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ConstructionMethodFour-week pilotAboutDiagnostic & contact
SheetG-00
FieldPRACTICE
StatusCURRENT
Version03

Your company already knows more than your AI does.

Heilman Operations organizes the company knowledge AI can rely on, establishes practical rules, builds repeatable workflows around real work, trains the people who use them, and measures whether the result is worth keeping.

Book the call → Explore the four-week pilot →
Layer 01
SourcesNot defined
What already exists, across systems, people, and projects.
Layer 02
KnowledgeNot defined
Captured, connected, and curated into one record.
Layer 03
WorkflowNot defined
Real work turned into something repeatable.
Layer 04
ReviewNot defined
Rules, permissions, and an accountable reader.
Layer 05
OutputNot defined
Trained people, and a measured result.
OUTPUT REVIEW WORKFLOW KNOWLEDGE SOURCES
F01Why most of this fails Published research, not opinion
95%

of enterprise AI pilots produce no measurable impact on the business.

MIT Media Lab, Project NANDA — The GenAI Divide: State of AI in Business 2025. Based on 300+ deployments, roughly 150 executive interviews and 350 employee surveys, against an estimated $30–40 billion of enterprise spend.

01
The cause is organizational, not technical. MIT calls it the learning gap: tools that never integrate into the workflows, structures and culture of the company. Model quality was not the differentiator.
02
The money went to the visible work. More than half of AI budgets went to sales and marketing pilots — high visibility, low return. The measurable returns came from back-office work.
03
Internal-only builds failed most. Pilots pairing internal specialists with outside expertise succeeded roughly 67% of the time, against roughly 22% for IT-only builds.
04
It is already happening without you. Personal AI tools are in use at more than 90% of firms — including the ones whose official pilots produced nothing.

This practice is built against those four findings. Each one has a named countermeasure in the method, and the countermeasures are what the four weeks actually deliver.

See what each one changes →
W01Recurring work / operating field Same request, two states
TODAYThe same request.
Every time.
Request
"Send me the latest cost summary."
Scattered files
final_v3_old
Hard to find. Hard to trust.
Personal AI
Different answers. No memory.
Mixed sources
Conflicting information. No context.
>>>
Approved sources
CurrentOwned
One authoritative record.
Workflow
Written down. Repeatable.
Human review
Someone accountable signs it.
Reusable output
Kept where the next person finds it.
C-01Initial applied field Construction

Construction.

The problem exists across established companies. The work starts with self-performing contractors — mechanical, electrical, and fire protection — because their institutional knowledge is unusually deep, spread across project systems, coordination models, fabrication history, and the people who ran the job.

Open the construction study →
One qualifications package, drawn as a schedule: the same submission assembled sequentially, then drawn from prepared knowledge. Both end at the same reviewer.
P-03Four-week pilot Fixed scope, fixed fee
ObserveStructureDeployMeasure

Four weeks to find where AI actually helps, prove it on real work, and leave you with the rules, the workflows, and a measured before and after.

Open the commission document →
A-04Principal Nate Heilman
20+ yearsSystems, technology, and operational leadership.
Marine Corps systems leadershipLed network environments supporting operational units and emerging unmanned aircraft systems.
Former COOFirmwide operations and delivery at The Charles F. Bolden Group.
Six operating principles govern every engagement. They come from environments where systems had to run without their author present, and where access to high-value assets was accounted for rather than assumed. The same discipline, applied to how a company adopts AI.
Read the operating doctrine → Full background →
Next C-01 Construction See the problem in your own work →

Start with a conversation about the work.

Thirty minutes, no deck. Where AI is already showing up in your company, and which department is worth starting with.

Three questions about the work
Contact

nate@heilmanops.com
Hopkinton, Massachusetts