Discovery
AuraScore 79/100

Technical Sales Engineer Discovery Dialogue for Distributed Tracing

Run an exploratory discovery interview focused on debugging workflows, observability gaps, and MTTR.

Deploy this template when speaking with Site Reliability Engineering (SRE) managers and DevOps leads who struggle with distributed troubleshooting. It builds a technical discovery script to uncover observability blind spots and incident triage costs.

Template

Role: Principal Technical Sales Engineer specialising in cloud observability, telemetry data, and production debugging.

Context

  • Target engineering team: {{engineering_org_name}}
  • Current monitoring vendor: {{current_monitoring_tool}}
  • Target resolution metric: {{mean_time_to_resolution}}
  • Service landscape scale: {{microservices_scale}}
  • Dominant failure mode: {{major_outage_pattern}}
  • Primary developer complaint: {{on_call_frustrations}}

Task

Generate an interactive technical discovery interview script to evaluate {{engineering_org_name}}'s telemetry stack, identify root-cause isolation bottlenecks, and uncover the operational cost of production debugging.

Method

  1. Establish conversational rapport by referencing the scale of {{microservices_scale}} and common telemetry blind spots.
  2. Craft an exploratory diagnostic sequence contrasting metric alerting with actual root-cause identification.
  3. Script focused interview probes targeting limitations in {{current_monitoring_tool}} during {{major_outage_pattern}}.
  4. Formulate discovery prompts analyzing the engineering time spent triage debugging to unpack {{mean_time_to_resolution}}.
  5. Develop developer-experience discovery questions investigating on-call fatigue driven by {{on_call_frustrations}}.
  6. Script active-listening talk tracks that probe distributed context propagation across asynchronous service boundaries.
  7. Build a technical qualification wrap-up that secures commitment for an architectural log and trace data evaluation.

Constraints

  • Dialogue MUST focus on debugging workflows, context propagation, and developer cognitive load.
  • MUST NOT use generic IT service management phrasing; use precise software engineering and SRE terminology.
  • Include explicit probe-and-pause cues to let the engineering lead elaborate on architecture flaws.
  • Total script length must remain concise and tailored for a 30-minute discovery session.

Output format

  • Section 1: Technical Rapport & Context Baseline (100 words)
  • Section 2: Telemetry & Instrumentation Diagnostic (4 multi-part questions with 'Listen For' notes)
  • Section 3: Incident Debugging Walkthrough Script (Step-by-step incident dissection dialogue, 200 words)
  • Section 4: On-Call & Developer Toll Validation (3 targeted questions)
  • Section 5: Technical Proof-of-Concept Closing Script (75 words)

Self-review

  • Does the script dissect the debugging path rather than surface-level dashboard metrics?
  • Are questions tailored to uncover shortcomings in {{current_monitoring_tool}} without sounding dismissive?
  • Does the incident walkthrough section accurately address {{major_outage_pattern}}?
AuraScore breakdown
79/100Provisional
Instruction clarity15/15 · Strong

Explicit role, a named task, and discrete steps the model can follow.

Context architecture12/12 · Strong

Background, inputs and variables the model needs before it starts.

Constraint engineering10/12 · Adequate

Hard boundaries — what the model must and must not do.

Output specification6/14 · Thin

A named, field-level shape for the response.

Reasoning structure10/10 · Strong

Ordered work items that force analysis before an answer.

Model compatibility10/10 · Strong

Length and structure that travel across frontier models.

Token efficiency5/10 · Thin

Signal density — instruction weight without padding.

Reusability7/7 · Strong

Documented variables so the scaffold adapts to new inputs.

Robustness3/5 · Adequate

Quality bar, assumptions and behaviour when inputs are thin.

Observed performance1/5 · Thin

How much real usage the template has behind it.

sales
sales-discovery
software-engineering-debugging
observability
debugging
sre