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20 Portfolio Project Ideas That Show Real Skills

Twenty portfolio project ideas for developers, designers, data and product people, with what each shows an employer, the first version and the hard part.

Mythex Team · 2026-10-22 · 6 min read

The best portfolio project ideas solve a real problem for a real person, show one or two skills clearly, and are finished: live, documented and explainable. Reviewers spend a few minutes per portfolio, so a working app for a real user (a club's booking system, a dashboard of public data, a redesign with research behind it) beats another clone of a famous product. Below are twenty ideas grouped by role, each with what it shows, the first version to build and the honest hard part.

All of these work as a web app or site you can link to. Once you have three or four, how to build a portfolio website covers how to present them.

What a strong portfolio project has

Front-end developers

1. Accessible form library demo

• Shows: Semantic HTML, keyboard support, error messages, screen reader testing.
• First version: Five common form patterns (sign-up, address, date range, file upload, multi-step) built properly, with a page explaining each accessibility choice.
• Hard part: Testing with an actual screen reader, not just an automated checker. How to make your website accessible has a checklist.

2. Recreated real-world page, then improved

• Shows: Layout, responsive design, attention to detail.
• First version: Pick a public page with a clear problem (a confusing timetable, a cluttered menu), rebuild it, then publish a version that fixes the problem, with before and after.
• Hard part: Respect. Use your own text and images, label it a concept, and don't copy logos or present it as the company's work.

3. Data-heavy table that stays fast

• Shows: Performance, sorting, filtering, pagination, loading states.
• First version: A table of 10,000+ rows from a public dataset with search, filters and saved views.
• Hard part: Measuring. Show load times before and after your changes.

4. Offline-friendly checklist app

• Shows: Service workers, local storage, sync when back online.
• First version: Checklists that work with no signal and sync when the connection returns. Native vs progressive web apps explains the options.
• Hard part: Sync conflicts when two devices edit the same list.

Full-stack and back-end developers

5. Booking system for a real small business

• Shows: Data modelling, login, emails, time zones, edge cases.
• First version: Services, availability, bookings, confirmation emails and an admin view. The booking builder can set up the basics so you can focus on the hard rules.
• Could earn: If the business uses it, a small monthly fee.
• Hard part: Double bookings and cancellations. Write about how you prevented them.

6. Multi-user client portal with roles

• Shows: Authentication, permissions, file uploads, security thinking.
• First version: Clients log in to see only their own files and messages; staff see everything. See how to build a client portal and the portal builder.
• Hard part: Proving one client can't see another's data. Include your tests in the write-up.

7. Inventory tracker with an audit log

• Shows: Relational data, history tables, reports.
• First version: Items, stock movements, low-stock alerts and a log of who changed what. Start from the inventory builder.
• Hard part: Keeping counts correct when two people update stock at once.

8. Public API with docs

• Shows: API design, validation, rate limiting, documentation.
• First version: A small API over a dataset you care about, with keys, limits and a docs page. How to build a REST API covers the shape.
• Hard part: Good error messages. They're what users of an API notice most.

9. Background job pipeline

• Shows: Queues, retries, scheduled work, monitoring.
• First version: An app that imports a CSV, processes it in the background, and emails a report when done. See how to run background jobs.
• Hard part: Failure. Show what happens when a job fails halfway.

Data and analytics

10. Public data dashboard with a question

• Shows: Cleaning data, choosing charts, telling a story.
• First version: One public dataset, one clear question ("Which bus routes run late most often?"), three charts and a written answer. The dashboard builder handles the layout.
• Hard part: Saying what the data doesn't show. Note gaps and caveats.

11. Personal spending analysis

• Shows: Categorisation, time series, privacy awareness.
• First version: Import a bank export (use sample or anonymised data in the public version), auto-categorise, and show trends.
• Hard part: Never publishing real financial data.

12. Small business KPI tracker

• Shows: Translating business needs into metrics.
• First version: For a friend's shop or club: five metrics they actually ask about, updated from a spreadsheet. How to connect Google Sheets to your app covers the link.
• Hard part: Picking metrics with the owner rather than for them.

Designers

13. Redesign with research

• Shows: User research, problem framing, iteration.
• First version: Interview three users of a local service's site or app, find one problem, and design and test a fix. Present findings, not just screens.
• Hard part: Getting real users. Three short conversations are enough; how to do customer interviews helps.

14. Design system for a small product

• Shows: Consistency, components, documentation.
• First version: Colours, type, spacing, ten components with states, and a live page showing them in use.
• Hard part: Showing it in a real product, not just a sticker sheet.

15. A working prototype, not just mockups

• Shows: That you understand how designs behave with real data.
• First version: Take one of your design projects and build it as a working web app, even a small one. An AI app builder like Mythex can turn your description into a working app with a live preview, which lets you test with real data and real users.
• Hard part: Being honest about what you built yourself and what a tool generated.

Product and no-code roles

16. Problem-to-launch case study

• Shows: Discovery, prioritisation, shipping.
• First version: Find a small problem in a group you're part of, write a one-page spec, build the simplest fix, launch it and measure use. How to write a product requirements doc with AI has a template.
• Hard part: Measuring anything real. Even "12 of 20 members used it in week one" is a result.

17. Internal tool that replaces a spreadsheet

• Shows: Process thinking, change management.
• First version: Turn a messy shared spreadsheet at a job, club or charity into a simple app. See how to turn a spreadsheet into an app.
• Hard part: Getting people to switch. Write about what you did to get them to.

18. Feedback portal with a public roadmap

• Shows: Gathering and prioritising user input.
• First version: Users submit and vote on ideas; you mark them planned, in progress or done. See how to build a customer feedback portal.
• Hard part: Saying no in public.

AI-focused projects

19. AI tool for one narrow job

• Shows: Prompt design, cost awareness, handling bad output.
• First version: One task done well, such as turning a recipe into a shopping list, with saved results and a way to correct mistakes. How to use LLM APIs covers keys and costs.
• Hard part: Showing how you evaluated it: ten test inputs and how many it got right.

20. Search over your own documents

• Shows: Retrieval, chunking, citing sources.
• First version: Upload a set of public documents (a club's rules, a game's manual) and answer questions with links to the source passage. What is RAG explains the approach.
• Hard part: Admitting when the answer isn't in the documents.

How to finish and present a project

1. Pick a real user before you start. A friend, a club, a former employer, yourself.
2. Ship a small version in two weeks, then improve it based on what the user says.
3. Put the code in Git. Even if you started in an AI builder, export it; how to use Git with an AI-built app shows how. (On Mythex, code export and GitHub are on the Pro plan.)
4. Read and understand the code. If an AI wrote parts of it, how to review AI-generated code helps you get to the point where you can explain it in an interview.
5. Write it up. Problem, user, what you built, key decisions, what broke, what's next. One page.
6. Keep it live. A broken demo link is worse than none. Check your links before each application.

For more ideas that aren't aimed at employers, see side project ideas you can build with AI or web app ideas.