From Idea to Working AI Prototype in 5 Days
No PowerPoint slides. No fancy reports. Just a working prototype you can test.
Why Prototyping Speed Matters
The classic scenario: you have an AI idea. A good idea even. So you set up a project, budget available, stakeholders enthusiastic. Then the preparation begins: requirements sessions, design reviews, risk analysis. Six months later? You have a nice report, PowerPoint slides and... still nothing that actually works.
Meanwhile, the moment has passed.
At plaiwrks, we do things differently. Not because we're lazy, but because we know: a working prototype in 5 days teaches you more than 6 months of planning. You immediately see where the challenges lie. You notice what your users actually want (spoiler: not what they thought they wanted). You know if it's even possible.
And only then do you decide: is this worth it?
The 3-Step Prototype Process
Day 1-2: Explore & Learn
We don't start with coding. We start with understanding.
On day 1 we do intensive sessions:
- What is the exact problem?
- Who actually uses this?
- What would success look like?
- Where are the pitfalls?
Many teams have "a good idea" without it being really worked out. This is where we do that.
Day 2 we look at data. What does your data look like? Is it clean enough? What tools do we need? What can we reuse from existing systems?
By the end of day 2, we know exactly what we're going to build.
Day 3-4: Build & Test
Now we do what it's all about: we build the working prototype.
This can be a chatbot (with Claude, ChatGPT, Gemini – doesn't matter, we're tool-agnostic). It can be an automation that processes data. An AI dashboard. Whatever.
Important: we only build what's needed. No fancy UI (not yet). No edge-case handling (not yet). Just: roughly working.
At the same time, we test. Real data, real workflows. We quickly see where the AI works well and where it fails.
Day 5: Document & Present
You now have something tangible. Something you can see working. Something you can experiment with.
We don't document with reports. We document with: this works, this doesn't work, and this we can try differently.
And your team? They can play with it. That's the advantage of prototyping instead of planning: your team gets excited when they see it working.
Examples of Prototypes We've Built
Case: Document Automation at a Law Firm
Idea: Can AI automatically read business documents and extract key data?
5-day prototype: Yes. We built a system with Claude API that read PDFs, extracted contract data (parties, amounts, dates) and put it in Excel. Not perfect – the AI sometimes missed nuances – but 85% automatic = huge savings on manual work.
What we learned: The AI worked fine, but the big problem was: who checks the output? For that you need a workflow, not just technology. Without the prototype, they would never have seen this.
Case: Lead-Scoring Chatbot at B2B Software Company
Idea: An AI chatbot that questions potential customers and then determines if they're "hot," "warm," or "cold."
5-day prototype: Working prototype. The chatbot asked the right questions, gave scores, integrated with their CRM.
What we learned: The technology worked perfectly, but the questions weren't right. Sales wanted to ask different things than what was in the original idea. Through the prototype, they learned in 5 days what they would never have discovered in 6 months of planning.
Case: AI Dashboard for HR Analytics
Idea: A dashboard showing which employees are likely to leave, who is most productive, where to invest in training.
5-day prototype: We built a simple dashboard with key data. Not pretty, not complete, but working.
What we learned: Much more data was needed than they had. The HR department had data in 5 different systems. And – this was big – line managers were afraid the dashboard would be used "against them."
Why Speed Matters
80% of what you do in 6 months of planning gets flipped when you start building anyway. Why not start building earlier?
A good prototype:
- Unmasks assumptions – what you thought was true turns out differently
- Helps descope – you see what's really hard and what you can let go
- Makes it tangible – abstract idea becomes concrete (and inspiring for your team)
- Gives confidence – when it works, you know: this is possible
Speed is also a mindset. It tells your team: we dare to start small and learn. We dare to fail, because it's a prototype.
What After Those 5 Days?
After prototyping you have three options:
- Build out – This works and delivers value. Now make it real/beautiful/scalable.
- Adjust – This works, but not as we thought. Try a different idea.
- Stop – This doesn't work or doesn't deliver value. That's ok, you know now early.
Many teams choose option 3 and are happy about it. Better 5 days wasted than 6 months.
Have an AI idea you want to test?
plaiwrks specializes in fast prototypes that actually work. We don't build to impress, we build to learn. Let's take your idea from paper to reality in 5 days.
View our AI prototyping approach →Written by Emma van Leeuwen
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