by Paul Helmick | Mar 1, 2026 | Videos
Paul’s Perspective: If your team is using AI in an ad hoc way, results vary by who wrote the prompt and how much context they remembered to include. Treating key workflows as reusable “skills” turns scattered experimentation into repeatable operations, which is...
by Paul Helmick | Mar 1, 2026 | Videos
Paul’s Perspective: If you’re using AI for real work, the bottleneck quickly becomes “agent reliability” and “context budget,” not model quality. Token-efficient web state plus a consistent command surface makes agent runs cheaper, more repeatable, and easier to...
by Paul Helmick | Feb 28, 2026 | Videos
Paul’s Perspective: If your company still thinks of technology as deterministic tools that do what you program, you’ll underinvest in data, governance, and new operating models. Leaders who treat AI as a learning system will redesign workflows, decision rights,...
by Paul Helmick | Feb 28, 2026 | Videos
Paul’s Perspective: AI agents move from novelty to leverage only when they’re treated like production systems: routed by cost/quality, instrumented with checks, and constrained with permissions. If you’re considering agents for customer support, operations,...
by Paul Helmick | Feb 28, 2026 | Videos
Paul’s Perspective: Most teams waste time debating which model is “best” and ignore the bigger decision: are you building a delegation engine for self-contained tasks, or a coordination layer for cross-functional work. That choice affects governance, process...
