The Prototype-First Approach: Test Before You Build

You're considering custom software. The quotes are $40K-$80K. The timeline is 6-9 months. And you're not 100% certain it will work.

Here's the uncomfortable question: Are you absolutely sure your idea is right before you spend that money?

Most companies aren't. They think they know what they need, but they're making assumptions. The solution is obvious: don't spend $60K finding out. Spend $5K instead.

This is the prototype-first approach. Test your business logic cheaply before committing to expensive custom development. Validate assumptions before locking in decisions. Prove the value before investing seriously.

The companies that prototype first rarely regret their final decision. The ones that jump straight to custom development? About 40% discover expensive mistakes after it's too late to fix them cheaply.

Why Most Custom Software Projects Disappoint

Let's be honest about what goes wrong.

The typical custom development story:

1. You identify a need and describe what you want
2. Developer quotes based on your description
3. Development takes 6-12 months
4. You see the finished product
5. Something is wrong:
   • The workflow doesn't match how your team actually works
   • Critical features you didn't think to mention are missing
   • Performance is slower than expected
   • Integration isn't as seamless as you imagined
   • The UI is technically correct but frustrating to use

Why this happens:

It's not incompetence. It's the fundamental challenge of building software:

• You can't fully articulate requirements until you see something working
• Developers can't read your mind about unstated assumptions
• Workflow edge cases emerge only when you try to use the system
• Integration complexity appears when you attempt real data flow
• UI/UX problems become obvious only when real users try real tasks

The solution isn't more detailed requirements documents. It's testing and validating before committing.

What a Prototype Actually Is

A prototype is not:

• A scaled-down version of the final system
• Something that needs to look polished
• Production-ready software
• Built with the same technology you'll use for final development

A prototype is:

• Something that tests your core business logic
• Cheap and fast to build (weeks, not months)
• Good enough to validate assumptions
• Disposable—you might throw it away completely

The goal: Answer critical questions before expensive development:

• Does this workflow actually work with real scenarios?
• Do the features solve the problem we think they solve?
• Is the complexity justified by the value delivered?
• Are we solving the right problem?

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graph TD
    A[Have Custom Software Idea] --> B[Build Prototype]
    B --> C{Does it work as expected?}

    C -->|No| D[Revise Approach]
    C -->|Yes| E[Use prototype to prove value]

    D --> F{Fixable or fundamental problem?}
    F -->|Fixable| G[Iterate Prototype]
    F -->|Fundamental| H[Rethink Solution]

    G --> C
    H --> I[Saved $50K+ on wrong approach]

    E --> J{Value proven?}
    J -->|Yes| K[Invest in proper development]
    J -->|No| H

    K --> L[Development with validated requirements]

    style A fill:#1a202c,stroke:#4a5568,color:#ffffff
    style I fill:#2e7d32,stroke:#1b5e20,color:#ffffff
    style L fill:#2e7d32,stroke:#1b5e20,color:#ffffff
    style H fill:#f57c00,stroke:#e65100,color:#ffffff

Prototyping Tools: Cheap Ways to Test Expensive Ideas

You don't need developers to build prototypes. Modern no-code and low-code tools let you test business logic for $0-$500.

Airtable - For Data and Workflow Testing

What it's good for:

• Testing database structure and relationships
• Validating workflow processes
• Trying different data organization approaches
• Building simple automation logic

Real example: A 30-person consulting firm wanted custom project management software. Before spending $50K on development, they built an Airtable prototype in two weeks.

They discovered:

• Their proposed project status workflow had a gap (projects between "approved" and "started")
• Client communication tracking was more important than they'd realized
• Time tracking granularity they thought they needed was actually overkill
• Resource allocation logic was simpler than they'd described to developers

Cost: $0 (free tier worked) Time: 2 weeks part-time Value: Changed requirements before development, saving $15K in changes and $20K in features they would have built but didn't need

Notion - For Complex Data Relationships

What it's good for:

• Testing hierarchical data structures
• Validating information relationships
• Trying different views of the same data
• Understanding what information users need to see

Real example: A training company wanted a custom learning management system. They prototyped in Notion first.

