Chris Ross Harris

Ventures / In progress

Job Ops

A decision-grade operating system for modern job search execution: pipeline visibility, resume version governance, and follow-up intelligence that improves speed and hit rate.

Job Ops

Problem / Audience / Approach / System / What I’m proving

Problem

Most job searches fail operationally before they fail competitively. Strong candidates still lose momentum because execution lives across scattered tools, inconsistent tracking, and low-signal follow-up habits.

Audience

Primary users are high-agency professionals managing multiple role tracks at once, plus operators supporting career pivots where consistency and speed both matter.

Leadership Objective

Design a repeatable search system that removes cognitive drag, creates alignment between strategy and execution, and gives users a clear weekly view of what is working.

Approach

I structured Job Ops as an operating model, not a checklist app. The product is built around decision points: where to focus, what to improve, and when to re-sequence effort.

The product strategy pairs behavioral design with operational clarity:

  • Standardize role intake so opportunities are scored before effort is spent.
  • Tie resume and cover letter versions to role archetypes and outcomes.
  • Turn follow-up into a timed cadence instead of ad hoc reminders.
  • Surface weekly signal loops so users improve pitch quality and targeting.

System Architecture

1) Pipeline Command Layer

A stage-based board and timeline view track each opportunity from sourcing to offer. Every record includes owner, urgency, status confidence, and the next required action.

2) Application Quality Layer

Each submission is paired with the exact resume and cover-letter variant used, enabling performance analysis by narrative, role family, and positioning strategy.

3) Communication Cadence Layer

Follow-ups, thank-you notes, and recruiter touchpoints are managed through structured intervals with escalation prompts when response windows pass.

4) Decision Intelligence Layer

Weekly dashboards summarize conversion rates, stale opportunities, response patterns, and high-performing story angles so users can refine strategy quickly.

What I’m Proving

  • Operational rigor can materially improve interview conversion without increasing total application volume.
  • Version-controlled messaging creates measurable feedback loops for personal positioning.
  • A single execution system reduces stress while increasing decision quality and speed.

Current Status

In progress. Core workflow architecture and interface patterns are established; next milestone is a private pilot focused on conversion uplift and cycle-time reduction.

Expected Outcomes

  • Faster application-to-interview cycle times through cleaner follow-up discipline.
  • Higher quality submissions through reusable narrative blocks and version governance.
  • Better strategic focus through weekly performance readouts instead of reactive activity.

Prototype Frames