Computer Impressions

Who this is for

• Organizations whose legacy applications create operational fragility, key-person dependencies, or compliance exposure.
• Companies running aging ERPs (Oracle, SAP, custom Clipper/FoxPro, vendor-EOL platforms) and weighing whether to modernize or maintain.
• Executive teams that cannot afford "rip and replace" — operational continuity is non-negotiable.
• Programs that have already attempted modernization and stalled, where a rescue is the realistic path.

What I provide

• Risk-sequenced execution — address highest-risk dependencies first, not the easiest or most visible systems.
• Institutional knowledge capture — systematic documentation of how systems actually work, not just how they're supposed to work.
• Parallel operation during transitions — new systems proven alongside legacy before cutover, with rollback at every phase.
• ERP conversions — software selection, vendor negotiation, implementation, cutover coordination, post-go-live support.
• Integration modernization — legacy/modern data flows, API design, sequenced retirement of point-to-point connections.
• Governance and security embedded throughout — designed in, not retrofitted.
• AI-ready architecture as outcome — modern infrastructure built to support governed AI deployment.

How I make knowledge stick: the Applied Hyper-Learning Method

One of the most common reasons modernization fails is that the new system gets documented but never actually understood. The team running it after cutover doesn't carry the institutional knowledge the legacy team carried in their heads — and "the documentation" isn't a substitute for that.

The Applied Hyper-Learning Method is a seven-framework operating system I use to make knowledge transfer real. Originally built to onboard the engineers I work with, it applies equally to client engineering teams during knowledge-transfer engagements. The frameworks span three phases — Learn the Basics, Learn to Produce, Learn to Thrive — and include patterns like The Handoff, Problem-Solving Sequence, Decision-Making Discipline, First Pass vs. Best Practice, Win-Win-Win, and The Unstuck Sequence.

See the seven frameworks →

Engagement models

Typical outcomes

• Legacy fragility reduced and single-person dependencies eliminated.
• Improved security posture, audit readiness, and compliance documentation.
• AI-capable infrastructure with data governance and security frameworks in place.
• Systems that support business growth instead of constraining it.
• Documented, transferable knowledge replacing tribal understanding.