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AI Podcasts

December 26, 2025

What I learned at the frontier of tech in 2025 (Kelly, Cowen, Wang, Prince)

Azeem Azhar

AI
Key Takeaways:
  1. The Macro Pivot: The transition from weightless software to energy-heavy hardware.
  2. The Tactical Edge: Stop building "wrappers" for model weaknesses.
  3. The Bottom Line: AI value is moving from the model to the grid and the individual reputation.
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December 26, 2025

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

a16z

AI
Key Takeaways:
  1. The Macro Shift: The Great Re-architecting. As legacy software moats evaporate and industrial supply chains reshore, value is migrating from passive data storage to active execution layers.
  2. The Tactical Edge: Target Archaic Verticals. Identify high-friction industries like mortgage servicing or IT support where the distance between intent and execution is currently measured in days.
  3. The Bottom Line: The next two years will reward those who build systems of action that replace human labor with autonomous agents and software-defined hardware.
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December 27, 2025

Why Scientists Can't Rebuild a Polaroid Camera [César Hidalgo]

Machine Learning Street Talk

AI
Key Takeaways:
  1. The Macro Trend: Economic complexity predicts growth better than current GDP. Capital will move toward "high-letter" economies like India and Indonesia.
  2. The Tactical Edge: Prioritize team retention over documentation. Since knowledge is embodied, losing a core team is equivalent to deleting the source code.
  3. The Bottom Line: Success in the next decade belongs to those who treat knowledge as a living network rather than a digital asset.
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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 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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Crypto Podcasts

February 6, 2026

Why Is Crypto Crashing? | Weekly Roundup

Empire

Crypto
Key Takeaways:
  1. Global liquidity expands, but new investment narratives (AI, commodities, tokens) grow faster. This "dilution of attention" pulls capital from speculative crypto, favoring utility or established brands.
  2. Focus on Bitcoin and revenue-generating crypto, or explore spread trades (long Bitcoin, short altcoins). Institutional interest builds in regulated products and yield strategies for Bitcoin.
  3. The market re-rates crypto assets on tangible value, not speculative hype. Expect pressure on altcoins without clear revenue, while Bitcoin and utility-driven projects attract smart money.
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February 6, 2026

Forecasting Crypto Market Regimes

0xResearch

Crypto
Key Takeaways:
  1. DeFi is building sophisticated interest rate derivatives that provide predictive signals for broader crypto asset prices. This signals a maturation of onchain financial markets, moving closer to TradFi's analytical depth.
  2. Monitor the USDe term spread on Pendle, especially at its extremes (steep backwardation or contango), to anticipate shifts in Bitcoin's 90-day return skew and underlying yield regimes.
  3. Understanding Pendle's USDe term structure provides a powerful, data-driven lens to forecast crypto market sentiment and interest rate movements, offering a strategic advantage for investors navigating the next 6-12 months as onchain finance grows more complex.
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February 6, 2026

Bittensor Novelty Search :: SN64 Chutes :: Serverless AI compute 🪂

The Opentensor Foundation | Bittensor TAO

Crypto
Key Takeaways:
  1. The Macro Shift: AI compute is commodifying, shifting from centralized, overcapitalized data centers to globally distributed, incentive-aligned networks. This decentralization drives down costs, increases resilience, and enables unprecedented privacy.
  2. The Tactical Edge: Builders should explore Chutes' TE-enabled agent hosting and "Sign in with Chutes" OAuth system for private, cost-effective AI applications. Investors should recognize the long-term value of protocols aligning incentives for distributed compute.
  3. The Bottom Line: Chutes is building the foundational, trustless intelligence layer for the decentralized web. Its focus on privacy, efficiency, and community-driven agent development positions it as a critical piece of the Bittensor ecosystem and a potential disruptor to traditional AI giants.
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February 6, 2026

Why Everything Broke at Once (Crypto, Tech, Gold) & What Happens Next...

Bankless

Crypto
Key Takeaways:
  1. The Macro Shift: Global markets are resetting crowded growth trades, with AI's disruptive force and shifting monetary policy impacting everything from tech stocks to crypto. This period is exposing underlying correlations and forcing a re-evaluation of long-held strategies.
  2. The Tactical Edge: Maintain psychological discipline and consider dollar-cost averaging into assets with strong fundamentals. Pay close attention to Ethereum's evolving technical roadmap, as specialized L2s and L1 scaling become central.
  3. The Bottom Line: This market downturn, while painful, is a crucible for conviction. For resilient investors and builders, it presents a rare opportunity to accumulate assets and build infrastructure that will define the next cycle.
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February 6, 2026

Vitalik Keeps Selling, Zhu Su maps the next cycle, Relay Raises $17M, Figure crosses $22B in HELOCs

The Rollup

Crypto
Key Takeaways:
  1. The "crypto casino" is giving way to "neo finance," where AI and traditional finance converge on blockchain rails. This means a fundamental re-evaluation of what constitutes "value" in crypto, moving from speculative tokens to real-world asset tokenization and critical infrastructure.
  2. Focus on infrastructure plays and real-world asset (RWA) tokenization platforms. Investigate projects that streamline institutional workflows or enable high-yield stablecoin products for retail, as these areas show sustainable growth independent of speculative market cycles.
  3. The next 6-12 months will see a continued bifurcation: the old speculative crypto market will consolidate, while the "neo finance" sector, powered by stablecoins, tokenized assets, and seamless cross-chain tech, will solidify its foundations. Position yourself to build or invest in solutions that bridge traditional finance with blockchain utility, rather than chasing ephemeral token pumps.
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February 6, 2026

The AI Privacy Problem No One's Talking About in AI with George Zeng

The Rollup

Crypto
Key Takeaways:
  1. The rise of powerful AI agents (like OpenClaw) creates an urgent need for secure, private compute. This isn't just about data protection; it's about enabling a truly decentralized, user-owned AI future, mirroring the internet's evolution from walled gardens to an open web. Centralized LLMs, even without ads, still collect and use sensitive user data, making confidential compute (TEEs) and local-first models essential for trust and control.
  2. Implement AI agents within confidential virtual machines (TEEs) and establish separate, quarantined accounts for them. This protects your core digital identity and assets from potential leaks or prompt injection attacks, allowing you to experiment with agent capabilities without exposing critical data. Consider open-source models for 90% cost savings and improved privacy.
  3. The next 6-12 months will see AI agents move from novelty to necessity. Builders and investors must prioritize privacy-preserving infrastructure and user-owned AI paradigms to capture this value securely. Ignoring these foundational security layers risks catastrophic data breaches and undermines the trust required for widespread agent adoption, making decentralized, confidential solutions a competitive differentiator.
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