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AI Podcasts

December 26, 2025

⚡️GPT5-Codex-Max: Training Agents with Personality, Tools & Trust — Brian Fioca + Bill Chen, OpenAI

Latent Space

AI
Key Takeaways:
  1. The Macro Shift: Agentic Abstraction. We are moving from Model-as-a-Service to Agent-as-a-Service where the harness is as important as the weights.
  2. The Tactical Edge: Standardize your CLI. Use tools like ripgrep (RG) that models already have "habits" for to see immediate performance gains.
  3. The Bottom Line: The next 12 months will see the end of manual integration engineering as agents become capable of navigating UIs and legacy terminals autonomously.
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December 26, 2025

Steve Yegge's Vibe Coding Manifesto: Why Claude Code Isn't It & What Comes After the IDE

Latent Space

AI
Key Takeaways:
  1. The commoditization of syntax means architectural judgment is the only remaining moat. As the cost of code hits zero the value of intent skyrockets.
  2. Replace your manual refactoring workflows with a burn and rebuild strategy. Use agents to generate entirely new modules instead of patching old ones.
  3. Seniority is no longer a shield against obsolescence. You must spend the next six months building your agentic intuition or risk being replaced by a PhD student with a prompt.
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December 28, 2025

One Year of MCP — with David Soria Parria and AAIF leads from OpenAI, Goose, Linux Foundation

Latent Space

AI
Key Takeaways:
  1. The Macro Evolution: Standardized communication layers are replacing custom API integrations. This commoditizes the connector market and moves value to the models that best utilize these tools.
  2. The Tactical Edge: Standardize your internal data tools using MCP servers today. This ensures your company is ready for autonomous agents that can discover and use your resources without manual API integration.
  3. The Bottom Line: The agentic stack is consolidating around MCP. Interoperability is no longer a feature; it is the foundation for the next decade of AI utility.
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December 26, 2025

How Claude Code Works - Jared Zoneraich, PromptLayer

AI Engineer

AI
Key Takeaways:
  1. The transition from Prompt Engineering to Context Engineering where the goal is keeping the model's workspace small and relevant.
  2. Replace your complex classification prompts with a single Bash tool. Let the agent write its own Python scripts to handle data transformations.
  3. The winners in the agent space will not be those with the most complex logic. They will be the ones who build the best tools for the model to use.
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December 26, 2025

Shipping AI That Works: An Evaluation Framework for PMs – Aman Khan, Arize

AI Engineer

AI
Key Takeaways:
  1. The Macro Shift: From Model-Centric to Eval-Centric. The value is moving from the LLM itself to the proprietary evaluation loops that keep the LLM on the rails.
  2. The Tactical Edge: Export production traces and build a "Golden Set" of 50 hard examples. Use these to run A/B tests on every prompt change before hitting production.
  3. The Bottom Line: Reliability is the product. If you cannot measure how your agent fails, you haven't built a product; you've built a demo.
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December 26, 2025

How AI Will Reshape The Economy In 2026 (a16z Big Ideas)

a16z

AI
Key Takeaways:
  1. The transition from passive data storage to active agentic execution across both financial and industrial sectors.
  2. Target unsexy legacy industries like mortgage servicing or rare earth processing where the margin for improvement is highest.
  3. 2026 marks the year where software eating the world moves from the screen to the physical supply chain and the autonomous agent.
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December 26, 2025

⚡️GPT5-Codex-Max: Training Agents with Personality, Tools & Trust — Brian Fioca + Bill Chen, OpenAI

Latent Space

AI
Key Takeaways:
  1. The transition from chatbots with tools to agents that build tools marks the end of the manual integration era.
  2. Stop building custom model scaffolding and start building on top of opinionated agent layers like the Codex SDK.
  3. In 12 months, the distinction between a coding agent and a general computer user will vanish as the terminal becomes the primary interface for all digital labor.
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December 26, 2025

Steve Yegge's Vibe Coding Manifesto: Why Claude Code Isn't It & What Comes After the IDE

