explainx / blog
Product managers can now build real working prototypes, internal tools, and data dashboards without writing a line of code — using AI coding tools. Here is exactly how to do it, what to build, and what to hand off.
Jul 9, 2026
If AI's job on your product team is recapping standups, you're leaving most of the value on the table. Here's how PMs are using AI for specs, research synthesis, prototyping, and scoping AI-powered features in 2026.
Jun 28, 2026
Four serious tools now compete for the same territory: no-code and low-code AI workflow building. Langflow, n8n, Make, and Flowise are not interchangeable. This comparison breaks down what each tool actually does well, where each one falls short, and gives you a three-question framework to pick the right one for what you are building in 2026.
Jun 22, 2026
Shortlist of 20 explainx.ai prompt generators for Product Management, spanning audio, text modalities and 9 high-level categories.
Product managers spend enormous amounts of time translating ideas into words — PRDs, specs, wireframes, Figma mockups — and then waiting for engineers to translate those words back into something clickable. Most of that delay is avoidable.
With AI coding tools, a PM can now go from idea to working interactive prototype in hours — without writing code. Not a Figma mockup. A real thing that runs in a browser, responds to clicks, and can be shared with a URL.
This guide is specifically for PMs: what to build, what tools to use, how to prompt, and how to connect your vibe coding work back to your engineering process.
For the consumer social version of vibe coding — Meta's Pocket app with prompt-built mini-games — see Meta Pocket: Vibe-Coded Gizmos. Pocket targets phone toys in a feed; this guide targets prototypes PMs hand to engineering.
You validate faster. Running a prototype past 5 users in a day beats two weeks of PRD review.
Your specs improve. Building something forces you to answer questions you didn't know you had — what happens if the field is empty? what does the error state look like? Engineering teams write less back-and-forth when the spec was written by someone who tried to build it.
You unblock yourself. Internal tools, dashboards, data pulls — things that would sit in the backlog for quarters can now be built in a day.
You earn engineering trust. PMs who understand what's hard to build (because they tried) write better trade-off decisions. Engineers notice.
Start with things that are entirely yours to build — internal tools, prototypes for user research, exploratory dashboards. Not production code.
| Build this | When |
|---|---|
| Interactive prototype of a new feature | Before writing the PRD — use it to align stakeholders |
| Landing page for an A/B test | For marketing tests that don't need backend logic |
| Internal dashboard (metrics, status board) | When eng backlog is full but you need the data |
| User research stimulus | A fake version of the product to test reactions |
| Script to clean or analyse a data export | Instead of copying 500 rows into a spreadsheet manually |
| Admin tool for customer ops | Simple CRUD interface your support team needs |
| Changelog / release notes page | Public-facing, fast to ship |
Cursor is the easiest entry point. It looks like VS Code — a code editor — but has AI built in that writes code from your descriptions.
Install it from cursor.com. Free tier is enough.
The key mode for PMs is Composer (Cmd + I on Mac, Ctrl + I on Windows): type what you want to build, press Enter, watch it create files.
If you want to give a bigger task and come back to a result, Claude Code (a terminal tool) can run longer sessions. Install:
npm install -g @anthropic-ai/claude-code
Then claude in any folder to start a session.
Let's build an interactive prototype of a new onboarding flow — the kind you'd normally sketch in Figma and then explain to 3 different people 5 different ways.
Open Cursor. Create a new folder. Open Composer (Cmd + I). Type:
Build a 3-step onboarding flow for a B2B SaaS product called "Trackr"
— a project management tool for remote teams.
Step 1: "What's your team size?" — 4 options as clickable cards:
Solo, 2–10, 11–50, 50+
Step 2: "What's your main challenge?" — 4 clickable cards:
async standups, task visibility, deadline tracking, team communication
Step 3: "You're all set" — personalised summary based on their answers.
e.g. if they chose "11-50" and "async standups", show:
"Trackr will help your mid-sized team cut standup time by 80%"
Single HTML file. Clean modern design. Dark background, white text,
blue accent (#3b82f6). Progress bar at the top. Back/Next buttons.
