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# Uber’s Zero Growth Stack: Scaling Services, While Optimising Infrastructure and AI Cost

**[InfoQ](https://daily.dev/sources/infoq)** · 3 min read · 1 upvotes · 0 comments

## Summary

Uber's 'Zero Growth Stack' initiative decouples infrastructure capacity growth from business demand, reducing physical hardware while maintaining service scaling. A key component is GOGCTunner, a dynamic Go garbage collection tuning library that adjusts GOGC values based on cgroup memory limits and live object utilisation, reclaiming 70,000 CPU cores across 30 services. On the AI side, Uber integrated generative AI into its development lifecycle through a layered architecture (Michelangelo, MCP Gateway, background agents like Minion and Shepherd, and review tools), achieving 31% AI-authored new code and 5,000+ monthly AI-generated unit tests. However, AI costs grew sixfold since 2024, with individual developer costs reaching $2,000/month, prompting Uber to impose $1,500 usage caps and shift to granular metrics like 'net code quality ratio' and 'compute efficiency per feature' to govern AI spend sustainably.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://www.infoq.com/news/2026/07/efficient-ai-infrastructure>

## Questions this post answers

### What is GOGCTunner and how does it optimize Go garbage collection at scale?

GOGCTunner is an open-source library built by Uber that dynamically adjusts the GOGC value based on live cgroup memory limits and object utilization, replacing static GC tuning. It maintains heap size at roughly 1.25x live objects while enforcing a 70% memory utilization threshold to avoid out-of-memory events, and it reclaimed 70,000 CPU cores across 30 mission-critical services.

_Engineers tuning Go memory and GC behavior at scale can find related infrastructure deep dives on daily.dev._

### How much are AI coding assistant costs increasing for engineering teams and how are companies controlling them?

AI-related development costs rose sixfold since 2024, with some individual developer costs reaching $2,000 monthly due to token-based billing. To control this, spend was capped at $1,500 per developer, alongside new metrics like a "net code quality ratio" (comparing hotfix rates between AI-authored and human-authored code) and "compute efficiency per feature" to weigh AI overhead against real value delivered.

_Teams weighing AI coding tool spend against real productivity gains can track this debate on daily.dev._

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---

Tags: [#golang](https://daily.dev/tags/golang), [#uber](https://daily.dev/tags/uber)

[View this post on daily.dev](https://daily.dev/posts/uber-s-zero-growth-stack-scaling-services-while-optimising-infrastructure-and-ai-cost-vsvgejjg1)

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