Build vs. buy
Capability fit, lifecycle cost, switching risk, integration, internal talent, vendor concentration, and the value of control.
Technology-finance depth
Architecture and economics belong in the same room.
Karl evaluates technology through business requirements, control design, total cost of ownership, adoption, and strategic flexibility. Build-vs-buy is rarely a binary choice; the real decision is which capabilities must remain differentiated, which can be standardized, and where integration risk moves.
Technology ROI
Benefits tied to cycle time, quality, capacity, risk, decision speed, and cash—not only licensing cost or claimed hours saved.
Cost allocation
Cost-center, shared-service, and internal-recharge designs that clarify consumption without creating counterproductive behavior.
Security and customization
Authority, data exposure, maintenance, auditability, and exception handling considered with user value and implementation speed.
Applied AI
Governed automation, not automation theater.
Through BlackBoxx.ai, Karl architects and pressure-tests practical AI systems: specialized agents, approval paths, automation, model and application integration, validation controls, and human-review checkpoints.
As an Apple Developer, he has multiple iOS applications in development and uses AI-assisted coding, agentic development tools, and automation to turn business requirements into testable products. The work is hands-on, but the standard remains operational: working software, clear authority, observable behavior, and evidence that the system does what it claims.
His interest in edge and distributed intelligence follows the same logic. Moving inference closer to devices changes latency, privacy, bandwidth, lifecycle management, and governance; it does not eliminate infrastructure.