Bradley Hartwick AI Product Builder & Leader

AI Product Builder & Leader

How I Lead

Products get better when the people around them grow.

The work gets better when the people do. I create the clarity, judgment, and confidence teams need to own consequential product work.

The goal is aligned autonomy: a team that can challenge the thinking, learn in the work, and move well without me in the room.

Troop photo at dawn after a field exercise, eyes redacted. Bradley Hartwick stands at far left, circled.

The leadership system

Empowered teams, aligned autonomy

Empowerment is not distance. It starts with clear intent, honest constraints, and decision rights that grow with the person. I stay close enough to coach the judgment, then widen responsibility as the team is ready to carry more.

Aligned autonomy mission command Commander's intent make the mission and boundaries clear Psychological safety make it safe to challenge, learn, and recover First-principles framing understand the problem before the answer Coaching the individual connect growth to meaningful work Delivery excellence build a rhythm the team can trust Tactful candor be direct without losing respect Product operating model Outcome-driven roadmapssolve problems, not ship features Continuous discoveryvalidate value and feasibility early Empowered squadscross-functional autonomy over execution Build · operate · transfer Buildharden infrastructure and AI/ML data baselines Operatedeploy into live customer environments for evidence Transferstandardize pipelines for repeatable scale Seven-lever alignment Hard leversstrategy, structure, systems Soft leversshared values, style, staff, skills Diagnose frictionto the lever, not the person

Aligned autonomy Mission command

  • Commander's intentMake the mission and boundaries clear
  • Psychological safetyMake it safe to challenge, learn, and recover
  • First-principles framingUnderstand the problem before choosing the answer
  • Coaching the individualConnect growth to meaningful work
  • Delivery excellenceBuild a rhythm the team can trust
  • Tactful candorBe direct without losing respect

In the work

Product operating model
Outcome-driven roadmaps solve problems, not ship features
Continuous discovery validates value and feasibility early
Empowered squads own execution across functions
Build · operate · transfer
Build hardens infrastructure and AI/ML data baselines
Operate deploys into live customer environments for evidence
Transfer standardizes pipelines for repeatable scale
Seven-lever alignment
Hard levers are strategy, structure, and systems
Soft levers are shared values, style, staff, and skills
Diagnose friction to the lever, not the person

Across three careers, the leadership task has stayed the same: turn clear intent into everyday judgment. These six practices help people understand the mission, own decisions, and move with confidence as they take on more.

Career one · Canadian Army

Dive Officer, 1 Combat Engineer Regiment

I selected and built the regimental combat-diver team through two dive preliminaries and two Exercise Roguish Buoy deployments. In that environment, intent, constraints, trust, and technical detail were inseparable; the team had to understand the mission well enough to make safe decisions when it mattered.

Career two · KPMG

Management Consulting

Consulting taught me to make change legible: connect operating models, organization design, and disciplined delivery, then say the difficult thing clearly enough that a team can act on it.

Career three · Product

Building intelligent products & empowered product teams

In product leadership, I rebuilt an operating model, introduced discovery and problem framing where they had not existed, and helped move an executive AI mandate from alignment into shipped capability.

Developing AI-native talent

Helping people become AI-native builders

I use the AI-Native Scale as a coaching language, not a ranking. It helps a person name where they are confident, choose the next meaningful stretch, and turn real product work into stronger judgment, greater independence, and more responsibility.

01StartName the starting point together
02AimChoose the next meaningful stretch
03BuildLearn through consequential work
04CoachReflect with peers and leaders
05ShowMake growth visible in the work
06GrowTake on greater responsibility
05

The AI-Native Scale

The scale gives the team a shared language for development, not a score. The useful conversation sits underneath it: where does someone already use AI with confidence, what judgment can they explain, and which real build would help them take the next step?

  1. 0
    Starting point

    Has not yet used AI in day-to-day work. The first step is a safe, useful problem and the confidence to begin.

  2. 1
    Explorer

    Uses AI for search, questions, or early thinking and is beginning to notice where it helps and where it falls short.