No external dependencies.
It writes a single index.html. Open it:
open index.html
You now have a clickable prototype to put in front of users today.
PM prompts are different from developer prompts. You care about behaviour, user experience, and edge states — not implementation details.
Describe the user's experience, not the code:
When the user clicks "Submit" with an empty email field,
show a red error message directly under the email input
that says "Please enter a valid email address".
The Submit button should not do anything until all required fields are filled.
Reference real product context:
This is a dashboard for our internal customer success team.
They need to see: customer name, plan tier, MRR, days since last login,
and a health score (1-5). The table should be sortable by any column.
Rows with health score 1-2 should have a red left border.
Describe the state, not the logic:
After the user saves their profile, show a green banner at the top
for 3 seconds that says "Profile updated" then disappears.
Don't navigate away.
Iterate with specifics, not "make it better":
The card layout looks cramped. Give each card 24px padding,
add 8px gap between them, and make the card title 18px instead of 14px.
This is the PM superpower — a custom dashboard that would otherwise sit in engineering's backlog.
Open a new folder in Cursor. Open Composer:
Build an internal metrics dashboard HTML page.
Data to display (hardcode sample data for now):
- 3 summary cards at the top: "Active Users" (2,847),
"New Signups This Week" (142), "Churn Rate" (1.8%)
- A table below showing 8 customers: columns are
Company, Plan, MRR, Last Login, Health Score (1-5)
Health scores 1-2 show red, 3 shows amber, 4-5 show green
- A simple bar chart showing weekly signups for the last 8 weeks
(use SVG, no chart library)
Design: clean, professional, dark theme. Font: system-ui.
No external dependencies. Single HTML file.
When it's done, open it. Then iterate:
Add a filter row above the table with dropdowns:
"All Plans" (Pro/Starter/Enterprise) and "All Health" (All/At Risk/Healthy).
Selecting a filter should instantly show/hide rows without a page reload.
You now have a filterable dashboard. Share the file by uploading to tiiny.host — free static hosting, get a URL in 30 seconds.
PMs live in spreadsheets. This replaces hours of manual work.
Say you have a CSV export of user sessions. Open Claude Code in your terminal, point it at the CSV folder:
claude
Then describe the analysis:
I have a CSV called sessions.csv with columns:
user_id, session_date, feature_used, session_duration_seconds, plan_type
Write a Python script that:
1. Loads this CSV
2. Shows average session duration by feature_used
3. Shows which features are used most by Pro vs Starter plan users
4. Flags any users who haven't had a session in the last 14 days
5. Outputs the results to a readable summary in the terminal
Then run it.
It writes the script, runs it, you read the output. What would have taken 90 minutes in Excel takes 5.
For user research: Test your prototype with real users before writing any spec. Use Maze or UserTesting — upload your HTML file or share a URL. Get behavioural data before you commit engineering time.
For stakeholder alignment: Show, don't tell. Put the prototype in your next review meeting instead of Figma. Stakeholders ask better questions when they can click something.
For engineering handoff: Share the prototype alongside your spec as a behavioural reference — not as implementation guidance. Say explicitly: "This shows what I mean by the experience. The actual implementation will differ." Engineers can use it to align on states and edge cases.
For PRD writing: Build the prototype first, then write the PRD. You'll write it in half the time and catch 80% of the questions engineering would have asked.
Don't try to make your prototype production-ready. The moment you start worrying about code quality, test coverage, and database schemas, you've left PM territory. That's engineering work.
Don't skip the handoff conversation. Engineers sometimes receive a vibe-coded prototype and feel pressure to build from it. Pre-empt this: "this is a prototype to communicate intent, not a starting point for code."
Don't debug alone for too long. If something isn't working after two attempts at describing the fix, paste the exact error message and let the AI diagnose it. Don't try to read the code yourself and fix it manually.
Don't build things that need real security. Anything handling real user data, payments, or authentication needs proper engineering. Vibe-coded prototypes are for exploration and communication.
Pick one per day:
After five sessions, you'll have a workflow. The sixth is where it becomes fast.