#software-development
92 episodes · Page 2 of 4
#2463: Tmux vs Modern Terminals: What Multiplexing Actually Gets You
What multiplexing actually means, why tmux still matters, and how WezTerm and Ghostty changed the calculus.
#2459: Drizzle vs Prisma: Which ORM Wins for AI-Native Backends?
Comparing Drizzle and Prisma for AI-native backends, MCP servers, and the future of agent-centric development.
#2444: Custom IDs: UUIDs vs Human-Readable Keys
How to design database IDs that balance security, human readability, and performance — with lessons from Stripe and TypeID.
#2439: AI Collapses the Framework Decision
Why Airtable fails for multi-user tools, and how AI builders are changing the framework decision for small businesses.
#2435: The Hidden Difficulty of Data Modeling
Stop designing database schemas from scratch. Here's where to find ready-made templates for common business apps.
#2434: From Spreadsheets to Databases: The Mental Shift
Stop treating databases like bigger spreadsheets. Learn the one conceptual shift that actually matters.
#2356: Why AI Coding Needs Two Brains
Discover how specialized fast apply models streamline AI-powered code edits, cutting costs and latency while maintaining precision.
#2345: Why File Naming Conventions Are More Than Just Style
Discover how file naming conventions like snake_case and camelCase impact development workflows, CI/CD pipelines, and filesystem compatibility.
#2338: Who Keeps Matplotlib Running?
How does a team of just 15 people maintain Matplotlib, the backbone of global scientific visualization?
#2336: How ADRs Solve AI's Institutional Memory Problem
Architectural Decision Records (ADRs) aren’t just documentation—they’re a way to give AI coding assistants the context they lack.
#2327: Why AI Developers Chose Discord Over Slack
Discover why Discord became the go-to platform for AI developers, outpacing Slack with its community-first design and informal vibe.
#2287: Is AI Code Generation the Future of Low-Code?
Exploring the rise of AI code generation and its potential to reshape the low-code movement.
#2255: Typst vs. LaTeX: The AI-Ready Document Engine
Can Typst succeed LaTeX as the go-to tool for programmatic typesetting, especially for AI agents? We compare the two and explore what makes a docum...
#2207: Specs First, Code Second: Inside Agentic AI's New Era
As AI coding agents evolve from autocomplete to autonomous cloud workers, the bottleneck has shifted—now it's about how clearly you specify what ne...
#2169: How Enterprises Are Rethinking Agent Frameworks
Twelve major agentic AI frameworks exist—yet many serious developers avoid them entirely. What patterns emerge in real enterprise adoption?
#2168: What Serious Agentic AI Developers Actually Need to Know
Python, TypeScript, LangGraph, and the frameworks reshaping how agents work. A technical map of the skills and concepts that separate prototypes fr...
#2166: Code vs. Canvas: How Developers Pick Their Tools
LangGraph or Flowise? The honest answer isn't obvious. Developers gain speed and integrations with visual builders—but lose version control, testin...
#2111: From Bricklayer to Foreman: AI's Dev Role Shift
AI frameworks are exploding while languages stay stable. Learn why core dev knowledge is shifting from syntax to systems thinking.
#2109: AI Is Forcing You to Use React
AI tools are reshaping developer stacks, favoring React and Postgres over niche frameworks.
#2071: Git Can't Handle AI Agents—Yet
Three AI agents in one repo is pure chaos. Here's why Git's design causes collisions—and how worktrees and locks can save your sanity.
#2070: SemVer, Changelogs, and the Social Contract of Code
Stop breaking the internet. Learn the exact system developers use to release software without causing chaos.
#2059: When Your AI Agent Runs Stale Code
npx is silently running old versions of your AI tools. Here's why your updates vanish into a cache black hole.
#2043: From Wrappers to State Machines
Skip no-code traps. Learn the real stack for building agentic AI: Python, TypeScript, and Rust.
#2018: When Micro Frontends Actually Make Sense
The frontend monolith is a nightmare of coordination. Micro frontends promise autonomy, but is the operational complexity worth the cost?