Software Engineering

Go from monolithic frontend pain to a fully deployed micro frontend architecture. A hands-on, production-focused guide to Webpack 5 Module Federation, ending with a complete multi-team app you build and ship yourself.

Deliver What Matters, When It Matters is a practical guide to delivery optimization for teams working in complex environments. Through real-world stories and actionable tools, it helps coaches, product managers, and delivery leaders close the gap between effort and impact.

Why learn one programming language when you can understand three at once? This book introduces the foundations of programming through a powerful side-by-side comparison of Python, Java, and C#, enabling readers to build strong conceptual understanding, transferable coding skills, and a solid pathway toward modern software engineering.

A leader at a company opens Slack one morning. The brief their virtual employee wrote looks normal: same headers, same prose voice, same cadence as every other brief that week. The last line ends mid-sentence. The API returned `stop_reason: "max_tokens"`. The system shipped it anyway. No exception. No log line. No retry. That bug doesn't look like the normal kind. This book is about why, and what to build instead.

You are not losing velocity because your engineers are slow. You are losing velocity because every line of untested code is a landmine your team laid for itself — and sooner or later, someone steps on it. This is the book that explains why. No syntax. No tutorials. Just the argument, the evidence, and the standard your team should already be held to. A 30-minute read that changes how you lead software quality forever.

A typed, signed-deliverable playbook for the enterprise-scale Oracle 19c → Azure migration. Across fifteen chapters, thirteen signed JSON deliverables chain end-to-end from Migration Assessment Bundle to Decommissioning Readiness Report. Defensible at a code review. Sign-off-ready for a director.

This book introduces screenshot testing (also called visual or snapshot testing): an automated approach that records a reference image of the expected design, then compares each test run against it to detect visual changes. It’s a natural complement to functional UI tests, which verify behavior but not appearance. The book focuses on the fundamental principles that apply to all frameworks. It works through the questions teams actually face: when to use screenshot tests and when not to, what to verify, which frameworks and tools fit your workflow, how to generate tests from preview functions in Jetpack Compose, how to integrate tests into a CI/CD pipeline, and how to optimize the whole process. By the end, you’ll be able to choose the framework that best suits your project and build a safety net that catches visual bugs before release. Every concept is demonstrated with a demo mood tracker application, with all code available online.

You adopted the agents. You kept the process. That is why it feels broken. AI agents do not need a better workflow. They need a methodology designed for them - one that starts before the first line of code and ends only when the system signals that something needs to change. ANSE is that methodology. Nine pillars. One unbroken loop. The next evolution of AI influenced development - Smarter not just Faster.

AI writes code faster than you can review it. This book gives you the gates: automated guardrails that catch bugs, enforce standards, and verify behavior before bad code reaches production. Stop being the last line of defense. Build the gates that catch the slop first, so you design and verify instead of proofread.

The chapter that grew into its own book: existential and universal restrictions, the correct VegetarianPizza pattern, and how OWL restrictions become EKA governance.

Most senior engineers don't fail AI systems interviews from lack of ability—they fail because they sound like builders when they need to sound like staff. This book gives you the answer flow, the system deep dives (RAG at billion-doc scale, agentic pipelines, token-cost tradeoffs), and the behavioral stories that earn L5/L6 offers at AI-first companies. Built for senior engineers targeting Staff AI Systems roles in the next 8 to 12 weeks.

Failure Driven Development Software Development Habits Haven't Caught Up to Cheap Compute. Design software the way electrical engineers design circuits — probes, test jigs, and a bowl of trusted parts — and field defects follow the same trajectory as hardware: toward zero.

Python Engineering Judgment is for engineers who already know Python and want to build the skill AI makes more valuable: the ability to reason about code, systems, tradeoffs, and failure modes. This deep, practical field guide teaches the Python object model, type system, decorators, generators, concurrency, asyncio, multiprocessing, API design, packaging, performance, debugging, security, observability, and reliability through the lens of real-world engineering judgment. Use it to prepare for senior, staff, principal, and tech-lead interviews, and to make better decisions in code reviews and production systems.

AI can write code faster than any human can review it. That changes the economics of engineering, but not what engineering is for. The bottleneck has moved from building to judging —and judgment cannot be prompt-engineered into a system designed for cheap proposals.

Stop being a 'Syntax Coder' and start becoming a 'Diagnostic Architect' by mastering the hidden mental models of software failure. This book teaches you how to own every logical branch of your system and eliminate bugs before they even happen. Stop guessing and start diagnosing.