Every backpacker knows the moment. Gear spread across the living room floor, a pack in the middle, and one question: will it all fit? Pack-fit answers that question before the packing starts. This post is about how and why we built it.

Why We Built It

We built Pack-fit as a short learning opportunity. We were given 3–4 days to plan, develop and release a site entirely from start to finish. The goal was more than a demo. It had to be a real, useful product that people could open and use on day one, and it had to show what a small team can deliver quickly when the work is focused.

Start With a Structured Plan

From this project we learnt a valuable lesson: the importance of a structured plan. When building a project alone, or entirely from a simple pitch, condensing your thoughts and concepts down is the first step to a successful project. When working on a project with AI, you are also trying to wrangle its thoughts. Thus, you must ground both yourself and the AI in a rigid plan.

That plan was built on a set of documentation rather than a single prompt or document. A product scope defined what Pack-fit would and would not do, decision records explained each major choice, and a set of working rules guided how the AI should build. Together, these documents kept the project on track. Every new idea could be checked against them, and whenever the AI drifted, they brought it back. In a project this short, the time spent writing things down was quickly earned back.

Simple Where It Counts

The plan also made it easy to change course. On day one, Pack-fit had a full backend: an API, a database and the infrastructure to run them. Checked against the scope, none of it was needed. The catalog is curated and read-only, and every check stands on its own, so we removed the backend and rebuilt Pack-fit to run entirely in the browser. That means no servers to maintain, no accounts to manage, and a site that is fast, inexpensive to host and private by design: each visitor's packing list stays on their own device.

Ambitious Where It Matters

Keeping the foundation simple left room for the parts that make Pack-fit stand out.

• A purpose-built fit engine. Litres are only half the story, so Pack-fit compares the shape of the gear with the shape of the pack, as well as the volume. If a bear canister is wider than a pack's published depth, the visitor sees it straight away.
• An interactive 3D sketch. Pack-fit draws one way the gear could sit inside the pack, with soft gear that squishes into gaps the way it does in real life. The sketch is built in background workers and starts preparing as soon as the visitor's pointer reaches "Add", so it keeps up as the list changes.
• Data people can trust. Every measurement comes from the manufacturers' published specs, covering packs and gear from 38 brands, and each figure is traced back to its source.
• A complete product. It includes a first-visit walkthrough, the visitor's own custom items, PDF and CSV export, a consent banner for European visitors, and automated tests that check every change.

Lock Down the Goal

Even for a fairly simple idea, it's incredibly important to put a foundation and safety net in place to really increase efficiency. Locking down your goal is the single most important piece of a successful project. It is what let Pack-fit go from a one-page pitch to a technically ambitious, purposeful product in a matter of days.

Have an Idea? Let's Build It

Pack-fit is a Launch Lab project from Appsquire. The same approach of a clear plan, a focused scope and careful engineering is how we work with our clients. If you have an idea you'd like to see built quickly and built well, reach us at info@appsquire.com.

Check out the project at https://pack-fit.app.