How to Build a Portfolio Project That Doesn't Look Fake

Why do most portfolio projects look fake to hiring managers?

Because they ignore business reality. The classic portfolio move — redesigning a famous consumer app — is what Aliena calls a fake project: it skips competitive context, revenue viability, and market analysis entirely. Hiring managers read this instantly as evidence that a designer lacks business sense. A beautiful redesign with no commercial reasoning behind it signals you can push pixels but can't think about impact.

The root cause is a shrunk First Diamond — the problem space. When you jump straight into Figma, you've skipped the divergent research and business validation that make a project defensible. The fix is to expand the First Diamond aggressively using AI before you touch a single screen.

How do I use AI to validate a portfolio idea?

Before opening Figma, run at least three to five product ideas through AI. For each one, prompt ChatGPT or an equivalent to produce:

1. A market analysis — who's competing, what gaps exist, where the opportunity is.

2. A revenue model design — how the product would actually make money.

3. A revenue prediction — a rough sense of the commercial upside.

Repeat this for every candidate idea, then select the one with the strongest business case. This is the opposite of falling in love with your first idea. You're diverging across options and converging on the most credible one — the First Diamond working as intended.

Why should a portfolio project have a PRD, not just a brief?

A design brief carries only the user perspective. It omits business goals and technical constraints, and that omission is exactly what makes personal projects feel fake. Use AI to draft a PRD (Product Requirements Document) that defines business objectives, success metrics, scope, constraints, dependencies, and risks.

The PRD becomes the anchor for all your solution-space work, and it demonstrates systems thinking — the ability to reason about the whole product, not just the interface. When a hiring manager sees a PRD behind your portfolio piece, the 'fake project' read disappears.

Where does AI stop and my own work begin?

AI accelerates validation, PRD drafting, content generation, and documentation. It does not replace primary research. If your portfolio project claims user insight, that insight must come from first-hand contact — real interviews, real observation. Searching online or asking a chatbot is not primary research, and reviewers can tell the difference.

Use AI to draft stronger recruiting emails and sharper interview questions, and to convert your rough notes into clean annotations. But the synthesis, the judgment, and the story you tell about what you learned — those stay with you. That's what makes the case study yours.

How do I document the project so it becomes a strong case study?

Every undocumented iteration is a liability. Keep your latest version at the top of your Figma file and allocate one page per major iteration. On each page, annotate what changed, why, and who gave the feedback. Use ChatGPT to turn rough notes into clean point-form annotations.

This documentation is your case study raw material. When a reviewer asks 'have you tried X?', you have a documented answer. When you write up the project, the narrative of divergence, decisions, and iteration is already captured.

What's my next step?

Pick three to five product ideas you're genuinely interested in. Before opening Figma, run each through AI-assisted market analysis, revenue modelling, and revenue prediction. Select the strongest, draft a PRD with AI, and only then begin designing — documenting every major iteration as you go. You'll finish with a project that reads as commercially credible and a case study that defends itself.