Head of Delivery

The Head of Delivery is the architect and steward of Capptus’ delivery operating system.

Their mission is to design a delivery environment where

• AI removes execution friction
• Human judgment, taste, and systems thinking drive decisions
• Small, high-leverage teams consistently outperform larger, siloed ones
• Knowledge compounds across projects instead of resetting each time

Core Responsibilities (AI-First & System-Led)

• Design the AI-First Delivery System (Primary Responsibility)

• Define how work flows from idea → delivery → learning:
• Where AI assists exploration, design, testing, and documentation
• Where human review and judgment are mandatory
• Where decisions must be explicit, documented, and reversible

Ensure all delivery roles operate in shared mediums

• Same artifacts
• Same tooling
• Same understanding of context
• Minimal handoffs

• Elevate Judgment as the Core Delivery Skill

Redesign delivery expectations so senior roles are evaluated on

• Quality of architectural decisions
• Tradeoff clarity
• Ability to frame problems, not just solve tasks

Institutionalize judgment rituals

• Lightweight decision reviews
• Explicit assumptions and risk articulation
• “What would make this decision wrong?” discussions

Protect time for thinking

• Architects and leads are not fully utilized
• Slack is intentional, not waste
• Judgment degrades under constant execution pressure

• Operate Delivery as a Living System

Treat delivery as

• Inputs (scope, constraints, talent, customer context)
• Flow (work in progress, dependencies, decisions)
• Outputs (value, quality, margin)
• Feedback (learning, reuse, improvement)

Identify and act on

Bottlenecks

• Feedback delays
• Misaligned incentives
• Over-optimization of local metrics
• Use data (including Certinia) as signals, not commands.

• Certinia as Observability, Not Control

• Surface patterns and constraints
• Track financial and delivery reality
• Enable fast, informed decisions

• Knowledge as a System Output

Every project must produce

Reusable patterns

Decision rationales

What-worked / what-didn’t insights

AI is used to

• Extract learning from delivery artifacts
• Summarize complex projects
• Connect current teams with prior context

Knowledge ownership is explicit

Assets are curated, pruned, and reused

Learning feeds back into future delivery design

• Talent Development for Systems Thinkers

What the HoD Builds

Consultants and developers who

• Understand the full delivery system
• Can reason across data, platform, business, and customer context
• Specialize deeply in judgment-heavy domains

Clear progression

From task execution → problem framing → system ownership → mentorship

Juniors are onboarded into thinking, not just doing

• Early exposure to decisions
• Explicit explanation of tradeoffs
• AI used as a learning accelerator

• Customer as Part of the System

Customers are treated as

• Active participants in delivery
• Decision-makers with constraints
• Sources of feedback, not interruptions

SteerCos are

• Alignment forums
• Constraint-renegotiation spaces
• Shared judgment environments

Leadership Expectations

• Optimize for long-term leverage, not short-term output
• Make invisible work visible (decisions, tradeoffs, learning)
• Use AI comfortably without surrendering responsibility
• Protect buena onda while holding high standards
• Think like a system architect, not a project manager.