Executive operator · Strategic intelligence · Applied AI

See clearly.
Decide better.
Move with precision.

I design AI-enabled intelligence and operating systems that help startups and established organizations understand their environment, make informed decisions, and execute faster.

Decision intelligenceLive synthesis
EnvironmentUnderstood
Decision pathVisible
Human judgmentRetained
The operating premise

Better intelligence
changes the decision.

The advantage is not producing more information. It is knowing what matters sooner—what is true, what is changing, what remains uncertain, and what the decision-maker should do next.

Applied well, AI compresses the distance from question to sourced insight, from insight to judgment, and from judgment to coordinated action. Time returned is measurable; a better decision is consequential.

Build from zero

Start smart before complexity hardens.

Give a startup clean information, deliberate workflows, decision visibility, and AI-enabled leverage from the beginning.

Reclaim from complexity

Recover intelligence, time, and control.

Connect fragmented information, expose hidden work, and return people to the judgments only they should make.

IntelligenceCollect and validate
DecisionFrame and resolve
ExecutionCoordinate and adapt
CapacityMeasure what returns
The experience behind the method

The environment changed.
The standard did not.

This is one continuous operating story—not a collection of unrelated careers.

Michael K. Doane
Michael K. DoaneCommercial operator and applied AI systems builder

Foundation

Standards earned under pressure.

Marine Corps reconnaissance established the foundation: selection, perseverance, relentless preparation, detailed intelligence, clear roles, and the discipline to adapt without losing the objective.

Commercial accountability

Results reset every month.

Starting as an individual contributor carrying a bag, performance was immediate and visible. That record grew into management, director, vice-president, sales and marketing, strategy, and development leadership.

Enterprise judgment

From the number to the whole business.

Consulting and private-equity environments widened the lens across people, operations, finance, growth, and execution—where a good idea only matters if the organization can carry it.

Applied AI

Learning by building.

A self-taught path through modern AI, guided by mentors and powered by a personal DGX Spark, became hands-on systems work and AI action learning at MIT Sloan. The focus remains practical: build, test, inspect, and improve.

Operating method

Prepared enough to move.
Adaptive enough to finish.

A disciplined deployment is not a string of prompts. It is an intelligence and operating system with sourced inputs, a defined decision, accountable owners, realistic rehearsal, and a safe way to adapt.

  1. 01

    Understand the environment

    Map the people, information, incentives, constraints, failure points, and what is known versus assumed.

  2. 02

    Build the operating picture

    Collect the right signals, preserve their sources, separate evidence from inference, and make the relevant context visible.

  3. 03

    Define the decision

    Clarify who decides, which options matter, what criteria apply, and what evidence will change the answer.

  4. 04

    Design and rehearse the system

    Choose the tools, data, owners, approvals, and fallbacks, then test them against representative work and edge cases.

  5. 05

    Deploy with control

    Move deliberately, preserve visibility, and maintain fallbacks, escalation paths, and accountable judgment.

  6. 06

    Measure and improve

    Track decision speed, confidence, commercial effect, time returned, errors reduced, and what the next iteration should learn.

Measure one consequence

What is faster intelligence and cleaner execution worth?

Better intelligence should improve the decision. A well-designed workflow should also return time. Model one defined role group actively using that workflow and compare it with the prior process.

Look for repeated work: manual status collection, duplicate entry, document search, handoffs, meeting reconstruction, and recurring analysis.
Capacity modelIllustrative annual estimate
Capacity reclaimed4,608hours / year
Estimated value$391,680annual capacity value
Equivalent focus2.5full-time years

Uses 48 working weeks and 1,880 productive hours per full-time year. Validate the active user count, time saved against the prior process, and the role group's hourly cost with real workflow data.

Selected work

Proof through operating systems.

Three examples of the method applied in different environments. Each begins with ambiguity and ends with something people can inspect, operate, and improve.

The situation

Leadership needed clearer visibility across projects while building controlled documentation supporting AS9115A software-quality readiness.

The work

Source-linked dashboards, ownership and decision records, evidence structures, release gates, and explicit separation of working information from validated and approved records.

The effect

Less repeated searching and manual status reconstruction, clearer evidence gaps, and a more reliable view of the next decision or control required.

Operating range

Intelligence before action.
Tools matched to the decision.

Strategic intelligence

Market, competitor, company, account, board, and executive research synthesized into a sourced point of view before the decision or meeting.

Commercial judgment

Enterprise sales, national accounts, growth strategy, sales leadership, marketing, and organizational development grounded in real buying environments.

Operating systems

Portfolio visibility, decision records, controlled knowledge, field coordination, workflow design, and operating cadence.

Applied AI infrastructure

Agents, local models, browser automation, structured knowledge, verification, approval systems, workload controls, backups, and rollback.

Start with the real work

Bring me the decision your team needs to make better.

Whether you are building from zero or working through accumulated complexity, we will identify the intelligence the decision requires, design the operating system around it, and measure the advantage created.

Portrait of Michael K. Doane
Michael K. DoaneStrategic intelligence · Operations · Applied AI