Techquarter

The AI tried six times to build it from scratch. Our engineer solved it with four words: just use a library.

The task was a drag-and-drop interface for organizing items in a hierarchy. Round after round, the AI tried to build it from scratch. Round after round, it fumbled.

Then he told it to stop and use an existing library. It immediately found a well-maintained open-source one, built by thousands of contributors, and the problem was solved.

The lesson from our AI roundtable: even when AI can build almost anything, the smartest move is often knowing what not to build.

AI makes writing code faster. It doesn't make every problem worth solving from scratch. That call is still human.

Read all the insights 🔗 https://buff.ly/jEqARNl

"The cloud will save us money."

Not on its own, it won't.

The platform makes savings possible. Decisions make them real: what moves, what gets right-sized, what gets switched off when nobody's using it.

Lower bills, less downtime, room to scale. That's the plan talking, not the platform.

Planning a migration? We broke down how to do it right, and what it costs when you don't, on the blog 🔗 https://buff.ly/FFfXCn2

Hiring a software team is a bit of a gamble. Only 1 in 200 projects hits all its targets.

But you can stack the odds in your favor. It comes down to the right team, the right scope, and asking the right questions upfront.

We broke down the full checklist, every question to ask and what a good answer sounds like, in our latest blog 🔗 https://techquarter.io/blog/software-development-partner-for-field-service/.

Can a mobile app really transform how your users engage with your platform?
For one education-focused NGO, the answer was a clear yes.

Faced with growing demand from mobile-first users, they turned to us to evolve their web-based recruitment platform.

Read the full case study on our website 🔗 https://buff.ly/eQJF55u.

After enough field service builds, you learn where projects tend to go sideways. Almost always, it traces back to scope that was fuzzy from the start.

So we scope four areas carefully before anything gets built. This carousel covers them, and the full checklist is on the blog: https://techquarter.io/blog/field-service-software-requirements-checklist/

Complex order flows called for a powerful solution.
We developed a cloud-native, multitenant platform for a virtual warehousing leader, ensuring seamless API, EDI and flat-file integrations and reliable scalability.

Read the full review 🔗https://2ly.link/25Y3L.

A fixed alarm limit only reacts once a machine is already over the line. By then the failure isn't coming, it's here.

AI works differently. It learns each machine's normal rhythm, notices the slow drift toward failure, and tells you what to fix first: Pump A in 2 days, Motor C this week, Fan B can wait.

That means no more scrambling over every alert like it's an emergency, and no more finding out when tenants are already calling.

Want the deeper dive? Read the full article on our blog 🔗 https://techquarter.io/blog/predictive-maintenance-software-for-field-service-companies/

Picking a software partner is one of those decisions that looks simple until you're six months in and something isn't going the way you expected. Most of the risk shows up early, in the questions you either asked or didn't during those first conversations.

We put together four we think matter most. Who actually owns the code and IP when the project wraps. How a team handles a feature that turns out harder than anyone quoted. Whether they'll ship something small first or push for one big contract. And how they think about security and where your data lives.

None of these are trick questions. A good partner will have clear answers ready. The ones who get vague or defensive are telling you something useful too.

We go deeper on all of this in our full guide to choosing a software partner 🔗 https://buff.ly/31nnGC6.

We asked a client's CTO what most companies get wrong about AI.

Not the tools. Not the budgets.

Fear.

Fear of experimenting. Fear of letting AI touch anything that matters. And in this market, that instinct quietly backfires: a prototype that once took months now takes days.
The failed experiment barely costs a thing.

So, honestly, what's the one AI experiment your team keeps finding reasons not to run?

Fear was just one of the hard questions on the table. The rest are in the full write-up 🔗 https://techquarter.io/blog/you-have-to-trust-the-model-notes-from-our-ai-roundtable/.

Some problems don't have an off-the-shelf answer. Building the answer is what we do.

Take golf facilities: availability, memberships, and booking rules complex enough that generic tools just break.

For our client we built Registry Golf, a platform that handles the whole operation in one place.

Read the full case study 🔗 https://techquarter.io/our-work-the-registry/.