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Anish Acharya
@illscience
🦞AI Apps investing @ A16Z; A1111; Boards of Ethos, Krea, Deel, Clutch, Untitled, Happy Robot + more; If you’re not at the table, you’re on the menu
参加 March 2009
3K フォロー中    36.1K ファン
my latest thinking on personal agents (from the pod w @davidpawlan + @joshelman): winners / losers - there's so much discussion of structural losers from personal agents (delta / amzn / comcast) and very little about the relative winners - presumably the long tail of merchants with great products and mediocre marketing benefit a lot - the idea that agents will perfectly mirror their principals is a fantasy imo... agents will have revealed non-rational preferences (i.e. for clean API surfaces) that are those of an alien mind - implied is a consumer research / wirecutter product where agents research and share their experiences with each other agent adoption - we should be giving agents laws and principles vs rules - fears of embarrassment will hold more people back than fears of privacy - agents need to be designed so some implicit preferences stay implicit, so their human can save face - group chats have an implicit social contract, and agents are only part of that contract if they're present from day one - agents can create a level of social indirection that actually brings people closer together (i.e. what tomo is doing with groups of humans who share aspirations) agent networks - if muse / instinct / wabi is consumer openclaw, what is consumer moltbook? - what economic exchanges can agents make on behalf of their humans? - is there a concept of "free" agents that operate within these networks of their own volition?
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David Pawlan, creator of Assistant Benchmark, has tracked 147 AI assistants so far, and in his group chats of AI power users, the number one fear is trust. It comes up in 22% of roughly 3,600 messages. He puts agents through head-to-head tests, like ordering same-day flowers as cheaply as possible or planning a weekend in LA that's both luxurious and cost-efficient, to see which ones can hold competing preferences. He joins a16z's Anish Acharya and Josh Elman to discuss why the scariest agent failures are the embarrassing ones, why agents are where e-commerce was in 1997, why scale is still a moat, and the "dark agent" that could speak to the parts of ourselves we don't reveal. 0:52 Inside a meetup for 100 agent nerds 2:52 Why we'll all have an army of agents 5:36 Trust is power users' top fear 6:28 Building fences around your agent 10:14 Privacy loses to free pizza 12:41 Can agents balance price and speed? 14:19 How agents define luxury differently 19:44 Migrating from one agent to another 21:06 What your photo roll tells an agent 25:48 Will agents make us more rational? 27:38 Why paternalism kills products 31:43 Gossipy agents as social glue 33:41 Scale is still a software moat 36:55 From OpenClaw to agents hanging out 39:23 Agents that introduce you to people 46:15 Predictions and the dark agent idea YouTube: @DavidPawlan @illscience @joshelman
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