Afleveringen
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0:00 - Opening
0:50 - HSMs for agentic payments & the security tradeoff in personal AI
8:36 - The fragility of cloud security
11:43 - Vora's compartmentalized architecture for personal AI
14:50 - Why Fable 5 feels nerfed
20:13 - Fable 5 isn't a big deal because intelligence is no longer the bottleneck (data & harnesses are)
23:38 - Local models are getting useful: Hermes Agent, Qwen 3.6, and LLM wikis
28:18 - Why fast local inference with DeepSeek v4 Flash changes things
35:00 - Better workflows (i.e., HumanLayer AI IDE) beats more agents
40:40 - Planning systems for AI coding
52:00 - Fable 5 and model ceilings/diminishing returns
55:00 - Personal data as an AI moat
1:00:43 - Intelligence = search efficiency
1:08:30 - Why harnesses matter more than models
1:13:30 - Reasoning versus stored knowledge
1:21:10 - Why AI is so good at coding
1:28:13 - Export controls and AI gatekeeping
1:41:55 - Decentralization as civilizational infrastructure
1:56:30 - Practical steps toward AI sovereignty
2:04:20 - Using AI to dumb vs strengthen yourself
2:07:40 - Human verification in the age of cheap answers
Everyone is focused on Fable 5, but what if the model wars are becoming a distraction? Jesse and Dustin discuss why the next phase of AI is probably less about raw model intelligence and more by data, harnesses, local hardware, memory, workflows, and control. The future may belong not just to the most powerful model, but the systems and stack around it.
🌐Learn more about Delegance at delegance.ai
🌐Learn more about Vora at vora.io
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0:00 0xSero intro
3:00 Finding the best models for your machine (local.ai)
7:29 Why choosing local models is so hard
12:15 Specs that mislead users
14:15 Memory bandwidth is the real bottleneck
16:26 Qwen on cheap consumer hardware
18:13 Gemma, Strix Halo, and faster local models
20:00 How diffusion models could change speed
21:55 Fable 5 as a turning point & AI export controls
26:57 What powerful models actually threaten
33:57 Should powerful models stay open?
39:20 When AI helps attackers and defenders
46:32 'AI safety' in the social media age
53:50 Why local AI becomes personal survival gear
1:03:30 The economic case for local AI
0xSero joins Jesse and Dustin to discuss the local AI hardware boom, why running models at home is still so confusing, and how open-weight AI, personal agents, and sovereign intelligence could shape the future.
🌐Learn more about Delegance at delegance.ai
🌐Learn more about Vora at vora.io
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Zijn er afleveringen die ontbreken?
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0:00 - Opus 4.8 agent workflows
7:02 - Ultracode and long coding workflows
17:05 - Why AI gets stuck in bad patterns
24:12 - What makes AI an actual collaborator
31:33 - Why specialization will beat one big model
36:14 - The real debate behind AI jobs
43:21 - The abundance case for AI
47:31 - The political roots of AI fear
59:37 - The new human premium & what AI reveals about human value
1:03:57 - The case for decentralized AI
1:11:29 - How AI helps rethink desire & make better choices
1:16:23 - Struggle unlocks human potential
Jesse and Dustin explore how Opus 4.8 and new agent workflows are changing the way people build with AI, then zoom out to the bigger questions: why AI should push back, why the future may be many specialized models, and the growing importance of decentralized AI.
🌐Learn more about Delegance at delegance.ai
🌐Learn more about Vora at vora.io
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0:00 What AI layoffs are getting wrong
5:54 The most important trait to hire for now
14:46 How AI unlocks untapped potential
22:04 Heidegger on fear & anxiety and AI’s self-help potential
31:50 Walter Benjamin and the main human job in an AI world
44:31 Why Claude feels special & how prompts create personality
50:47 Gemma 4 with vs without a system prompt
54:56 AI is still missing real planning
1:04:07 Did LLMs unlock the ability to simulate consciousness?
