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Engineering operations

Reference build

Bug triage time cut by 70%

An agent that reads incoming bug reports, attempts reproduction from the available context, and routes what it cannot reproduce with the specific questions that would unblock it.

70%less triage time

At a glance

Duration
13 weeks
Team size
1 person
Engagement
New build
Project type
AI & automation
Industry
B2B SaaS

The situation

The challenge

Most triage effort goes into reports that cannot be reproduced as written. The information needed is usually knowable, but asking for it is manual and repetitive.

What we did

Attempt reproduction automatically, and when that fails, ask precisely for the missing piece rather than sending a generic request for more detail.

The calls that mattered

  • Reproduction attempted before routing

    The agent tries the steps against available context first, so a triaged bug arrives with evidence attached.

  • Specific questions, not 'please provide more information'

    When reproduction fails, the agent names what is missing. Generic requests are why bug reports stall.

What changed

reduction in triage time
70%reduction in triage time
of unreproducible reports return specific questions
100%of unreproducible reports return specific questions

Triage time down 70%, with unreproducible reports returned carrying the specific questions that would resolve them.

Services used

  • Automated reproduction attempts against report context
  • Structured triage output with severity and routing
  • Targeted follow-up question generation

What we would do differently

Every project has one of these. Publishing it is the point — a case study with no regrets in it is marketing, not evidence.

Knowing when to stop was the design problem. An agent that keeps trying to reproduce a bug burns more time than the triage it replaced.

Services used

More work

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