30 mistakes enterprises make with AI transformation, from a practitioner
alex_verem · x · 2026-09-25
Practitioner @mardehaym lists 30 common enterprise AI transformation mistakes: buying AI licences isn't a strategy — define problems and expected improvements first; don't expect every employee to become an AI engineer; agree on what a good answer looks like before prompting, keep verified corrections as test cases and rerun them on changes; and investigate the whole setup (instructions, missing info, tools, surrounding software) before blaming the model.
More from Companies & People
- Meta researcher quips the $14B hire is a 'poaster' two orders of magnitude better — francoisfleuret · 2026-09-25
- Hyperagent launches Rooms, a multiplayer space where agents and humans work together — aakashgupta · 2026-09-25
- TBPN podcast: Meta Connect reactions, Zuck's beer pong controversy, ClusterMAX 3.0 — jordihays · 2026-09-25
- AGI House clarifies: an applied AI lab and VC, no longer a hacker house since 2024 — agihouse_org · 2026-09-25
- bold_lab_ai hiring: postdocs and RAs due Oct 9, strategic partnership PM due Oct 14 — josephdviviano · 2026-09-25
- fal's GenMedia Conference draws Disney's Sean Bailey and Taika Waititi in SF — DynamicWebPaige · 2026-09-25