  3. 2
    Practitioner

    Can reliably use prompts to draft, summarize, compare, and move a piece of work forward.

  4. 3
    Integrator

    Builds AI into a real workflow with assistants, agents, or connected tools and can explain how the pieces improve the work.

  5. 4
    Builder

    Creates AI-native products and artifacts, brings multiple tools together, and evaluates quality, risk, and usefulness.

  6. 5
    AI-native leader

    Approaches problems AI-first, attempts work that was previously out of reach, and helps others raise their own standard of practice.

Learning in the work

Stretch, support, and just-enough instruction

I use 70–20–10 as a coaching rhythm, not a formula. Most growth comes from owning consequential work. Peers and leaders make the learning visible. Focused instruction arrives when it can unlock the next move.

70%

Stretch work

Real problems worth owning

I give people meaningful product work, side projects, or ventures that ask more of them than the last build did. They ship, show what changed, and explain what they learned.
20%

Coaching and community

Growth with and through others

I connect people with peers, mentors, experts, and leaders who can challenge the work, share their craft, and help turn experience into judgment.
10%

Focused learning

Instruction when it unlocks the next move

I bring in curated resources, worked examples, and focused teaching at the moment a person needs them—enough structure to move without pulling them away from the work where capability becomes real.

Framework sources. The scale and development approach draw from AI-proficiency and fluency models by Larridin, The Thinking Company, and Alex Ewerlöf, alongside the Center for Creative Leadership's 70–20–10 development framework.

Capability at community scale

A place for builders to learn by building together

Program~30 founding members · September kickoff

I founded the AI Product Community of Practice at Smith School of Business to turn individual curiosity into shared capability. Members bring consequential problems, pair across six crafts, build something real, show how they worked, and leave behind a pattern the next builder can use. It is participation over presentation: the community grows by making the work visible and reusable.

Six crafts, one shared promise: build something real and help someone else learn from it
The member result:one real build · discovery → deployment · portfolio proof Build & Ship AI-native builders Strategy choose a consequential problem Architecture make the system feasible and governable AI apply capability where it earns trust Design make the change useful and usable Change management design adoption into the work Leadership create visible practice and ownership The practice loop:bring live work → pair crafts → build & demo → reflect together → share the pattern Members show their method, never client data. Growth language:the AI-Native Scale · 0 → 5 0 · Starting pointa safe, useful first problem 1 · Explorersearch, questions, and early thinking 2 · Practitionerreliable prompts that move work forward 3 · IntegratorAI connected into a real workflow 4 · Buildercreates and evaluates AI-native products 5 · AI-native leaderraises the standard for others Growth through real work: Build · show · reflect · share then choose the next meaningful stretch Designed success conditions: stated targets — not verified outcomes 60%+of active members progress by ≥1 band 1+build shipped or demoed per active member, per term 6 of 6craft domains active with a named steward

Members leave with more than inspiration: they leave with a build, a clearer method, and proof of how they think and work.

Leadership beyond the team

From conversation to commitment—and follow-through

I designed and led the workshop to move the room from discussion to ownership. We closed with 15 commitments carried by 40 named leaders and a follow-through rhythm designed to help those ideas become action across Smith School of Business, Ivey Business School, and the McMaster Digital Transformation Research Centre.

Deliveredworkshop complete In progressfollow-through flywheel taking shape
The commitment flywheel · five turns
Commitment flywheel in flight 1 Commit named, in public 2 Follow through 3 / 6 / 9-month check-ins 3 Capture gather what changed 4 Tell the story share what others can learn 5 Draw interest invite the next cohort
What the session produced
15 commitments to responsible digital innovation
40 named leaders carrying them
How I structured the room to think

Better questions, not automated answers. Four AI thought partners—Skeptic, Systems, Futurist, and Responsible—helped participants examine the problem from different angles. People still made the decisions.

Context that carried forward. Each table's problem, statement, and notes remained visible as the conversation developed, so later questions could build on earlier thinking.

AI-native and human-led. Participants used their own devices without accounts, and commitments remained private until their champions approved them.

Explore further

See what I build, how I build it, and who I am.