Support Engineering
How Guide automated engineering support using Decimal
Transformed engineering support from constant interruption into automated investigation workflow
SANJEET HAJARNIS
Guide is building the AI agent for recruiting coordination. Their platform automates complex interview scheduling workflows coordinating candidates, interviewers, and hiring teams across complex ATS systems to help recruiting teams move up to 7x faster.
But running those workflows at scale introduces a different challenge. When customers have questions about scheduling behavior, candidate portals, or ATS integrations, answering them often requires digging through production logs, code, and customer-specific configuration.
The challenge
Guide works closely with their enterprise customers through shared Slack channels where hiring teams can ask questions, report issues, or request help with scheduling workflows.
For Guide’s customers, fast responses are part of the product experience. But for the engineering team, maintaining that responsiveness meant constantly jumping into production investigations.
Customer questions frequently require real debugging work.
A typical issue might involve:
tracing interview scheduling logic across multiple interview stages
checking candidate portal configuration for a specific role
inspecting Datadog logs tied to a specific integration
With no dedicated support team, these investigations fell directly to the founding engineers.
Customer support was becoming our biggest operational bottleneck. We're constantly getting pinged across dozens of customer channels, and while fast responses are part of our value proposition, it's extremely time consuming.
Troy Sultan, Co-Founder & CEO
The team was looking to automate the entire flow instead of building a traditional support team.
Automating engineering investigations
Guide integrated Decimal directly into their existing Linear workflow.
When customers post questions in Slack, Linear automatically creates tickets. Decimal immediately performs the same investigation an engineer would run: scanning Guide's codebase, querying Datadog for relevant production logs, understanding customer configuration, and cross-referencing log events with code behavior.
The system handles the most complex aspects of support investigation:
Code analysis: Tracing through Guide's interview scheduling engine, candidate portal logic, and ATS integration implementations to understand intended behavior
Production troubleshooting: Filtering Datadog logs by specific organizations and time ranges to reconstruct what actually happened
System state analysis: Querying Guide's custom tools to fetch current customer configuration, interview status, and integration health
Root cause identification: Connecting disparate signals from logs, code, and configuration to identify the actual source of issues
By the time an engineer opens the Linear ticket, the investigation is complete.
The breakthrough was when Decimal started leveraging our production systems directly. It correctly analyzes our codebase, Datadog logs, and traces through complex scheduling logic. For technical issues, it's identifying the right failure points and providing implementation-level context.
Austin Cooley, Co-Founder & CTO
Example: diagnosing candidate portal behavior
A customer noticed that prep materials they had recently updated for a role were not appearing correctly in the candidate portal, sharing links to both the job configuration page and the candidate portal showing outdated content.
Decimal pinpointed the issue by tracing through Guide's code and identified the underlying behavior: prep material updates only apply to candidates scheduled after the change. Existing candidates retain the original prep material for consistency.
Decimal provided the technical explanation and solution directly to the customer in the Linear ticket. The customer confirmed the solution immediately.
The outcome
Guide transformed engineering support from constant interruption into automated investigation workflow that maintains high-touch customer experience without sacrificing engineering velocity.
The impact extends beyond handling more tickets:
Engineering focus restored: Issues get analyzed before any engineer involvement
Response quality improved: Engineers review completed investigations with full technical context
Scalability without headcount: Support capability scales with product complexity
Guide achieved their ultimate vision: fully automated first responses that customers trust and accept.
Seeing Decimal responses autonomously getting routed directly to customers at 2:32am was the culmination of all our technical work - automated engineering support that actually works.
Austin Cooley, Co-Founder & CTO
Guide proved the future of engineering support: intelligent workflows that handle complex investigations automatically while maintaining high-touch customer experience, eliminating the traditional choice between engineering velocity and customer responsiveness.
