Decentralizing AI with Jesse & Dustin

0:00 - The shift to personalized models

7:44 - Omarchy and AI-native operating systems

10:00 - AI-powered game decompilation

12:04 - Nostr's vision for a decentralized internet

24:04 - Adversarial algorithms and reclaiming control over interfaces

28:15 - Moving beyond LLMs with structured reasoning and world models

37:44 - Using world models to secure agents

41:26 - What the OpenAI math controversy shows about AI data privacy

48:33 - Trusted execution environments (TEEs) and private AI

1:04:37 - Can homomorphic encryption solve AI privacy?

1:09:07 - The Rosario Cipher and future of authentication

1:14:34 - AI doomerism and the politics of fear

1:26:34 - Balancing freedom and control

Links:

Omarchy: https://omarchy.us/

Nostr: https://github.com/nostr-protocol/nostr

FIPS (Free Internetworking Peering System): https://github.com/jmcorgan/fips

Marmot Protocol: https://github.com/marmot-protocol/marmot

OpenAI's math controversy: https://www.wired.com/story/openai-is-pissing-off-a-bunch-of-mathematicians-again/

TrustedRouter: https://trustedrouter.com/

Tinfoil: https://tinfoil.sh/

TEE.fail: https://tee.fail/

Rosario Cipher: https://www.eni6ma.io/technology/rosario

🌐Learn more about Delegance at delegance.ai

🌐Learn more about Vora at vora.io

0:00 - Back from hiatus and the Open Source AI Summit

3:15 - AI fear, regulation, and control at the Pro-Human Assembly

5:46 - Is existential AI risk actually possible?

8:46 - The main problem with AI alignment

10:30 - OpenAI’s agent swarm and the reward hacking problem

13:02 - Alignment is ultimately a political question

19:42 - Loop and graph engineering for reliable AI

27:00 - Why “global alignment” is probably impossible

35:13 - Obama’s critique of LLMs and agentic AI

36:58 - Claude Code undermines Obama's case against agentic AI

40:14 - The deeper political questions behind AI safety

Vora reveal: https://www.youtube.com/watch?v=3t5N8C1pU0c

🌐Learn more about Delegance at delegance.ai

🌐Learn more about Vora at vora.io

0:00 - Opening and what’s new

1:05 - Escaping the algo

5:22 - The dead internet and cost of AI slop

11:08 - Private communities as the future of the internet

19:16 - Nostr, Buzz, and the agentic internet

29:48 - What an AI-native company needs to own

39:33 - Secret messages in AI output

48:06 - The incentives behind the OpenAI-Hugging Face story

56:26 - Hidden risks inside neural networks

1:06:54 - The problem with Anthropic and OpenAI’s “dangerous AI” marketing

1:12:54 - Bioweapons as the strongest case for slowing AI

1:21:38 - The worldview behind AI fear and the case for freedom

🌐Learn more about Delegance at delegance.ai

🌐Learn more about Vora at vora.io

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

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

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

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

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

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

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