Courses on the IT operating model and its economics, portfolio intelligence and AI-ready data, rationalization and modernization, AI governance and exposure management, and AI operations and agents. Each course is a concise knowledge pack of frameworks, decision criteria and common pitfalls, written for the people who run enterprise technology.
Choose your role for a suggested sequence of four courses. Every course stands on its own, so you can also begin anywhere.
The tracks follow the sequence of IT decisions: setting direction, establishing the facts, changing the portfolio, governing risk and running operations. More courses will be added to each track. Get notified when they are published.
The IT operating model as agents take on routine work, and the economics of IT, from cost transparency to unit cost, AI spend and value.
How the IT function changes when software agents carry a growing share of the work, and how to lead that change.
Cost transparency, unit economics and value realization across cloud, SaaS, data cloud platforms, data centers and AI.
Establishing from evidence what the organization runs and how it connects, and whether its data is ready for each intended AI use.
Building an evidence-based model of your applications, infrastructure and dependencies that stays current.
Preparing enterprise data for retrieval, agents and models: fitness, context, lineage, permission and access.
Rationalizing the application portfolio and modernizing what stays, with results confirmed at switch-off and cutover.
Deciding what to retire, consolidate, modernize or keep, and carrying those decisions through to switch-off.
Recovering knowledge from legacy code, choosing the right strategy, and demonstrating equivalence before cutover.
Governing AI against law and standards, and reducing exposure by prioritizing on evidence and removing what is not needed.
Turning regulation and frameworks into a working governance system for AI.
Prioritizing what attackers can reach and exploit, and reducing the attack surface itself.
Applying AI to IT operations, from diagnosis to remediation under guardrails, and building and running AI agents as production services.
From telemetry and service level objectives to automated diagnosis and governed remediation.
Architecture, protocols, identity, evaluation and operations for enterprise AI agents.
Twelve to fourteen slides per course: frameworks, decision criteria, common pitfalls and a closing summary.
Each course lists its sources under Further reading, from NIST and CISA to FIRST and the FinOps Foundation.
Every course is available as a PDF to share with your team or use in a working session.
No registration or payment. Read the slides in the browser or download the PDF.
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We run private working sessions that apply these courses to your own estate and portfolio.