Insights & practical guides

Better decisions.
Better AI in practice.

Our thinking on the work behind enterprise AI: what to build, how to know it works, and who owns it next.

For the leaders making the investment,
the teams building it,
and the people making it work.

Start here / Our perspective

Make AI an operating capability

Buying access to a model is one decision. Building a workflow your business can accept, operate, and improve takes several more.

Read the perspective

Perspective 3 min read

Five decisions that matter

  1. The work

    Define the outcome and its owner.

  2. The people

    Design judgment into the workflow.

  3. The evidence

    Test what must go right—and what can fail.

  4. The ownership

    Prepare the team to operate it.

  5. The value

    Measure the work after release.

01 / Choose the work

Make the investment decision.

Define where AI belongs, what success means, and whether the work is worth changing.

Perspective 3 min read

Make AI an operating capability

Five decisions that turn an AI initiative into something a business can own and improve.

For executives and transformation sponsors

Decision guide 4 min read

Choose your first AI workflow with evidence

A practical way to compare AI opportunities, test the business case, and decide whether to build, buy, improve, or stop.

For business sponsors and transformation leads

02 / Build with evidence

Make the result inspectable.

Connect knowledge, evaluate real work, and distinguish a plausible response from an accepted outcome.

Engineering guide 4 min read

Test the workflow before you trust the result

Build an evaluation set that tests completed work, difficult inputs, permissions, and failure recovery—not just plausible answers.

For engineering leads, domain reviewers, and release owners

Architecture guide 4 min read

Build a knowledge assistant people can trust

Design source ownership, permissions, retrieval, and answer acceptance together so people can inspect and use the result.

For knowledge owners, architects, and service leaders

Perspective 3 min read

Why independent verification matters

Separate what an AI system says happened from the evidence needed to accept its work.

For architects, engineering leads, and control owners

03 / Own the capability

Make it work after launch.

Prepare the people, responsibilities, and operating practices that keep the workflow useful.

Operating playbook 4 min read

Who owns the AI capability after launch?

The decisions, handover assets, and change controls that keep an AI workflow usable after the implementation team leaves.

For operating owners, delivery sponsors, and procurement teams

Workshop guide 3 min read

AI workflow readiness checklist

Assess business value, context, controls, and ownership together. Turn unanswered questions into decisions with an owner and evidence.

For business, technology, and operating owners

Take it into the meeting

Working documents.
Ready to adapt.

Editable text templates for your own environment. No email required. Add your evidence, owners, and decisions.

Engineering in the open

Explore the implementation, too.

Our open-source work gives you another way to examine how we approach agent connectivity and reliability.

Explore our engineering