Personas

Specific people at Canary Co. Grounded in O*NET/ESCO roles. Instantiate archetypes — each one shows a pattern through a real-work lens.

2 built · gaps in 7 divisions
Task key: Employee Only Employee + AI AI Only

Persona 01

Asha Mehta

Tier-1 Support Adviser · Operations · Customer Operations

O*NET 43-4051.00 Customer Service Representatives Calderbridge contact centre 6 years at Canary Co Age 34

Who they are

Asha handles product complaints and D2C order problems. She is good at the hard calls — the upset customer, the genuine fault — and quietly proud of it.

What they do

  • Employee + AITake inbound calls and messages about faulty products and orders.
  • AI OnlyLook up order and account details across systems.
  • Employee OnlyResolve complaints within policy; decide goodwill gestures.
  • Employee + AIDraft written replies to complaints.
  • AI OnlyLog call outcomes and reasons.
  • Employee OnlyDe-escalate angry or distressed callers.
  • Employee + AIRoute complex cases to specialists.

Skills that matter

  • Active Listening The part of the job she rates as the actual job.
  • Social Perceptiveness Reading whether a caller is angry or frightened.
  • Service Orientation Knowing when policy isn't the answer.
  • Reading Comprehension Parsing messy customer messages.

Relationship with AI

A new tool suggests draft replies and "next best actions". Asha doesn't trust it. Twice it suggested a chirpy reply to someone clearly distressed. She uses it for routine order queries and ignores it on anything emotional — and resents being measured on whether she "adopts" it.

The friction point

The suggested-reply tool is fine for "where's my order" and wrong for "your product gave my child a rash". Asha's worth is in telling the difference. The rollout metric can't see that.

Persona 02

Tom Reilly

Logistics Planning Analyst · Operations · Supply Chain & Logistics

O*NET 13-1081.00 Logisticians Rotterdam Ex-warehouse, worked up to planning Age 41

Who they are

Tom knows the network better than the planning system does. Impatient with meetings, happiest when something he built saves an afternoon.

What they do

  • Employee + AIPlan inbound/outbound flows across sites.
  • AI OnlyPull and reconcile data from the planning and ERP systems.
  • Employee + AIBuild forecasts and reorder schedules.
  • Employee + AIInvestigate why a route or stock level went wrong.
  • Employee OnlyBrief the transport teams.
  • AI OnlyProduce the weekly planning report.

Skills that matter

  • Systems Analysis Sees the network as a whole.
  • Complex Problem Solving The "why did this break" work.
  • Critical Thinking Knowing when the model is wrong.
  • Active Learning Teaches himself the tools nobody bought him.

Relationship with AI

Tom already automated half his own job. He wrote scripts and a spreadsheet model that does the weekly report in minutes, plus an LLM prompt chain that drafts the route exceptions. IT doesn't know. It works, until the day it doesn't and only Tom can fix it. He's ahead of the official programme and slightly off the books.

The friction point

Shadow automation: Tom's tools are better than the sanctioned ones, undocumented, and a single point of failure. The org benefits and is exposed at the same time.
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