Xodiac

An agent built broken code from a spec that no one had deleted. The spec existed. The new one existed too. No one told the agent which was current.

That's context rot. And unlike stale docs, it doesn't slow you down. It produces bad output at full speed, consistently, before anyone realizes what's happening.

Context isn't documentation anymore. It's infrastructure. It has to be maintained like one.

https://xodiac.ca/articles/context-is-the-new-documentation/

Context Is the New Documentation AI agents don't browse wikis or ask colleagues; they use the context you give them. Here's why context management is now a core delivery discipline.

Teams with high AI adoption merge 98% more pull requests. Sounds like winning, right?

Look closer: those PRs are 154% larger and take 91% longer to review. More code, bigger batches, slower understanding. That’s not speed. That’s debt accumulating quietly.

Your SDLC was designed for humans writing code at human speed. AI broke that assumption, and patching won’t fix it.

There are 4 structural shifts that separate teams shipping sustainably from teams quietly drowning. Two you’ve probably started. Two you probably haven’t.

Swipe for all four. Full breakdown on the Xodiac blog, link in bio.

You bought the AI tool. Your developers use it daily. Velocity is up.

So why does delivery feel harder than a year ago?

McKinsey has a number for this: 79% of organizations using AI haven’t redesigned how work actually flows. They added AI on top of a process built for humans. The result is faster code generation feeding the same old bottlenecks.

The 21% that get real returns did something different, and it wasn’t buying a better tool.

Swipe to see why adding feels safer than redesigning, and the question that changes everything.

Full article on the Xodiac blog: https://xodiac.ca/articles/why-isnt-ai-improving-software-delivery

48% of enterprise leaders now call AI adoption a massive disappointment.

That number was 34% just one year ago. Investment is at an all-time high. The technology keeps improving. And yet results are getting further from expectations, not closer.

This isn't a technology problem. It's a systems problem.

Swipe through to see what the data says is actually going wrong, and what separates the 29% of organizations seeing real ROI from everyone else.

Full breakdown in the blog: https://xodiac.ca/blog/articles/why-ai-adoption-is-disappointing