Normalized claim
Engineering productivity gain: 2-3 x
Our engineering team experience 2-3X productivity gains by using Amazon Q Developer.
Inside Mondelēz's Cloud and AI Transformation using Amazon Q Developer
Use case typeCode assistantUpdated Jun 13, 2026
Mondelēz International is modernizing its cloud engineering environment and using Amazon Q Developer to help scale developer onboarding and productivity. The company expanded the tool from a small pilot to its full engineering organization so teams could use it in daily workflows. The AWS implementation is governed by an internal AI review board, encryption keys for sensitive data, centralized configuration that disables training for outside use cases, and monitoring by engineering leaders. The article also describes Mondelēz building an internal MCP for interacting with Amazon Q Developer and internal systems, including infrastructure-as-code repositories and observability platforms.
- Organization
- Mondelēz International
- Industry
- Consumer & Food
- Location
- United States
- Published
- May 2026
Reported outcomes
Engineering productivity gain: 2–3×
Productivity & throughput
Server provisioning time: Approximately 20 minutesServer provisioning time before: 7 days
Catalog median for productivity & throughput deployments: +40% across 100 reported metrics. Compare benchmarks →
Planned next steps
- The source says the pilot could deliver: Integrated AI into daily developer workflows.
Why do we believe this?Outcome claims, sources, and evidence checks
Normalized claim
Server provisioning time: 20 minutes
Fully compliant servers are now ready in about 20 minutes.
Normalized claim
Server provisioning time before: 7 days
server provisioning, which used to take seven to ten days.
Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks
- Customer
- Mondelēz International
- Provider
- AWS
- Maturity
- Pilot
- Linked source
- AWS Case Study
The company expanded the tool from a small pilot to its full engineering organization so teams could use it in daily workflows
Customer identity supportedSource describes one deploymentMaturity supported
Primary read
Use case focus
Showing 3 of 4
- 1Developer productivity
- 2Code generation
- 3Cloud engineering
- Mondelēz integrated Amazon Q Developer into daily developer workflows, starting with a pilot and expanding it across the engineering organization.
- The company used an internal AI review board to approve usage, applied encryption controls for sensitive data, centrally disabled training for outside use cases, and set leader oversight and monitoring.
- Engineering teams also built an internal MCP to connect Amazon Q Developer with internal repositories and observability systems for IaC template retrieval, code generation, and infrastructure questions.
- The company reported 2-3X engineering productivity gains.
- Engineers were described as becoming productive in days rather than months.
- Secure server provisioning dropped from 7-10 days to about 20 minutes.
- The tool helped improve security practices by writing and refining IAM policies and by finding insecure IaC configurations.
Architecture
Amazon Q Developer was embedded into developer workflows and extended with an internal MCP that connected to internal IaC and observability systems. Governance included an internal AI review board, encryption key controls, centralized disablement of outside training, and engineering-leader monitoring.
Sources & evidence1
Evidence: Medium65/100Evidence strength
- Customer explicitly identified
- Deployment status explicitly supported
- Primary source available
- Quantified outcome available
- Technical implementation details available
Type: Customer StoryPublished: May 27, 2026Publisher: AWSEvidence: VendorConfidence: Medium
AI-generated summary. Verify important details with the linked sources before relying on this case.
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