Insights
Technology matters, but it is rarely enough by itself. The customer problem, domain expertise, adoption path, and business outcome decide whether the technology becomes useful.
Insights
Manufacturing AI: From Technology to Commercial Value looks at how changes in the manufacturing technology stack affect adoption, differentiation, business outcomes, scalability, and growth.
A commercialization-focused view of why AI value in manufacturing starts with familiar customer outcomes, not with the technology label itself.
Commercial questionIf the business problem is familiar, where does AI create incremental value that customers will recognize and pay for?
Read articleA practical view of how frameworks create discipline while experience, curiosity, and customer context tell a seller when the sales motion needs to change.
Commercial questionIf every customer follows a different path to change, how much of enterprise selling can really be standardized?
Read articleIdeas I'm Exploring
These are areas Jonathan is still pressure-testing, not a public publication queue or settled recommendation set.
Working idea
A working idea about whether public-private infrastructure models could reduce the cost and community friction of data-center development while keeping compute, models, and applications competitive.
The discussion framework separates long-lived, shared infrastructure from fast-moving private technology, asking what protections should follow material public support, how public risk should be ring-fenced for communities and ratepayers, and how supported infrastructure can avoid deciding which compute, model, or application provider wins.
Future thought
Future thoughts on whether agents change the economics of connecting industrial systems, workflows, data context, and outcome-focused software.
Future thought
Future thoughts on where industrial context should live when AI depends on data that carries operational meaning.