1:12:28 Claude Code’s permission security theater
1:15:03 Return to consciousness discussion
A wide-ranging conversation covering what AI layoffs are getting wrong, why Claude feels different, how prompts shape personality, and why AI forces us to rethink consciousness.
🌐Learn more about Delegance at delegance.ai
🌐Learn more about Vora at vora.io
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0:00 - Matt Molineaux intro
1:30 - Agents before LLMs
3:23 - Why Matt hated LLMs at first
5:34 - Why AI (and LLMs) need world models
13:05 - The problem with LLMs' nondeterminism & the case for adding logic
21:49 - How & why open-weight local models could win
25:22 - Who owns AI-generated work?
31:17 - Can governments control LLM outputs?
35:30 - Mythos and AI danger messaging
41:16 - Whose ethics govern AI?
48:37 - Filtering the internet through agents
56:03 - Controlling AI is short-hand for controlling humans
1:01:43 - How & why decentralization builds resilience
1:06:48 - Can AI solve coordination problems?
1:16:12 - "Personal lens": Aligned local AI project
1:25:15 - Why LLMs still need logic
1:34:30 - The stack after LLMs
A conversation with Delegance co-founder Dr. Matthew Molineaux on what comes after LLMs, why AI needs world models and logic, and how open-weight local inference could shape the next AI stack.
🌐Learn more about Delegance at delegance.ai
🌐Learn more about Vora at vora.io
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0:00 - Introducing Max Webster & the first trilogue
2:32 - Is reality made of language?
8:10 - Do LLMs understand the world?
12:09 - Is language more than description?
18:51 - The hidden power of naming
25:28 - The language beneath everything
29:41 - How meaning changes life
36:57 - The limits of thinking & concepts
42:40 - The weird psychology of vibe coding & why it gets emotional
49:04 - Are LLMs enough for superintelligence?
58:20 - Could AI self-perpetuate and run without humans?
1:06:18 - What AI reveals about us
1:12:24 - Is there something beyond language?
1:24:03 - Why imagination makes language powerful
1:30:15 - The infinite game after AI
A wide-ranging conversation with Max Webster on why LLMs work better than they “should,” what language reveals about reality, and what AI reveals about the human mind.
🌐Learn more about Delegance at delegance.ai
🌐Learn more about Vora at vora.io
🌐Learn more about Hivemind at hivemind.vc
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0:00 - Why AI is your birthright (if you're American or European)
5:00 - The fight over training data
10:29 - Was AI invented or discovered?
18:31 - Why open models matter
27:34 - Building a better AI workflow
47:44 - Why agents need world models
56:52 - Choosing the right AI & why AI needs more than LLMs
1:11:51 - Coding as discovery not execution
1:13:56 - Can the world become language?
1:28:23 - How names unlock understanding
1:41:00 - Why private AI matters
1:47:30 - Will superintelligence = superwisdom?
Episode 2 of Decentralizing AI with Delegance co-founder Dustin Dannenhauer and Vora co-founder Jesse Posner.
🌐Learn more about Delegance at delegance.ai
🌐Learn more about Vora at vora.io
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Timestamps:
0:00 Podcast origins and the AI moment
3:11 Dustin’s background: AI research, bitcoin, Nostr, and decentralization
11:20 Jesse’s background: from philosophy and law to bitcoin security
17:18 Dustin’s startup (Delegance) vision and world models explained through chess
25:45 Determinism: why AI works better with structure and clear rules
34:05 Reflecting on process: how to debug better, waste fewer tokens, and improve workflow
50:50 The end of apps and the rise of personal AI interfaces
1:06:48 The stakes of AI that serves the individual
Delegance co-founder Dustin Dannenhauer and Vora co-founder Jesse Posner kick off the Decentralizing AI podcast by introducing their backgrounds and exploring some of the ideas that will shape the show, including: AI, bitcoin, decentralization, world models, the future of software, and importance of AI serving the individual rather than the interests of platforms, governments, or other institutions.
🌐Learn more about Delegance at delegance.ai
🌐Learn more about Vora at vora.io
