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Engineered AI-DLC Across the Engineering Lifecycle for a 500M+ Media Platform
How Claude became part of software delivery - from code authoring and review to infrastructure, troubleshooting, QA, and operations.
The Opportunity
A large-scale media and entertainment platform serving 500M+ active users across India operates across cloud infrastructure, Kubernetes, CI/CD, application development, and production operations.
The opportunity was to move beyond using AI for individual tasks and bring it into the broader engineering context; where teams work with code, repositories, tickets, infrastructure, logs, pipelines, and operational systems.
The goal: make AI part of the engineering lifecycle, from understanding a request through implementation, validation, and operations.
The OpsTree Approach
AI Across the Engineering Lifecycle
OpsTree brought Claude into the engineering environment across development and operations.
Claude works alongside the engineering context teams already use; repositories, pull requests, logs, traces, infrastructure configurations, cloud tooling, CI/CD systems, and operational workflows.
This allows engineers to move from request to implementation to validation with AI participating throughout the lifecycle.
Engineering With Claude
Code authoring, refactoring, migrations, and test generation.
Diff and PR analysis, bug identification, simplification, and review assistance.
Log and trace analysis, debugging, RCA, troubleshooting, and solution validation.
Kubernetes, Terraform, Helm, CI/CD, cloud tooling, and infrastructure workflows.
Test scenarios, edge cases, QA assistance, documentation, and release readiness.
The Impact
AI Across Everyday Engineering Work
The adoption is helping engineering teams improve speed and reduce effort across the lifecycle:
- 60%
Faster code authoring & refactoring
- 80%
Faster code reviews
- 60%
Faster debugging & RCA
- 40%
Reduced infrastructure troubleshooting effort
- 50%
Faster test scenario generation
- 30%
Reduced documentation effort
- Days → Hours
Faster ticket & request understanding
- 30%
Improved CI/CD & automation workflows
Rather than measuring AI impact at a single engineering touchpoint, the opportunity is to improve productivity across the entire delivery lifecycle.
The Transformation
From AI Assistance at Individual Tasks to AI Embedded Across the Engineering Lifecycle
Claude is being used across software development and operations—from authoring and reviewing code to troubleshooting infrastructure, validating changes, generating tests, and maintaining engineering documentation.
The shift is from asking AI for help to bringing AI into the engineering context itself.