Customer support in the AI era
Most AI-powered customer support is optimised for deflection, not resolution. The problem isn’t bad agents, it’s architecture: no shared context, no real permissions, no escalation path that works.
Enhancing software, elevating teams.
Search posts, tags and authors
What’s new?
Featured posts
Mental capacity is a bottleneck
AI removes bottlenecks until it reaches the one that doesn’t move: human cognition. The faster AI makes your system, the more your team’s mental capacity becomes the constraint. You can’t add more of it.
Parallelise yourself with Git worktrees
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.
Editor’s Choice
Previous posts
Get started with our best stories
Taste is the moat
When AI closes the execution gap, taste becomes the differentiator. Curation, judgement, and the willingness to say “not this” compound over time in ways that models can’t replicate.
Is the AI agent frenzy similar to the mobile app hype of the early 2010s?
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 authenticity tax
AI-generated content has made polished writing look suspicious. The deeper cost is the thinking you skip when you outsource the words that define your position.
The cost of the quick fix
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.
Your limit will reset at 12pm
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.
The SaaS audit bingo card: insights after auditing 180+ SaaS companies
After auditing 180+ SaaS companies, the same patterns keep showing up: a CTO who does everything, documentation nobody updates, a backlog from 2019. Here's what the bingo card looks like, and what AI is changing about it.