What does it actually take to double an engineering team’s output in just nine months?In this episode of techdaily.ai, David and Sophia break down how Intercom reportedly doubled merged pull requests per employee by combining AI coding agents with the right engineering foundation, cultural permission, and strict guardrails.This is not a story about simply buying a shiny AI tool and hoping developers move faster. It is a practical look at why AI only works at scale when the company already has the systems, visibility, and leadership mindset to support it.You’ll hear how Intercom approached AI-driven engineering by focusing on: Mature CI/CD pipelines that could handle faster code delivery Automated testing that prevented AI-generated chaos from overwhelming reviewers Developer telemetry that revealed which AI workflows were actually working Custom guardrails that forced AI agents into high-quality pull request processes Technical debt reduction through automated maintenance and cleanup tasks A culture where leadership absorbs risk so engineers can experiment freely The growing need to build software that is friendly to AI agents, not just human users David and Sophia also explore a bigger shift already reshaping digital products: what happens when your customers’ AI agents interact with your software before humans ever do?From invisible sales funnels to machine-readable interfaces, this episode looks at why the future of software may depend less on button colors and more on whether bots can understand, navigate, and complete tasks without friction.Tune in for a sharp, conversational breakdown of AI productivity, engineering culture, software velocity, and what agent-first design could mean for the internet ahead.Subscribe to techdaily.ai for more conversations on AI, software development, enterprise technology, and the systems changing how modern teams build.

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