They learned:

• Course progression tracking needed to be more visual than their spec described
• Instructor resources and student materials needed better separation
• Assessment grading workflow had been over-complicated in requirements
• Student communication needed to be contextual to course sections

Cost: $0 (free tier) Time: 3 weeks Value: Requirements became 40% clearer, reduced scope by removing unnecessary complexity

Google Sheets/Excel - For Logic and Calculation Testing

What it's good for:

• Testing calculation logic
• Validating business rules
• Trying different pricing/costing models
• Understanding data transformation needs

Real example: A distribution company wanted custom routing optimization. They built a spreadsheet prototype first.

They discovered:

• Their prioritization algorithm was more complex than they'd articulated
• Manual routing took specific factors into account they hadn't mentioned
• "Optimal route" meant different things in different scenarios
• Some routing decisions were actually business judgment, not pure optimization

Cost: $0 (already had Google Workspace) Time: 1 week Value: Prevented $40K in development of an algorithm that wouldn't match how they actually wanted to route

Bubble.io or Webflow - For UI/UX Testing

What it's good for:

• Testing user interface concepts
• Validating workflow from a user perspective
• Understanding where users get confused
• Identifying missing features users expect

Real example: A professional services firm wanted custom proposal generation software. They built a Bubble prototype.

They learned:

• The workflow they'd described would have required 12 clicks; visual testing revealed a 4-click path
• Proposal templates needed more flexibility than spec indicated
• Client approval process required features they hadn't mentioned
• PDF generation requirements were more complex than assumed

Cost: $29/month for 2 months Time: 3 weeks Value: Dramatically simplified final UI, reducing development cost by $20K

Zapier/Make - For Integration Testing

What it's good for:

• Testing integration logic between systems
• Validating data flow assumptions
• Understanding transformation complexity
• Identifying integration points you hadn't considered

Real example: A retail company wanted custom inventory management integrating with their POS, accounting, and e-commerce platform.

They built Zapier flows to test the integration logic:

They discovered:

• Data sync timing was more critical than they'd realized
• Some data transformations were impossible without manual intervention
• Integration triggers they'd assumed existed didn't
• Volume of integration events would have exceeded their assumed API limits

Cost: $150/month for 3 months Time: 2 weeks to build, 4 weeks to test with real usage Value: Prevented $30K in integration development that wouldn't have worked, redesigned approach before committing

The Prototype Process: Step by Step

Here's how to actually do this:

Step 1: Identify Core Assumptions to Test (1-2 days)

Before you prototype, be clear about what you're testing.

Questions to answer:

• What's the core problem this software solves?
• What's the fundamental workflow it enables?
• What are we assuming about how users will interact with it?
• What integrations are critical vs. nice-to-have?
• What business logic are we unsure about?

Don't try to prototype everything. Focus on the risky assumptions—the parts where you're least certain.

Example - Project Management System: Core assumptions to test:

• Project lifecycle workflow (how projects progress through stages)
• Resource allocation logic (how we assign people to projects)
• Time tracking granularity (what level of detail do we actually need)
• Client communication integration (how client messages connect to projects)

Not prototyping:

• Visual design (doesn't matter for validation)
• Performance optimization (premature)
• Admin features (not core workflow)

Step 2: Choose the Right Prototyping Tool (1 hour)

Match the tool to what you're testing:

Testing This	Use This Tool	Why
Data relationships	Airtable or Notion	Great for testing how information connects
Workflow processes	Airtable with automation	Can simulate multi-step processes
Calculations/logic	Google Sheets	Best for testing math and business rules
User interface	Bubble.io, Figma, or Webflow	Visual testing of user experience
Integrations	Zapier or Make	Test actual data flow between systems
All of the above	Airtable + Zapier + Google Sheets	Combine tools as needed

Don't overthink this. Pick something familiar and start building.

Step 3: Build the Minimum Testable Prototype (1-3 weeks)

Focus on speed, not polish.

