AI Updates on 2026-02-22

Anthropic releases Claude Opus 4.6 with improved capabilities, though specific benchmarks show mixed results on complex rendering tasks @deedydas

Shopify deployed AI coding assistants across all teams by assigning an intern to each team after discovering interns used AI to complete two-week tasks in one day @tbpn
SaaS companies continue using traditional software tools (Slack, Zoom, Figma, Notion) despite AI coding advances, suggesting implementation complexity remains a moat @fchollet
AI coding tools show jagged capabilities with persistent weaknesses in photorealistic rendering and object interaction despite improvements in basic code generation @deedydas

Public opposition to AI stems from consistent messaging by AI company CEOs about massive job losses, creating rational concern despite current chatbot utility @alexolegimas
AI companies face political challenges from failure to articulate non-ominous future visions beyond vague promises while emphasizing job displacement @emollick
Jaggedness in AI capabilities creates bottlenecks requiring human intervention, with 1000 identical model agents sharing weaknesses unlike diverse human teams @emollick

Real-time video understanding by AI remains underexplored despite economic value in applications requiring AI to watch and interpret the world continuously @emollick
NVIDIA's DreamDojo demonstrates world models from video becoming central to robotics, with pretraining on motor behavior dynamics showing promise over vision-language models @JitendraMalikCV

Research shows AI models become more incoherent rather than systematically misaligned with extended reasoning, challenging assumptions about longer inference @emollick