AI Weekly Malaysia

Ethan Mollick walks back his own thesis that working with AI agents would require human-style management — specifying delegation and agent org structure — saying the Bitter Lesson caught him out: his research found planning steps now add much less value because models plan for themselves, just as elaborate retrieval plumbing and prompt chains were overtaken by models that seek information on their own. His demo is a one-prompt music video where Fable wrote lyrics and sent them to Suno, and Opus 5.5 did everything else in code with no image generation and no feedback. He frames the current wave as 'Clawlikes' — Meta's Muse (currently the number one App Store app), OpenAI's dots, plus Grok Bot, Instinct and Gemini Spark — agents that get computer access and connect to your email and financial records.

Why: If you maintain multi-step prompt chains or hand-built retrieval/orchestration scaffolding, this says the payoff shrinks with every model release — benchmark a single-prompt baseline against your pipeline before investing more engineering in the scaffolding. Separately, Muse and dots ask users to hand over account connections to email and financial data, so if you ship anything in that space, the competitive bar and the user's security expectations are being set by agents that already request that access.