The challenge
As Director of IT Operations, Howard Zeemer describes his role as “making sure everyone else moves faster.” His teams manage all infrastructure and DevOps culture at LendingTree, supporting the systems that power every product and internal service.
With over 1,200 microservices and multiple clouds in play, the team faced challenges in:
- Sprint planning and story generation: Manually translating Confluence briefs into Jira stories, estimating story points, and creating subtasks.
- Cloud spend reporting: Reconciling billing data, often requires manual exports and spreadsheet pivots.
- Debugging and context switching: Understanding distributed service interactions across dozens of repositories.
- Unit test coverage: Writing and maintaining test cases consuming up to 30% of developer time.
- Documentation and reporting: Generating consistent, up-to-date documentation across tickets and pipelines.
Earlier AI tools promised automation but required too much setup and context feeding.
“A lot of tools gave you results only after a ton of effort. You got out of them what you put in.” — Howard Zeemer, Director of IT Operations, LendingTree
Why Augment Code?
LendingTree adopted Augment Code to bring context-aware intelligence into daily workflows. Zeemer’s teams needed AI that could operate across multiple tools, understand their existing automation pipelines, and adapt to their DevOps environment.
“Out of all the tools I’ve used, Augment came the closest—and found things I hadn’t thought of.”
Deep multi-repo context
Augment seamlessly ingested context from multiple repositories and CI/CD pipelines.
“I told Augment, ‘Build the pipeline using our rules.’ It picked it up and ran with it—didn’t even look twice.”
Integrated planning automation
By connecting Augment to Jira and Confluence, Zeemer’s team used it to:
- Parse planning briefs
- Generate and estimate user stories
- Create subtasks and rubrics for sprint execution
“My PMs were ridiculously excited. What used to take a day now takes minutes.”
Smart cloud spend analysis
Augment automates spend comparisons between AWS and Azure, surfacing percentage and dollar changes by service.
“It tells me which orgs have the biggest spend changes and what they’re related to. I even used Augment to write an Azure MCP for spend management.”
Automated debugging and unit testing
When one team spent hours chasing a WebSocket permissions bug, Augment identified and fixed it in minutes.
“One of my engineers pointed Augment at the code—it solved the problem in 15 minutes.”
Augment also generated comprehensive unit tests, covering the tool’s annual cost within a single month of use.
Results and benefits
| Impact Area | Before Augment | After Augment |
|---|---|---|
| Unit test coverage | 30% developer time | Automated, tool spend ROI achieved in just 1 month for the entire year |
| Sprint planning | 1-2 days per sprint | Minutes via Jira + Confluence integration |
| Cloud spend reporting | Manual excel reconciliation | Automated summaries and graphs |
| Debugging | 2+ hours on critical bugs | 15 minutes with Augment |
| Documentation | Time-consuming and manual | Generated inline with tasks |
Augment now supports engineers, PMs, and operational staff alike—freeing time for higher-value work.
“The goal is simple: make AI do the toil so we can do the fun stuff.”
About LendingTree
LendingTree operates one of the largest online lending marketplaces in the U.S., connecting consumers to financial products across mortgages, credit cards, and personal loans. Its engineering teams manage over a thousand microservices spanning AWS and Azure, maintaining the reliability and scalability that underpin the platform’s financial infrastructure.
By embedding Augment Code across development, planning, and operations, LendingTree’s teams now spend less time wrangling the process with more time improving systems that matter.