Advancing Intelligence

AI Insights

Don’t even think about bringing AI/ML in-house, seriously!

Bringing proprietary AI in-house is not a workable plan that has occasional side effects. It is a bad move with a straight line to failure – and that’s not hyperbole. Gartner reports that 85% of enterprise AI initiatives fail directly, meaning they never advance beyond the prototype (proof-of-concept) stage. Producing a fieldable product is an outright impossibility for most enterprise teams. Those that beat the odds by getting past the prototype stage still only stand a desperate hope for success. Success with proprietary AI requires surviving a gauntlet of execution challenges covering training at scale, generalization, performance, field qualification testing, software engineering, systems integration, human-centered design, and other workstreams. Mix in a highly technical domain that is packed with esoteric engineering challenges and the typical enterprise stands no chance. I’m sorry, but that’s the reality.

Read More »

Stop trying to be Agile

Abandon all efforts to get better at Scrum, SAFe, or whatever Agile snake oil you’ve been pitched. None of those make a difference. Whether your organization is good at Scrum, or terrible at it, the outcome is the same. As for SAFe, the closer you get – the worse things are. For ordinary software development

Read More »