Christopher SchmidtEnterprise technology leadership
Enterprise platforms · Engineering · Data & AI

Building the enterprise platforms that turn data and AI into operational capability.

I lead engineering organizations, modernize production platforms, and scale enterprise adoption. My work connects architectural depth with organizational accountability and measurable business outcomes.

Explore my leadership work Explore DARF
~5 → ~100

Enterprise customers adopting RTI

Microsoft · United States and Canada · ~24 months

25 / 200+

Direct reports / broader stakeholders

Microsoft · Enterprise supplier risk

~90%

Reduction in operating costs

Precision eControl · Production SaaS

01 / Selected leadership work

Enterprise outcomes.
Hands-on accountability.

Selected work across enterprise adoption, organizational capability, and production platform ownership.

Microsoft01

Scaling a capability into enterprise adoption.

Aligning product, engineering, sales, partners, and enablement around enterprise adoption in the United States and Canada.

~5 to ~100 customers in ~24 months
Explore the leadership case
Microsoft02

Bringing supplier-risk assessment forward into onboarding.

Reframing a roughly 90-day reporting process around the decisions it needed to support, with operational and analytical workstreams that enabled earlier identification of supplier risk.

~90-day baseline · 25 direct reports · 200+ stakeholders
Explore the leadership case
Precision eControl03

Changing the economics of a production platform.

Modernizing a customer-facing SaaS platform while improving operating economics and daily pipeline performance.

~90% lower operating costs
Explore the leadership case

Results are shown in their operating context. Each case distinguishes direct responsibility from cross-functional influence.

View leadership work
02 / How I lead

One use case at a time.
A foundation built to last.

I start with a consequential business decision and an accountable owner, then establish the meaning, data, integration, governance, auditability, observability, and operational controls that use requires.

Read my leadership approach
01

Define the business decision

Start with a specific business outcome, the people affected, and an accountable owner. Define what the system may read, recommend, or change before choosing the technology.
02

Build the foundation it needs

Establish the meaning, data quality, state, integration, governance, auditability, and observability required for this use. A bounded use case is not a reason to omit a critical control.
03

Make operation accountable

Set governed authority, test failure paths, and name the operating owner. Auditability should explain a decision; observability should reveal whether the system and its controls are working.
04

Prove value, then expand

Measure the result against the intended outcome. Reuse what is proven, reassess what changes, and choose the next use case on evidence rather than extending scope by default.

Governance sets the boundary.

Define ownership, permitted behavior, operating limits, and the conditions that require review.

Auditability explains the decision.

Retain the context, evidence, state, and authority needed to reconstruct what happened.

Observability reveals operation.

Expose behavior, failures, control drift, performance, and cost, then connect a signal to an accountable response.

03 / An original framework

Trustworthy answers.
Governed action.

The Data and AI Readiness Framework separates two questions that deserve their own evidence. A reliable answer does not, by itself, establish authority to act.

DARF · 53 capabilities · 8 layers · 2 distinct questions

Explore the framework Try a worked decision
01 / SEMANTIC27 capabilities

Semantic
Readiness

Can you trust the answer?

  • Semantic Integrity
  • Context Stability
  • Analytical Explainability
  • AI Readiness & Interoperability
02 / OPERATIONAL26 capabilities

Operational
Readiness

Can you trust the system to act on it?

  • State
  • Policy
  • Execution
  • Audit

Assess the defined use and its evidence. Do not hide a mandatory failure inside an overall readiness score.

04 / Writing & speaking

Ideas grounded in
operating reality.

Business decisions first, with the architectural depth to explain what makes them possible.

Selected writing
architecture-strategy / 2026-07-09

Stop Dooming the BI Developer

architecture-strategy / 2026-07-02

Why explaining the problem isn't the same as being trusted to fix it

Explore writing & speaking
Selected appearances
FabCon & SQLCon 2026

Implementation Patterns for Fabric Real Time Intelligence

March 19, 2026

Published speaking archive
Professional connections

A conversation about
building what matters.

For professional connections, speaking, and thoughtful discussion about enterprise technology leadership.

Get in touch