We're past the hype phase and into the "figuring it out" phase. AI is reshaping how we build, hire, and collaborate, but the reality on the ground doesn't always match the pitch. In this session, Pushpay shares what they are actually seeing across teams and organizations: the common traps, the unexpected side effects, and the coping strategies that are actually working. Come ready for an honest, practical conversation about thriving with AI rather than just surviving it.
What this session is about
Playbook
Editorial commentary · what to actually do about this on Monday
The concept
Past hype phase, into "figuring it out" phase. Honest read on AI's effects on building, hiring, collaborating. Common traps, side effects, coping strategies.
Why it matters
Hype-cycle consensus is wrong. Ground truth from teams in the trenches matters more than vendor decks.
The hard parts
AI's side effects show up months later: skill atrophy in juniors, debugging gaps, code-review fatigue.
Playbook moves
(1) Track AI usage's *second-order effects*. (2) Survey juniors specifically — they're affected differently from seniors. (3) Make first-principles debugging part of the team's training cadence.
The surprise
One of the most common unexpected AI side effects is junior engineers losing the ability to debug systems they didn't write. AI gets them through; the deeper understanding doesn't form. Plan for it explicitly. The juniors you hire today will be your seniors in 3 years; what they're learning now matters.
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Independent editorial perspective — not an official AWS or speaker statement. Designed for executives evaluating what to brief their teams on next.
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