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AI Podcasts

January 8, 2026

AI, markets, and power: A conversation with Paul Krugman

Azeem Azhar

AI
Key Takeaways:
  1. Capital is replacing labor as the primary driver of productivity.
  2. Prioritize investments in incumbents with massive distribution or lean startups that swap payroll for compute.
  3. The US remains the primary engine of growth but the internal divide between tech hubs and the hinterland will widen as AI concentrates wealth.
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January 9, 2026

Artificial Analysis: The Independent LLM Analysis House — with George Cameron and Micah Hill-Smith

Latent Space

AI
Key Takeaways:
  1. The decoupling of parameter count from active compute via sparsity means intelligence is becoming a software optimization problem as much as a hardware one.
  2. Audit your agentic workflows for turn efficiency rather than just cost per token.
  3. In a world of infinite tokens, the winner is the one who can verify the truth the fastest.
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January 7, 2026

Marc Andreessen's 2026 Outlook: AI Timelines, US vs. China, and The Price of AI

a16z

AI
Key Takeaways:
  1. The transition from "adding machines" to "human cognition" models is an 80-year correction finally hitting the vertical part of the S-curve.
  2. Prioritize application-specific models that backward-integrate into the stack.
  3. AI is a physical and digital build-out that will define the next decade of global power.
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January 6, 2026

Who Controls AI's Future? The Battle for GPU Access | CoreWeave SVP

Weights & Biases

AI
Key Takeaways:
  1. The transition from general-purpose compute to specialized AI infrastructure mirrors the rise of Snowflake in the data era.
  2. Audit your current cloud spend to identify where generalist latency is throttling your GPU goodput.
  3. Performance bars move every two years. If your infrastructure isn't purpose-built for AI today, you will be priced out of the market tomorrow.
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January 5, 2026

Welcome to AIE CODE - Jed Borovik, Google DeepMind

AI Engineer

AI
Key Takeaways:
  1. The Macro Pivot: The transition from LLMs as chat interfaces to LLMs as logic engines. As models move from text prediction to logic execution, the value moves from the model itself to the verification systems surrounding it.
  2. The Tactical Edge: Audit the stack. Prioritize the integration of agentic coding tools like Jules to shorten the feedback loop between ideation and deployment.
  3. The Bottom Line: Code is the only medium where AI can self-correct and scale without human intervention. The next 12 months will be defined by who can turn raw model power into reliable, self-healing code.
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January 5, 2026

Claude Agent SDK [Full Workshop] — Thariq Shihipar, Anthropic

AI Engineer

AI
Key Takeaways:
  1. Moving from "Model-as-a-Service" to "Environment-as-a-Service" where the harness matters as much as the weights.
  2. Replace your bespoke API tools with a single bash tool. Use a well-structured file system.
  3. The next year belongs to builders who stop treating LLMs as chatbots. They will treat them as system administrators.
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January 6, 2026

Building durable Agents with Workflow DevKit & AI SDK - Peter Wielander, Vercel

AI Engineer

AI
Key Takeaways:
  1. The Macro Transition: We are moving from "fire-and-forget" prompts to durable execution environments where state is as important as the model itself.
  2. The Tactical Edge: Wrap your existing tool calls in the `useStep` function to gain instant retry logic and execution history.
  3. The Bottom Line: Reliability is the primary moat in the agent market. Builders who adopt durable workflows will move to production while others are still debugging local scripts.
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January 6, 2026

Build a Prompt Learning Loop - SallyAnn DeLucia & Fuad Ali, Arize

AI Engineer

AI
Key Takeaways:
  1. The move from manual prompt engineering to automated prompt learning. As models become commodities, the proprietary loop that refines them becomes the moat.
  2. Implement a Train-Test Split for your prompts. Use a subset of failure data to generate new rules and validate them against a separate holdout set to ensure the logic holds.
  3. Reliability is the only metric that matters for agent adoption. If you are not using a feedback loop to update your system instructions, you are building on sand.
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January 6, 2026

The Netflix Culture Code That Changed Entertainment Forever | Reed Hastings Interview

Invest Like The Best

AI
Key Takeaways:
  1. The move from industrial management to creative inspiration. As AI automates routine tasks, the only remaining value is high-variance human creativity.
  2. Apply the Keeper Test today. Ask your leads which team members they would fight for and provide generous exits for the rest to reset your talent bar.
  3. Scaling doesn't require more rules. It requires better people. If you can maintain talent density, you can run fast while your competitors choke on their own handbooks.
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Crypto Podcasts