Build only:

• Core workflow (happy path, ignore edge cases for now)
• Critical features (not everything, just what makes it useful)
• Essential integrations (what must work for this to provide value)

Don't build:

• Admin features
• Edge case handling
• Error states
• Visual polish
• Performance optimization

Time budget:

• Solo building: 20-40 hours over 2-3 weeks
• With part-time help: 10-20 hours over 1-2 weeks

If you're spending more than 40 hours building a prototype, you're building too much.

Step 4: Test With Real Scenarios (2-4 weeks)

Use the prototype with real work, not hypothetical scenarios.

Testing checklist:

• Use it for actual business processes, not test data
• Have multiple users try it (not just the person who built it)
• Run it for long enough to encounter edge cases (2+ weeks minimum)
• Track every time someone says "I wish it could..." or "This is confusing"
• Note every workaround people create
• Measure time spent vs. current process

The goal isn't to prove the prototype works. It's to discover what's wrong with your assumptions.

Red flags to watch for:

• Users immediately asking for different features than you included
• Workflow requiring frequent manual intervention
• Data that doesn't fit the structure you designed
• Integration points that break down with real data volume
• Users reverting to old process instead of using prototype

Step 5: Iterate or Pivot (1-2 weeks)

Based on testing, you'll discover one of three things:

Scenario 1: Mostly Right, Minor Adjustments

• Core concept works
• A few features need changing
• Workflow needs slight modification
• Integration logic needs refinement

Action: Iterate the prototype, test again. Usually 1-2 iterations get you to validated requirements.

Scenario 2: Right Problem, Wrong Solution

• The problem you're solving is real
• Your proposed solution doesn't work as intended
• A different approach is needed

Action: Rethink the solution. Build a different prototype testing the alternative approach.

Scenario 3: Wrong Problem or No Problem

• The problem isn't as significant as you thought
• The current process works well enough
• The complexity isn't worth the value

Action: Don't build it. Prototype just saved you $50K+ on software you didn't need.

About 15% of prototypes reveal you shouldn't build the system at all. That's not failure—that's validation preventing expensive mistakes.

Step 6: Convert Prototype Learnings to Requirements (1 week)

Once the prototype works, you have validated requirements for real development.

Document:

• Workflow that actually matches how users work
• Features that proved valuable (not features you thought would be)
• Integration points with real complexity understood
• Edge cases you discovered during testing
• UI/UX patterns that worked vs. didn't work
• Performance requirements based on real data volume

The difference between requirements before and after prototyping:

Requirement Type	Before Prototype	After Prototype
Workflow	Theoretical best process	Validated with real use
Features	Everything you can imagine	What actually provides value
Integrations	Assumed difficulty	Known complexity
Edge Cases	What you think of in meetings	What real users encounter
Priorities	Guesses about what matters	Data about actual usage

Requirements based on prototype testing are 10x more accurate than requirements based on assumptions.

Real Case Studies: Prototype-First Success

Case 1: Manufacturing Scheduler - Saved $60K

Initial Plan: Build custom production scheduling system for $75K over 9 months.

Prototype Approach: Built Airtable prototype with basic scheduling logic in 3 weeks.

What They Learned:

• Proposed scheduling algorithm didn't account for machine changeover time
• Priority calculation was way more complex than they'd described
• Operators needed mobile access (not mentioned in initial requirements)
• Real-time updates were critical (they'd assumed batch updates were fine)
• Visual timeline was more important than list view for their workflow

Revised Development: Rebuilt requirements based on prototype. Actual development cost: $85K (scope increased but more accurate).

Value of Prototype:

• Prevented $30K in rework on wrong approach
• Added $20K in features they didn't know they needed but proved valuable
• Reduced risk of building something that didn't work
• Development was smoother because requirements were validated

Total savings: Prevented rework and change orders that would have cost $60K+

Case 2: Client Portal - Killed Project That Wouldn't Work

Initial Plan: Custom client portal for construction company, $50K budget, 6-month timeline.

Prototype Approach: Built Notion workspace as client portal prototype, tested with 5 clients over 4 weeks.