Latent Space

AI
Key Takeaways:
  1. Software is moving from a scarce resource produced by humans to a commodity generated by agentic swarms.
  2. Move beyond simple chat interfaces and start experimenting with agentic loops plus MCP servers to automate entire workflows.
  3. The AI Engineer is the new F1 driver of tech. Mastery of the tool belt matters more than the ability to build the car from scratch.
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December 24, 2025

METR's Benchmarks vs Economics: The AI capability measurement gap – Joel Becker, METR

AI Engineer

AI
Key Takeaways:
  1. The Capability-Utility Gap is widening. We see a divergence where models get smarter but the friction of human-AI collaboration keeps productivity flat.
  2. Deploy AI for mid-level engineers or low-context tasks. Avoid forcing AI workflows on your top seniors working in complex legacy systems.
  3. The next year will focus on reliability over raw intelligence. The winners will have models that require the least amount of human babysitting.
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Crypto Podcasts

December 29, 2025

Investing Trends for 2026: DeFi, Tokenization, Capital Formation, Speculation & AI

Bankless

Crypto
Key Takeaways:
  1. The move from human-centric trading to an agent-led economy where programmable money is the native substrate.
  2. Prioritize startups building verticalized tokenization for high-yield exogenous assets rather than generalized service providers.
  3. Crypto is becoming the invisible backend for global finance. Over the next year, the winners will be those who hide the blockchain while using its efficiency to crush traditional margins.
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December 28, 2025

Getting To The Bottom Of Quantum w/ Rearden

The Gwart Show

Crypto
Key Takeaways:
  1. The Macro Transition: Cryptographic security is moving from static models to active systems that must anticipate both classical and quantum breakthroughs.
  2. The Tactical Edge: Audit your UTXOs to ensure no address reuse and keep your Xpubs strictly offline.
  3. The Bottom Line: Quantum risk is a long tail event that serves as a catalyst for necessary Bitcoin upgrades like OP_CAT and BIP 360.
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December 28, 2025

Getting To The Bottom Of Quantum w/ Rearden

The Gwart Show

Crypto
Key Takeaways:
  1. The Macro Shift: Technical reality is decoupled from venture capital hype.
  2. The Tactical Edge: Use hashed addresses and run a node.
  3. The Bottom Line: Quantum is an engineering hurdle rather than an existential crisis for the next decade.
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December 28, 2025

What Can DeFi Users Actually Do on Canton Network Today?

The DCo Podcast

Crypto
Key Takeaways:
  1. The Macro Shift: Institutional Migration. As large-scale capital seeks on-chain efficiency, it will gravitate toward networks that offer privacy as a default.
  2. The Tactical Edge: Monitor Infrastructure. Track the rollout of Canton-native stablecoins to identify when the liquidity floodgates open for professional traders.
  3. The Bottom Line: Canton is building for the "Quiet Money." If you are looking for the next dog coin, look elsewhere, but if you want to see how the global financial system actually moves on-chain, this is the network to watch over the next year.
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December 26, 2025

2025 Year in Review

Bell Curve

Crypto
Key Takeaways:
  1. The transition from "Infra-as-an-Asset" to "Infra-as-a-Service" means valuations will now track real cash flows rather than speculative multiples.
  2. Prioritize protocols that pivot to B2B strategies or vertical integration.
  3. The next 12 months will reward those who build for users rather than for the "crypto-native" echo chamber.
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December 26, 2025

Keith Singery & Garrett Oetken: TAO.com Wallet, Bittensor, TAO Flow, Governance, Subnets | Ep. 77

Ventura Labs

Crypto
Key Takeaways:
  1. The Macro Transition: Capital is migrating from passive staking to active participation in specific intelligence commodities.
  2. The Tactical Edge: Audit the founders behind subnets before swapping tokens.
  3. The Bottom Line: Bittensor is becoming a modular AI stack where the value lies in the integration of specialized subnets rather than isolated performance.
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