code platform.
The API Safety Net: Why Exit Strategy Matters
One crucial factor that influenced my advice was their platform's API accessibility. Unlike some no-code platforms that lock you into their ecosystem, their chosen platform exposes APIs that allow you to build around their core functionality. This means the team doesn't face a binary choice between "stay with no-code" or "rebuild everything from scratch."
When evaluating any no-code platform, ask yourself: "Can I access my business logic and data through APIs?" This single question can save you from vendor lock-in and enable incremental migration strategies.
A Phased Evolution Strategy
Rather than recommending a complete platform change, I suggested a hybrid approach:
- Keep the working parts: Continue using the no-code platform for web scraping and basic data processing where it performs well
- Build around the limitations: Create custom UI components and industry-specific features using traditional development
- Experiment incrementally: Test improvements in isolated areas before making wholesale changes
This approach maximizes their existing investment while providing the flexibility they need for growth.
Industry-Specific Considerations
The team mentioned plans to expand beyond their initial vertical into other industries. This raised an important point about no-code scalability. Different industries have different data sources and formats. Some sectors might have standard web pages, while others provide specifications in PDFs or other formats.
As you expand across industries or use cases, no-code platforms become increasingly restrictive. What works for one vertical might be completely inadequate for another.
The Economics of No-Code vs Custom Development
The feedback pattern they described—"that's very difficult" or unexpected time requirements for seemingly simple changes—is a red flag. It suggests they're pushing against the platform's boundaries.
This is the hidden cost of no-code: as your requirements become more sophisticated, simple changes become disproportionately expensive. You're paying for the platform's ease-of-use constraints even when you no longer need them.
Technical Recommendations Worth Considering
During our conversation, I shared several technical insights that apply broadly:
- Prompt engineering matters tremendously: LLMs are sensitive to format. Using structured markdown with headers, bullet points, and clear sections can dramatically improve extraction accuracy
- Consider alternative AI models: While OpenAI gets the headlines, Google's Gemini 2.5 Pro often performs better for data extraction tasks
- API flexibility is crucial: Most AI providers have similar APIs, so switching models shouldn't require architectural changes
The Path Forward: Strategic Technology Decisions
This situation illustrates a broader principle about technology strategy. No-code tools are excellent for validation and early development, but they're not always the right foundation for scalable, differentiated products.
The key is recognizing when you've outgrown your initial platform and having a migration strategy that preserves your investment while unlocking new capabilities. This isn't about no-code being "bad"—it's about using the right tool for the right phase of your company's journey.
Questions for Your Own No-Code Projects
If you're building on no-code platforms, ask yourself:
- Can you access your business logic through APIs?
- How will industry expansion affect your technical requirements?
- Are simple changes becoming disproportionately expensive?
- Do you need user analytics and fine-grained control over user experience?
- What's your plan for when you outgrow the platform's constraints?
The goal isn't to avoid no-code—it's to use it strategically and know when it's time to evolve. This team made smart early decisions and now they're making smart growth decisions. That's exactly how technology strategy should work.
No-code got them to market. Custom development will get them to scale. And with proper planning, they can bridge between both worlds without throwing away their existing investment.