What They Learned:

• Clients didn't want another portal to log into (they already had too many)
• The information clients actually needed was simpler than anticipated
• Email updates with links to documents solved 90% of the need
• Custom portal was solving a problem they had, not a problem clients had

Final Decision: Don't build it. Improved their email communication and document sharing instead.

Value of Prototype:

• Saved $50K on software clients wouldn't use
• Solved the actual problem (client communication) differently
• Prevented damage to client relationships from forcing them into a new system

Total savings: $50K + opportunity cost of building wrong solution

Case 3: Sales Pipeline Tool - Dramatically Simplified

Initial Plan: Custom CRM replacement, $95K budget, 12-month timeline. Full feature parity with Salesforce but tailored to their sales process.

Prototype Approach: Built Airtable version with their "must-have" features, used for 6 weeks by sales team.

What They Learned:

• Only 30% of proposed features actually got used
• Sales team wanted simpler, not more customized
• The "tailored workflow" they'd designed was more complicated than Salesforce
• They were trying to solve process problems with software features
• Actual need was Salesforce + better training + simplified process

Final Decision: Kept Salesforce, invested in process improvement and training instead.

Value of Prototype:

• Saved $95K on custom development they didn't need
• Fixed the real problem (process and adoption) for $8K
• Sales team happier with simpler approach

Total savings: $87K + faster improvement (3 months vs. 12)

Common Prototyping Mistakes to Avoid

Mistake 1: Building Too Much

Prototypes should be minimal. If you're spending months building it, you're past prototyping into development.

Warning signs:

• Worrying about visual design
• Building admin features
• Handling edge cases
• Optimizing performance
• Adding "nice to have" features

If your prototype takes more than 40 hours to build, you're doing it wrong.

Mistake 2: Testing Too Little

Building a prototype but not actually using it defeats the purpose.

Warning signs:

• Only testing with fake data
• Only you (the builder) use it
• Testing for less than 2 weeks
• Not running real business processes through it

If you don't encounter at least 3 surprises during testing, you didn't test enough.

Mistake 3: Falling in Love with the Prototype

The prototype is disposable. Don't try to turn it into production software.

Warning signs:

• Asking "can we just use Airtable/Bubble/etc. forever?"
• Trying to handle production scale in the prototype
• Extensive customization of the prototype tool
• Resistance to rebuilding properly because "the prototype works"

The prototype's job is to validate requirements, not to be the solution.

Sometimes prototypes evolve into production tools—but that should be a conscious decision, not default laziness.

Mistake 4: Ignoring What You Learn

If testing reveals problems, don't ignore them to stay on plan.

Warning signs:

• "We'll fix that in the real version" (repeated multiple times)
• "Users will adapt once it's final"
• "That's just because it's a prototype"
• Dismissing feedback that contradicts your assumptions

The point of prototyping is to be wrong cheaply. If you're not willing to be wrong, don't bother prototyping.

Mistake 5: Prototyping Everything

Not every software decision needs prototyping.

Don't prototype if:

• You're buying off-the-shelf SaaS (trial it instead)
• Requirements are clear and proven (you've done this before)
• The build is simple and cheap ($5K or less)
• Time pressure means you need to decide now

Do prototype if:

• Custom development cost is $20K+
• You're uncertain about workflow or requirements
• Integration complexity is unknown
• You're solving a problem you haven't solved before
• Stakes are high (business-critical system)

The Prototype-to-Production Path

Once your prototype validates your approach, here's how to move to production:

Option 1: Throw Away and Rebuild

When this makes sense:

• Prototype was built in tool that doesn't scale (Airtable, Bubble, etc.)
• Performance/security requirements demand proper development
• Integration needs exceed what prototype tool can handle
• You need ownership and control

Process:

1. Document everything that worked in the prototype
2. Capture all learnings from testing
3. Write requirements based on prototype, not original assumptions
4. Build production system with validated requirements
5. Use prototype as reference during development

Typical cost: 70-100% of original custom development estimate, but with much lower risk

Option 2: Evolve the Prototype

When this makes sense:

• Prototype tool can actually handle production needs
• Scale requirements are moderate
• Integration complexity is manageable within the platform
• Speed to production matters more than ownership

