The Hello Spark Method
We’ve been lucky to build for a wide variety of businesses, jet brokers, medical billers, therapy practices, machine shops, and almost every job has meant working inside a process nobody had written down. Over those jobs we’ve settled into a way of working that holds up, and it comes down to five commitments.
We wrote this page for ourselves first. It’s what we use to train anyone who builds with us, and we rewrite pieces of it whenever a job teaches us something.
It’s public because you should be able to see how we work before you decide to work with us.
We take the time to understand the work before we design anything
How a business describes its process and how it actually runs are rarely the same. So we start by sitting with the people who do the job and going through it a step at a time. The exceptions they’ve stopped mentioning are usually where software breaks, and this is the cheapest moment to find them.
We tell you when something isn’t worth building
If something off the shelf already covers it, or a build won’t save more than it costs, we say so. When it is worth building, you get one flat quote. Scope and price are agreed before any code, and nothing is billed hourly, so nobody has a reason to take longer than the job needs.
You see working software the whole way through
We build the riskiest part first and run it on your own data, because a prototype that survives your worst document tells you more than a specification ever will. From there you watch the system take shape, which is the only reliable way to catch a misunderstanding while it’s still cheap to fix.
We’re careful about where AI makes decisions
A model is good at judgement calls on messy input, so that’s the job it gets. Everything it touches is split into steps we can check. Anything that has to be exact, totals, dates, whether two records match, runs in code. And anything expensive or hard to undo stops and waits for a person.
We build for the day something breaks
Getting software working once is the easy part. Permissions, backups, error handling and what happens when something fails at 2am are what make it something your business can run on. That work is invisible in a demo, and it’s most of the job.
To see what this looks like on a real job, read about the spec sheet pipeline we built for Smarter Aircraft. They’d already tried it with off-the-shelf AI tools and got something that looked right and came out different every run. Better prompting wasn’t the fix.
