TALENT on demand TALENT on demand
Source · Moonshots with Peter Diamandis and Moonshot Mates
1 / 8
· The Agent Playbook
Build. Buy. Borrow. Bot.
A four mode decision framework for every role.
BUILDstrategic, weird, ambiguous
BUYscarce, repeatable
BORROWfractional specialist
BOTpredictable, definable
Chapter one · The matrix

The matrix replacing hire or contract.

Plot every role on two axes. Strategic value vertical, predictability horizontal. The cell tells you the mode.

Strategic value →
Build
Full time talent for ambiguous, high stakes work the model cannot define.
≈ 12 to 18% of headcount
Buy
Acquire scarce, repeatable expertise via vendors, M&A, or licensed platforms.
≈ 18 to 24%
Borrow
Fractional on demand specialists. Strategic work without permanent overhead.
≈ 22 to 28%
Bot
Agents and automation for predictable, well bounded operational tasks.
≈ 32 to 42% by 2027
Predictability of work →
01

Default is bot.

If a task is definable in a prompt, it belongs in the bottom right unless evidence says otherwise.

02

Build only what is strategic and weird.

Top left should never exceed 18% of spend, or you are subsidising commodity work.

03

Borrow before you buy.

Fractional access reveals true scope. Conversion to acquisition is cheaper after six months of need.

04

Replot every quarter.

Capability moves diagonally as model costs fall. Today's Build role is next year's Bot.

Chapter two · The four layer stack

What an agent workforce actually is.

The dialogue collapsed agents into a single category. They are not. The deployable architecture has four layers with separate ownership, governance, and economics.

04
OrchestrationRouting, escalation, audit. Owned by the Chief Digital Orchestrator (CDO), the C suite role that owns AI agent fleet operations.
human led
03
Reasoning agentsMulti step planning, tool use, judgement under uncertainty.
model led
02
Specialist agentsNarrow tasks. Coding, drafting, retrieval, classification.
task led
01
FoundationModel, memory, identity, permission scope. Pay per token.
infra led
90 percent of failed deployments are layer three problems.

Reasoning agents released without orchestration above them produce unsupervised judgement at scale. The most expensive failure mode in the matrix.

The CDO owns layer four.

Not the CIO. Not the CHRO. The role deciding which decisions humans keep, which they delegate, and which they audit is a new C suite function. Without it, layers one through three drift.

Chapter three · The economics

Cost per task, human versus agent.

A representative sample across knowledge work. Costs include model spend, oversight load, and revision cycles. The rightmost column is what most finance teams miss.

TaskHuman costAgent costPer task cutVolume ×Net impact
Sales call summary$8.40$0.12
−98%
14×−71%
First draft contract$42.00$1.80
−96%
−74%
Tier 1 support ticket$5.20$0.08
−98%
22×−66%
Software unit test$22.00$0.30
−99%
11×−85%
Compliance review$120$18.00
−85%
−70%
Strategic plan section$580$220
−62%
1.4×−47%
Board narrative$1,400$1,150
−18%
1.0×−18%
Chapter four · The decision flow

How to choose, in four questions.

A single decision tree your Chief Digital Orchestrator should run before approving any net new headcount. Stop at the first yes. The exit determines the sourcing mode.

Run this tree before authorizing any net new role Four binary questions. Four sourcing outcomes. The dashed line is the scale up path from validated bot pilots to licensed buy. Open requisition START Definable in a prompt? Tasks, inputs, outputs all specified upfront Yes Volume > 50 / week? Industrial throughput justifies the orchestrator Yes BOT Agent + orchestration Cost: ≈$0.10 / task No No scale up BUILD Full time hire Yes Strategic + recurring? Owns a differentiating capability long term No BORROW Fractional specialist BUY Licence or acquire
BUILD · own it
BUY · license or acquire
BORROW · fractional
BOT · agent + orchestration
Chapter five · The operating rhythm

How a CDO spends a quarter.

Four cadences. Each with a single owner, a single deliverable, a single exit. This is the operating model the evidence associates with an orchestration owner.

Weekly · Signal

Read the agent telemetry.

  • Task volume by agent vs human
  • Escalation rate per workflow
  • Cost per task drift
  • Identify next migration candidate
Output Monday signal page.
Monthly · Migrate

Move one role across the matrix.

  • Pick one Build candidate
  • Pilot in Borrow or Bot
  • Validate quality at 95%
  • Recast headcount plan
Output Role transition memo.
Quarterly · Map

Redraw the capability heat map.

  • Replot all roles on matrix
  • Update model cost assumptions
  • Review failed pilots
  • Brief the board
Output Refreshed sourcing matrix.
Annual · Architect

Redesign the org for next year.

  • Set Bot ratio target
  • Reset hiring caps by quadrant
  • Approve infrastructure spend
  • Lock the comp framework
Output Workforce blueprint.
Chapter six · Synthesis

What the evidence points to.

Across 250+ episodes of Moonshots, the recurring pattern is that work is being re-sourced, not simply automated. Three takeaways follow from that.

Reading the pattern

Three observations the evidence supports.

Four sourcing modes, not two

The hire or outsource binary is widening. The recurring framing in the source treats Build, Buy, Borrow and Bot as parallel options for the same task. Each role becomes a sourcing decision rather than a fixed headcount line.

Agent economics vary by task

Cost per task is the discriminating variable. The evidence suggests agents are favourable for high volume, well bounded work and weaker on judgement heavy or sparse tasks. The unit of analysis is the task, not the job title.

Orchestration needs an owner

A mixed human and agent workforce does not coordinate itself. A commonly cited gap is the absence of a single accountable owner for agent operations. One coined label for this role is the Chief Digital Orchestrator: the person who owns the operating rhythm across modes.

Every role is a
sourcing decision.
Three observations that recur across the source material, restated plainly.
Observation 01

The matrix is a lens.

Plotting roles across Build, Buy, Borrow and Bot surfaces where the same task could be sourced more than one way. It is a way of reading an org, not a prescription.

Observation 02

Pilots precede claims.

The evidence favours measuring cost per task on a small number of high volume workflows before drawing conclusions. Forecasts of wholesale displacement remain forecasts.

Observation 03

Rhythm beats one off moves.

Where the pattern holds, a recurring operating cadence with a clear owner does more than any single migration. Coordination is the constraint.

About this briefing.

One of five briefings distilled from 250+ episodes of "Moonshots with Peter Diamandis and the Moonshot Mates". Claims are attributed to that source; forecasts are marked as forecasts.

www.talentod.com