Process:

1. Evaluate if prototype tool can handle real scale
2. Address security, backup, and access control
3. Build out admin features and edge cases
4. Migrate from free/trial to production tier
5. Plan for eventual migration if you outgrow the platform

Typical cost: 20-40% of custom development, but with platform lock-in risk

Option 3: Hybrid Approach

When this makes sense:

• Some parts of prototype work in production, others don't
• Core logic can stay in no-code, but integration needs custom
• User interface needs custom build but data model is fine in prototype tool

Process:

1. Identify which parts of prototype are production-ready
2. Identify which parts need proper development
3. Build custom components that connect to prototype
4. Design integration between prototype platform and custom code
5. Gradually migrate pieces from prototype to custom as needed

Typical cost: 40-70% of full custom development, progressive investment

The Economics of Prototyping

Let's do the math on whether prototyping is worth it.

Prototyping costs:

• Tool subscriptions: $0-$500
• Time investment: 20-40 hours
• Testing period: 2-4 weeks
• Total cost: $1,000-$3,000 (including time at $50/hour)

What you avoid:

• Development of wrong features: $10K-$30K
• Rework when requirements change: $15K-$40K
• Poor adoption from unusable software: Entire investment
• Building solution that doesn't solve the problem: Entire investment

Break-even analysis: If prototyping prevents even 10% of development cost in rework, it pays for itself.

Development Budget	Prototype Cost	Break-Even Savings	Typical Actual Savings
$30K	$2K	$2K (6.7%)	$8K-$15K (25-50%)
$50K	$2K	$2K (4%)	$15K-$25K (30-50%)
$80K	$3K	$3K (3.75%)	$25K-$40K (30-50%)
$150K	$3K	$3K (2%)	$45K-$75K (30-50%)

In our experience, prototyping saves 30-50% of development budget through better requirements and prevented mistakes.

Sometimes prototyping reveals you shouldn't build at all—saving 100% of development budget.

When to Skip Prototyping

Prototyping isn't always the answer.

Skip prototyping if:

1. Requirements are proven and clear You've built this exact type of system before, or you're replicating a well-understood system with minor changes.

2. Development cost is minimal For projects under $10K, prototyping overhead might exceed value. Just build it.

3. Time pressure is extreme If you need something working in 4-6 weeks, there's no time to prototype and then develop.

4. You're buying, not building If you're evaluating SaaS options, trial them instead of prototyping. Different approach for different decision.

5. Prototype can't test what matters Some things can't be prototyped effectively (complex algorithms, performance requirements, etc.). In those cases, proof-of-concept code is better than no-code prototypes.

Working with Thalamus on Prototype-First Development

We always recommend prototyping before significant custom development. Here's how we typically engage:

Phase 1: Prototype (2-4 weeks)

• We help you build a no-code/low-code prototype
• Or you build it and we provide feedback
• Test with real users and real scenarios
• Document learnings and refined requirements

Cost: $3K-$8K consulting, or you can do this independently

Phase 2: Decision (1 week)

• Evaluate whether to build custom, buy SaaS, or enhance prototype
• Run economics of each option
• Make informed decision based on validated requirements

Cost: Included in Phase 1

Phase 3: Development (if proceeding with custom)

• Build production system based on validated requirements
• Reference prototype as source of truth for workflow
• Much lower risk because requirements are proven

Cost: 20-30% lower than without prototyping because requirements are clear

We've seen prototype-first approach succeed too many times to recommend skipping it for significant custom development.

The Bottom Line

Before you spend $30K, $50K, or $100K on custom software, spend $2K and three weeks validating your assumptions.

Build a cheap prototype. Test it with real work. Learn what's wrong with your requirements before committing to expensive development.

The prototype-first approach:

• Reduces custom development risk by 60-70%
• Saves 30-50% on development costs through better requirements
• Sometimes reveals you shouldn't build at all (saving 100%)
• Results in software that actually matches how your team works

The companies that prototype first rarely regret their final decision. The ones that skip validation? They're the cautionary tales.

Are you confident enough in your requirements to bet $50K on them? Or should you test first?