Flintstoning your way around hard technical challenges

Sometimes the best solution to a problem is to step around it.

When was the last time you butted your head against a technical challenge and had several failed attempts to solve it? Maybe it was due to limitations of the platform you’re using or limitations of your own technical ability. Or maybe it was just a really freakin’ hard problem to solve that is solvable via technical means but not ultimately worth the energy for doing so.

Sometimes the best solution isn’t to “beat the problem” so much as to side-step it with a human-powered solution. I’m going to show you a technique for doing this called “Flintstoning” and give you some guidelines for how to identify situations where a low-tech Flintstoned solution might make more sense than tackling the problem head-on.

What is Flintstoning?

Flintstoning is using human power under the hood to solve what would traditionally be a software-based problem. I first heard this term back in 2006 via Cambrian House . It’s typically used in the context of doing things in a decidedly-manual way early on in a startup for the sake of learning a process inside & out before you try to automate it . But it’s valuable in other contexts such as in the case where you have a particularly elusive technical challenge that meets a certain set of criteria.

When does it make sense to Flintstone?

If you can answer yes to these five questions it’s likely that your problem is a good candidate for a Flintstoning-based solution:

1. problem is particularly “fuzzy”
2. a human can do the task cheaply
3. easy to expose an interface
4. costs of solving via software-powered outweigh value of problem
5. does not need to be solved in real-time

Let me give you a concrete example of a good Flintstoning solution candidate from a comment on one of my recent YouTube videos :

This guy Tapan is asking if it would be possible to use my hack with browser-based automation for essentially doing periodic garbage collection clearing out unused photos in his database after a certain time period.

Browser-automation really isn’t the right tool for this. He needs the equivalent of a cron process that runs inAdalo and handles this but Adalo currently has no concept of time-based system generated tasks so he’s scratching his head trying to figure out how to automate this garbage collection process.

Rather than engineering a technical solution I suggested he just hire a virtual assistant (VA) to log into his app weekly and clean out the unused images in the database. Given how Adalo works with the ability for two apps to share the same database it’s trivial for him to create a special admin interface for his VA with heavily-restricted permissions that enables that person to handle this without creating any real security risk. With maybe two hours of work between recruiting and tasking the VA and writing a quick visual interface his garbage collection problem is solved with no more head butting. He’ll pay a few dollars each week in VA fees but has saved would could be a couple thousand dollars in dev work and has the problem handled immediately so it’s a massive win.

Considerations and tools

Obviously not every problem lends itself to being solved in this way but by going through your feature backlog and analyzing what’s on your plate dev-wise using the above five questions, you may find you can knock out a bunch of features using this technique in short order.

I have a few VA’s from Upwork on retainer in Slack with standing open hourly contracts and for situations like this I can simply record a Loom video and task them in situations like these. This works well for situations when there’s a bit of context required to understand and complete the task and it’s low-priority and infrequent work that’s required.

For situations where the work is more mindless, 24/7 and n