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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 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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December 24, 2025

PhD Bodybuilder Predicts The Future of AI (97% Certain) [Dr. Mike Israetel]

Machine Learning Street Talk

AI
Key Takeaways:
  1. The Macro Shift: Scaling laws are hitting a diminishing return on raw data but a massive acceleration in reasoning. The shift from statistical matching to reasoning agents happens when models can recursively check their own logic.
  2. The Tactical Edge: Build for the agentic future by prioritizing high-context data pipelines. Models perform better when you provide massive context rather than relying on zero-shot inference.
  3. The Bottom Line: We are 24 months away from AI that makes unassisted human thought look like navigating London without a map. Prepare for a world where the most valuable skill is directing machine agency rather than performing manual logic.
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December 23, 2025

Continual System Prompt Learning for Code Agents – Aparna Dhinakaran, Arize

AI Engineer

AI
Key Takeaways:
  1. The transition from model-centric to loop-centric development. Performance is now a function of the feedback cycle rather than just the weights of the frontier model.
  2. Implement an LLM-as-a-judge step that outputs a "Reason for Failure" field. Feed this string directly into a meta-prompt to update your agent's system instructions automatically.
  3. Static prompts are technical debt. Teams that build automated systems to iterate on their agent's instructions will outpace those waiting for the next model training run.
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December 23, 2025

Developer Experience in the Age of AI Coding Agents – Max Kanat-Alexander, Capital One

AI Engineer

AI
Key Takeaways:
  1. The Macro Shift: The transition from writing to reviewing as the primary engineering activity. As agents generate more code, the human role moves from creator to editor.
  2. The Tactical Edge: Build CLIs for every internal tool to give agents a native text interface. This increases accuracy and speed compared to visual automation.
  3. The Bottom Line: Developer experience is the infrastructure for AI. Investing in clean code and fast feedback loops is the only way to ensure AI productivity gains do not decay over the next 12 months.
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December 23, 2025

Small Bets, Big Impact Building GenBI at a Fortune 100 – Asaf Bord, Northwestern Mutual

AI Engineer

AI
Key Takeaways:
  1. The Macro Shift: The transition from "Human-in-the-loop" to "Agent-as-the-interface" for enterprise data.
  2. The Tactical Edge: Audit your metadata quality now because LLM accuracy is a direct function of your documentation.
  3. The Bottom Line: Success in enterprise AI is not about the biggest model but about the smallest, most frequent wins that build institutional trust.
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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-Productivity Gap. We are entering a period where model intelligence outpaces our ability to integrate it into high stakes production.
  2. Audit your stack. Identify tasks where "good enough" generation is a win versus high context tasks where AI is currently a net negative.
  3. Do not mistake a climbing benchmark for a finished product. For the next year, the biggest wins are not in smarter models but in better verification loops.
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December 24, 2025

PhD Bodybuilder Predicts The Future of AI (97% Certain) [Dr. Mike Israetel]

Machine Learning Street Talk

AI
Key Takeaways:
  1. The transition from simple Large Language Models to Reasoning Models marks the end of the stochastic parrot era.
  2. Build agentic workflows that utilize high-context windows for recursive problem solving.
  3. We are moving toward a world where intelligence is a commodity. Your value will shift from knowing things to directing outcomes over the next 12 months.
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Crypto Podcasts

January 24, 2026

Gold Sets the Bar, But Bitcoin Can Catch Up. Here’s How: Bits + Bips

Unchained

Crypto
Key Takeaways:
  1. The institutionalization of Bitcoin has temporarily sacrificed its digital gold status for liquidity, creating a massive opportunity for those who can stomach the volatility before the next decoupling.
  2. Monitor Japanese government bond yields as a leading indicator for global risk tolerance.
  3. Bitcoin is currently a liquidity sponge, not a bunker. Expect it to follow the Trump Put and tech earnings until its volatility profile mirrors a currency rather than a speculative stock.
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January 23, 2026

The Intersection of AI and Crypto: What Worked, What Didn’t, and What’s Next | Roundup

Bell Curve

Crypto
Key Takeaways:
  1. The market is moving from the "Compute Layer" to the "Agentic Layer." Owning the GPU is less valuable than owning the agent that controls the wallet.
  2. Build agent-first interfaces. Stop designing for human clicks and start structuring your data so an LLM can execute transactions on your behalf.
  3. The next 12 months belong to on-chain agents that handle treasury ops and commerce. The "decentralized GPU" narrative is dead. The "AI Agent with a bank account" narrative is just beginning.
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January 23, 2026

The “Quantum Threat” Behind Bitcoin’s Sudden Sell-Off

Bankless

Crypto
Key Takeaways:
  1. The transition from global cooperation to regional protectionism is driving a capital outflow loop that favors hard assets over sovereign debt.
  2. Monitor the development of quantum-resistant signatures on alternative L1s to hedge against Bitcoin’s potential cryptographic obsolescence.
  3. The next year will be defined by the race to tokenize real-world assets and the struggle to maintain protocol relevance as TradFi giants enter the arena.
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January 22, 2026

DePIN’s Biggest New Deal: Valeo x NATIX | Alireza Ghods

Proof of Coverage Media

Crypto
Key Takeaways:
  1. The transition from digital-only AI to Physical AI requires a massive bridge of high-fidelity video data.
  2. Monitor DePIN projects that move from "map-to-earn" to "train-to-earn" for foundational models.
  3. NATIX is no longer just a mapping company; it is the data refinery for the next generation of autonomous machines.
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January 21, 2026

Markets Are Entering A Wartime Economy | Cem Karsan

Forward Guidance

Crypto
Key Takeaways:
  1. The transition from a supply-side model to a populist-driven wartime economy makes inflation a permanent feature rather than a bug.
  2. Rotate out of traditional portfolios into non-correlated volatility strategies and hard assets.
  3. The next decade belongs to those who recognize that the rules-based order has been replaced by a raw competition for strategic resources.
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January 21, 2026

How Nansen’s New Trading Agent Makes It Easier to Follow the Smart Money Onchain

Unchained

Crypto
Key Takeaways:
  1. The commoditization of technical infrastructure means alpha moves from who has the data to who has the best prompts.
  2. Test agentic workflows with small capital amounts to identify where natural language outperforms manual execution.
  3. The next 12 months will see a transition from manual click-and-sign trading to intent-based portfolio management.
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