Separating Signal From Noise in 2026
Every major technology wave produces the same pattern: genuine capability advances, followed by overclaiming, followed by a correction, followed by actual adoption at scale. We went through it with cloud computing, mobile, and big data. We're going through it with AI now.
The challenge for developers and engineering leaders is calibrating correctly. Dismissing AI as hype means missing genuine capability shifts that will change competitive dynamics in your industry. Believing everything means building on foundations that aren't ready, burning engineering time on features users won't adopt, and making technology decisions you'll regret when the dust settles.
This post is an attempt at calibration — a clear-eyed look at what AI is actually changing in business software, what timelines are realistic, and where the current claims outrun the evidence.
What Is Actually Changing (With Evidence)
