Dynamic programming is usually taught with mutable arrays and index arithmetic — Kotlin’s generateSequence and sequence { } let you express the same recurrences as infinite, lazily-evaluated streams. Background Classic dynamic programming (DP) involves filling a table bottom-up: allocate an… Continue Reading
Kotlin has always marketed itself as functional-friendly, but until the K2 compiler era, inline lambdas had a subtle second-class limitation that forced awkward workarounds in functional-style code. Background Functional programming in Kotlin relies heavily on higher-order functions and lambdas —… Continue Reading
JetBrains Koog: A Kotlin-Native Agent Framework That Skips the Python Tax If your backend is Kotlin or Java and you want to add AI agents, you’ve been forced to either wrap a Python service or accept a framework that treats… Continue Reading
Writing shared business logic once and shipping it to both Android and iOS turns out to be far less painful than I expected. Background The premise of Kotlin Multiplatform (KMP) has always sounded attractive: define your data models, network layer,… Continue Reading
Swift 6.3’s @c Attribute: Replacing @_cdecl and Making C Interop a First-Class Citizen For a decade, exposing Swift code to C required an underscore-prefixed, unsupported hack — Swift 6.3 finally makes it official. Background Swift has always been able to… Continue Reading
With Xcode 26.3, Apple quietly unlocked something big: native support for the Model Context Protocol (MCP). It’s an open standard that lets AI agents plug directly into Xcode and actually use it — not just suggest code. Tools like Claude Agent and… Continue Reading
The real AI shift for iOS engineers isn’t about ChatGPT generating SwiftUI views. It’s about the Model Context Protocol (MCP) — an open standard that allows AI agents to directly operate your development tools. Building apps, running simulators, deploying to… Continue Reading
Despite the excitement around autonomous coding agents, the highest-leverage way to use LLMs today is deliberately — staying in the loop. That will change as AI improves, and eventually your role will shift to defining the what and the why. But we aren’t… Continue Reading
One of the most profound changes AI brings to development is a fundamental paradigm shift in how expertise works. Traditionally, becoming effective in a domain—whether frontend, backend, infrastructure, or data—required years of focused specialization. Today, AI tools are collapsing those… Continue Reading
Vibe Coding by Steve Yegge and Gene Kim introduces a transformative approach to software development, where programming evolves from a solo, syntax-heavy task into a collaborative, high-speed partnership with artificial intelligence. This method, called vibe coding, allows developers to express their intentions… Continue Reading