February 12, 2026

Santiago Santos: My New Crypto Investing Playbook

The Rollup

Crypto
Key Takeaways:
  1. The investment focus must shift from foundational layers to the services built on top.
  2. Prioritize investments in public equities of companies that actively use crypto infrastructure or in private equity of crypto-native applications with strong, centralized teams capable of rapid decision-making and direct value reinvestment into their token.
  3. The market is increasingly discerning between tokens that compound value and those that do not.
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February 12, 2026

Is Nic Carter Right? How Serious Is Bitcoin's Quantum Risk?

Unchained

Crypto
Key Takeaways:
  1. The quantum threat forces a re-evaluation of cryptographic foundations, pushing blockchains towards more robust, future-proof designs. This shift is not just about defense but about positioning for long-term institutional trust and capital.
  2. Prioritize chains actively researching and implementing post-quantum solutions, especially those with clear migration roadmaps and a willingness to adapt core protocols.
  3. The race to quantum-proof crypto is on. Chains that act decisively now will secure their future, attract significant capital, and potentially set new industry standards, while those that delay risk systemic failure.
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February 13, 2026

Coinbase Earnings, Bitcoin vs Tech, and Crypto’s Quantum Threat

Unchained

Crypto
Key Takeaways:
  1. AI's compute demand reshapes infrastructure, pulling Bitcoin miners into stable new business models while forcing crypto to confront an existential quantum threat.
  2. Prioritize chains and protocols investing in post-quantum cryptography, focusing on clear migration roadmaps and robust hash- or lattice-based solutions.
  3. The next 6-12 months will clarify miner AI contracts, Bitcoin's market correlation, and quantum upgrade urgency. Position your portfolio and research towards projects showing foresight and execution.
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February 12, 2026

This Is Crypto’s Biggest Bottleneck (and LI.FI Solves It)

The DCo Podcast

Crypto
Key Takeaways:
  1. The fragmentation of crypto liquidity across chains demands a unified, programmable interface for complex user strategies. LI.FI's VM and transaction rail are building this composable layer, abstracting away the underlying complexity.
  2. Investigate protocols building on LI.FI's infrastructure for streamlined multi-chain operations. For tokenized asset issuers, prioritize integration with platforms offering broad wallet distribution like LI.FI.
  3. The future of crypto involves seamless multi-chain interactions and widespread tokenized asset adoption. LI.FI's innovations position them as a core enabler, making sophisticated DeFi accessible and driving liquidity to new assets over the next 6-12 months.
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February 13, 2026

Dispersion Is Exploding While Main Street Reaccelerates | Weekly Roundup

Forward Guidance

Crypto
Key Takeaways:
  1. The era of easy, broad-market gains from passive investing is ending. Unprecedented AI capital expenditure is driving a wedge between tech and tangible assets, forcing a re-evaluation of traditional correlations and creating a bifurcated market where "real things" with fixed supply constraints are gaining favor over software-driven growth. This shift is also revealing a quiet reacceleration in Main Street economics, previously masked by top-tier spending.
  2. Adopt a long-short, beta-neutral approach to capitalize on extreme market dispersion. Identify and invest in "bottleneck" assets (e.g., metals, energy, manufacturing inputs) that are essential for AI infrastructure and have inelastic supply, while selectively shorting or avoiding overvalued software companies facing existential threats from AI.
  3. The market is undergoing a fundamental re-rating. Capital will increasingly flow from over-indexed, high-multiple digital assets to under-owned, supply-constrained physical assets. Ignoring this "flipping of the boat" means missing out on significant alpha and risking capital in sectors facing structural headwinds.
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February 12, 2026

What Does AI Mean For Your Future?

1000x Podcast

Crypto
Key Takeaways:
  1. AI is driving a rapid, unprecedented capital concentration into a select group of companies and hard assets, creating a bifurcated economic reality where skilled labor gains leverage while low-skill labor faces immediate displacement.
  2. Invest in the "picks and shovels" of the AI boom: the companies building data centers, providing energy, and offering specialized services to this infrastructure. For individuals, become an AI-fluent, indispensable contributor in your field.
  3. The next 3-4 years are a critical window. Position your finances and career now to capitalize on the AI-driven wealth transfer and avoid being left behind as economic value consolidates at an accelerating pace.
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