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Beep & Boop

Helping founders create a mascot they can use beyond a single image.

Before I became a product designer, I spent a lot of time drawing characters. I’ve always loved how a good mascot can give a brand personality and make it instantly recognizable. But commissioning one can be expensive, especially for a startup.

The Beep & Boop homepage: “Every brand deserves a face,” with polaroid-style renders and a handwritten character brief pinned to a grid

While AI makes generating a character easy, getting that same character to look consistent across different poses and expressions is another challenge.

So I built Beep & Boop, a character design studio where anyone can create a mascot, refine it, and leave with a kit they can actually use.

beepandboop.com
Role
Product designer, builder
Timeline
July 2026, ongoing iteration
Models
Claude (development)
Status
Live. One-time packs at $19 and $34

01 / ORIGIN

Creating consistent characters that brands can build stories around.

Before I became a product designer, I spent a lot of time drawing characters. I’ve always loved how a memorable character can give a brand personality and become part of its identity.

AI makes creating a character surprisingly easy. The harder part is keeping that character recognizable across different poses, expressions, and situations.

That’s where Beep & Boop started. I wanted to build a character design studio that went beyond generating a single image, giving brands a consistent character they could keep using and build stories around.

02 / EXPERIENCE

Designing a studio, not another prompt box

I wanted Beep & Boop to feel like sitting down at a character designer’s desk, not staring at an empty text field.

The experience guides people through visual decisions about their character’s appearance, personality, and style. Once they’ve created something they like, they can refine it, lock the design, and generate a twelve-image contact sheet.

The challenge was making the process feel approachable while giving people enough control to create a character that felt like their own.

03 / DECISIONS

Getting the details right

Some of the most important improvements came from using Beep & Boop as a customer.

The original builder relied on text fields, so I introduced a guided experience. But the model implemented it as a second, competing builder. I brought everything back into one flow.

Later, I discovered that completing a purchase could send someone back to an empty character brief. I fixed the handoff so people could pick up exactly where they left off.

Both problems reminded me that a feature can work technically and still create a poor experience.

Beep & Boop is live, with free character previews and one-time purchases for complete character kits.

As with several of my other projects, the biggest challenge now is distribution. I want to get it in front of founders and small businesses who could benefit from having a distinctive character but might not have considered creating one.

Building the experience was one challenge. Learning how to find its audience is the next.

From idea to production, with AI as a collaborator.

Glossy black robot character with glowing eyes

Discover

Understand the problem

  1. Step 1: Frame the idea

    Problem, audience, desired outcome

  2. Step 2: Explore together

    Questions, alternatives, tradeoffs

  3. Step 3: Validate assumptions

    Research, feasibility, evidence (AI research - I decide)

Define

Set the direction

  1. Step 4: Define the product

    Requirements and success criteria

  2. Step 5: Plan the work

    Milestones, tasks, acceptance tests. AI drafts

  3. Step 6: Approve the plan

    I revise scope before work begins. My approval.

Deliver

Build, verify, release

  1. Step 7: Build + review loop

    Implement, agent audit, fix, recheck (AI and agents)

  2. Step 8: Connect + test

    Services, env setup, staging QA

  3. Step 9: Ship + learn

    I approve release; we iterate. My approval

I use AI throughout the product development process, from exploring an idea and challenging assumptions to defining requirements, building, and reviewing the implementation.

But I don’t want a model that simply agrees with me. I expect it to question decisions, identify tradeoffs, and provide evidence that the work actually functions.

I review the plan, direct the experience, and use independent agents to help verify the implementation. Before release, I test the product and make the final call.

AI makes it possible to move much faster. My responsibility is making sure we’re moving in the right direction.