BlogField notes · by the team at Pirxey

Notes from the launch pad. How we ship software that works.

Articles from the team — AI productivity, software business, MVP delivery, and how we pick partners over vendors. Written by engineers who ship, not consultants who slide-deck.

Business

5 min read

The Growing Trend of Embedded Finance: Why You Shouldn't Ignore It

Embedded finance is quietly reshaping how customers pay, borrow, and insure. Learn the six types, where businesses lose money, and how to catch the shift.

Business

3 min read

Loan Marketplace MVP: What Should Be Built First and What Can Wait?

Learn which five features a loan marketplace actually needs at launch, what can wait, and how to sequence the build so your budget proves the core match engine first—instead of funding mobile apps and servicing tools before anyone knows the model works.

Business

4 min read

How to Choose a Software Partner for a FinTech Product Without Increasing Regulatory and Delivery Risk

Most FinTech systems fail at fragile integrations, not bad code. Learn the 5 criteria and the one question that separate a true FinTech software partner from a risky vendor.

Leadership

5 min read

It's Not About Clicking Faster, It's About Expanding the Range of What Gets Done

AI's real value is not faster execution but expanding what teams can reasonably explore, prepare, and understand — and the new bottleneck that creates around judgment.

Leadership

6 min read

When AI makes product decisions look cheaper than they are

AI rarely removes the cost of a product decision. It redistributes it — across teams, across reviewers, across edge cases nobody owns. A look at why so many AI features pass adoption while quietly making the organisation more expensive to run.

2 min read

AI Doesn't Take Jobs. It Takes Away Excuses.

AI doesn't care. It doesn't reward struggle. It rewards clarity. And clarity is rare. What disappears first is not work, but cover.

5 min read

Building AI Products Before the Organization Is Ready

Most AI products fail not because the model is weak, but because the organization hasn't decided who owns the risk, what errors are acceptable, and where the downstream cost will land.

4 min read

AI Agents Are Not Just Changing Tools. They Are Redefining Accountability.

The real question is not what AI agents can do, but what happens to accountability once a system is no longer assisting work but actively participating in execution.

Why we write. And what you'll find here.

Lessons from shipping.

Every post comes from real client work. Not thought leadership — what actually happened, what we learned, what we'd do differently.

Opinionated, not neutral.

We have takes — on MVPs, on AI tooling, on how to pick a software partner. You'll know where we stand, with reasons.

Practical, not academic.

Every article ends with something you can use — a checklist, a question to ask, a code snippet. Read it, apply it, ship.

Want us to write about something specific?

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