Blindfolded AI: Why AI Fails Without Enterprise Context, and How StackRails Solves It
DUBLIN, Nov. 3, 2026 /PRNewswire/ -- "Our engineers push AI coding to its limits every day, on large and complex codebases. We adopted AI earlier than most, and soon found that in large multi-repo codebases, AI agents kept making breaking changes. So we built StackRails," says Alexander Wheeler, founder of StackRails.
StackRails maps how code and systems depend on each other across a business, using its own graph technology. It gives AI agents that architectural context and the company's policies before they write, then checks the result against the same policies, so an AI change fits the architecture and doesn't break anything downstream.
The product is available now. StackRails will share more at Gartner IT Symposium/Xpo, November 9 to 12, 2026, at the Barcelona International Convention Center.
The new reality of coding
"Enterprises already pay for AI coding tools. StackRails doesn't replace them; it makes them effective," says Magnus Backström, StackRails co-founder. "It works with agents like Copilot, Claude Code and Codex, giving them knowledge of your own systems before they write. Over time, that means fewer engineering hours and tokens spent rediscovering the codebase or fixing changes that broke something downstream."
What is StackRails?
StackRails connects code, infrastructure, APIs, data flows, documentation and engineering policies into one architecture model that shows how systems work and what a change will affect. Through the StackRails plugin, coding agents get the context they need, so new code fits the existing codebase instead of adding poor design choices or shadow code. StackRails then checks each pull request against your policies and reports what breaks one; your repository settings decide whether a failed check stops the merge. It also runs AI architecture reviews that find technical risks and policy breaches and suggest fixes. The result is code that needs fewer rewrites before it reaches production.
Mapping everything has a useful side effect. "Once your whole system is mapped, you get a complete picture of it, with documentation that stays up to date," says Alexander Wheeler. "Anyone on the team can ask their coding agent how part of the system works, so knowledge no longer sits with the one or two people who built it."
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