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AI Podcasts

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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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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Crypto Podcasts

December 23, 2025

Why Isn't Bitcoin Going Up? | Jeff Park

1000x Podcast

Crypto
Key Takeaways:
  1. The retailification of finance is merging public and private markets, making conviction more valuable than spreadsheets.
  2. Monitor high-conviction government rumors or national strategic transitions to front-run institutional capital that is too slow to move on ideology.
  3. Success in the next year depends on viewing volatility and privacy as core features rather than bugs in the system.
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December 22, 2025

Bitcoin Needs Vol, BTC vs Gold, Retail Trading Edge, 2026 Predictions | Jeff Park

1000x Podcast

Crypto
Key Takeaways:
  1. The retailification of finance is merging public and private markets. Every news event is becoming a tradable asset.
  2. Stop competing with bots on spreadsheets. Identify national strategic priorities that drive durable capital flows.
  3. Bitcoin’s next leg up depends on a return to its roots as a volatile and self-custodial alternative to the legacy system.
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December 22, 2025

The State of Crypto, 2026 Predictions & Espresso's Token Launch | Jill Gunter

Empire

Crypto
Key Takeaways:
  1. The transition from Crypto as a Cult to Crypto as a Rail means the next winners will look like boring fintech giants rather than flashy token launches.
  2. Focus on infrastructure projects solving for fast finality and interoperability. These are the toll booths for the coming wave of corporate tokenization.
  3. The next 12 months will be defined by the Corpo Chain explosion. If you are not building for speed and performance, you are building for a niche that is shrinking.
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December 22, 2025

Is The Crypto-Native Era Coming to an End? - Lessons from 10 Years in Crypto

Bankless

Crypto
Key Takeaways:
  1. The transition from "Crypto-Native" to "Invisible Backend" means value accrues to protocols that function like Linux.
  2. Monitor the 2026 IPO window for SpaceX and OpenAI to anticipate a major capital rotation.
  3. Success in the next decade requires building for the 99% who do not care about decentralization.
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December 19, 2025

Crypto Prices Are Down...Builders Aren’t!

Bankless

Crypto
Key Takeaways:
  1. Fiat is failing as a currency, resulting in a push toward assets that maintain or grow purchasing power.
  2. DeFi offers real yield opportunities, making it a compelling alternative for capital preservation.
  3. Traditional finance is validating public blockchains, indicating a significant shift in finance towards crypto integration.
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December 21, 2025

Bittensor Brief #15: $TAO Bull Case + Bitcast SN93

Hash Rate Podcast

Crypto
Key Takeaways:
  1. Strategic Implication: Bittensor's unique decentralized AI model, coupled with Bitcoin-like scarcity and a self-marketing subnet, sets it apart as a foundational AI infrastructure play.
  2. Builder/Investor Note: The $TAO halving creates a significant supply shock. Builders should observe Bitcast's "one-click mining" and AI-powered automation as a blueprint for efficient decentralized applications.
  3. The So What?: The convergence of reduced supply and increased marketing via Bitcast could drive substantial demand for $TAO over the next 6-12 months, making it a critical asset for those tracking the AI and crypto intersection.
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