Umar Abdullah.

Built Entalogics into a cybersecurity and software engineering company. 11+ years in software engineering. Made the jump to AI-augmented delivery in 2023 — with the security discipline to make generated code survive production.

Read the founder story

I spent over eleven years writing software the slow way. Then AI got good enough to change that — and most agencies kept doing things the slow way anyway.

Umar Abdullah, CEO & Founder of Entalogics

5.0 Client Rating30 Under 30

CHAPTER 01

The old reality

I've been building software for over 11 years.

For most of that time, the process looked the same everywhere: hire developers, write code manually, line by line, file by file. A project with 50 screens meant 4-5 months. A SaaS platform with payments and dashboards meant 6 months minimum. A custom Chromium browser meant a year or more — not because developers were slow, but because every component had to be hand-coded from scratch.

I built hundreds of projects this way — web apps, mobile apps, desktop applications, SaaS platforms, custom browsers. The process worked. It just hadn't fundamentally changed in over a decade.

CHAPTER 02

The turning point

Then in late 2022, something shifted.

AI coding tools started becoming genuinely usable — not perfect, not replacing developers, but useful in ways that changed how fast a skilled engineer could work. I started experimenting: code generation first, then AI-assisted architecture planning, testing, documentation.

AI doesn't replace good engineers. It makes them dramatically faster.

CHAPTER 03

What AI handles vs. what engineers decide

The math completely changes when you split the work right.

AI accelerates

Boilerplate code that used to take a week now takes hours. Test cases can be generated automatically. Documentation can be produced as part of the workflow.

Engineers decide

Business logic, scalable architecture, feature prioritization, security decisions, and edge-case handling still require senior engineering judgment.

That's what senior engineers do. And when you combine a senior engineer's judgment with AI's speed - the math completely changes.

CHAPTER 04

Browser Developers

Chromium has been at the center of Umar's work since 2015. Over the years he has built and maintained custom browsers for security companies, crypto and privacy products, and enterprise teams, including hardened browsers, white-label builds, and long-term Chromium version porting.

In 2026, that browser work got its own home: Browser Developers, a specialist browser engineering consultancy where Umar serves as Chief Browser Architect. EntaLogics stays focused on AI-augmented software development and cybersecurity, while Browser Developers takes on custom Chromium and Firefox browsers, white-label browsers, extensions, desktop apps, and Chromium fork maintenance.

Same senior engineers, now with a dedicated team for browsers.

Visit Browser Developers

CHAPTER 05

Why Entalogics was built

I knew the development industry was about to change fundamentally.

Most agencies were still billing for manual labor — charging clients for the time it takes a developer to type code. If AI handles 40-60% of that typing and the process doesn't change, clients are paying for work that isn't being done by hand anymore.

That's when I started Entalogics.

Not as another dev shop, but as a company built from the ground up around AI-augmented development — every engineer using it across the full lifecycle, architecture through documentation. I took everything I'd learned from 11 years and hundreds of projects and rebuilt the process around one question:

“If AI handles the repetitive work, what should engineers actually spend their time on?”

The things that determine whether a product succeeds or fails: architecture, business logic, security, scalability, edge cases, code review.

The 30% of the work that's responsible for 90% of the outcome.

That's what Entalogics does differently. We didn't bolt AI onto an old process. We built a new process around AI from day one.

The difference

What changed when we built around AI.

The same quality. Fundamentally different speed. This is what a 600-project pattern recognition looks like when you stop billing for typing.

Area

Boilerplate code

− Before (traditional)

Written manually, 1-2 weeks per module