Using Claude Code as the orchestrator and Codex as the engine gives you the best of both tools: Claude's UI, Codex's depth, and minimal Claude token spend. The economics only work when the task is big enough to justify two layers.
The bottleneck in software engineering has shifted from typing to understanding. As AI handles implementation, engineers who thrive will be those who recognise patterns, curate guardrails, and connect technical decisions to business outcomes.
Five types of documentation, five different AI leverage stories. The question isn’t whether to involve AI in your docs; it’s where each type belongs and how much maintenance you can hand off.
Pairing with an AI feels like pair programming. It isn't. There's one prior in the room, and it's trained to agree. This post makes the case for mob programming and spec-driven development as the structural fix.
Errors don't just happen; they land somewhere. Validation, generic, idempotent ignore, warning log, or Sentry: each routes failure to a different audience. Get the routing wrong and either engineers go blind to real bugs, or state corrupts silently.
Auditing data-heavy companies reveals the same pattern: asynchronous data processing crammed into the synchronous web stack. The contention shows in performance, delivery, and team dynamics. Isolation fixes all three.
Cheap consumer devices from Amazon and BestBuy ship with factory-installed malware and botnet software. The Zero Trust principle isn’t paranoia; it’s the only safe assumption for any network you don’t fully control.
Your codebase degrades the same way shared resources do: not from malice, but from missing governance. Elinor Ostrom proved the commons can survive. Her principles map to software teams with uncomfortable precision.
Business users love Lovable. Engineers tend to panic. A real-world case study of how to wrap an AI builder in guardrails so non-technical teams can move fast without quietly rewriting the systems that give your product its edge.
I used to teach people to code. And looking back, I was teaching students to write it by hand while the tools that write it for them were getting better every single month. So what should a coding classroom actually look like now?
Every legacy codebase is a palimpsest: layers of decisions written on top of each other, none fully erased. Geoffrey Dhuyvetters argues that what looks like technical debt is often stratigraphy, and you read it before you rewrite it.
The claude -w flag spins up an isolated git worktree in seconds, so you can keep coding while a long-running task occupies your main session. No conflicts, no context pollution, no waiting.
In 2010, every business convinced itself it needed a mobile app. Fast forward to 2025, and the script is identical, just with AI replacing mobile as the technology everyone insists they can't afford to be without.
The quick fix isn't cheaper. It's cheaper today. Bram Devries traces how deferred fixes compound into emergencies, and argues that naming the trade-off out loud is the only way to break the cycle.
Half of today's AI best practices are coping mechanisms for temporary scarcity, not timeless engineering insights. Geoffrey Dhuyvetters traces the arc from SMS bundles to token limits, and argues the price curve only goes one direction.
