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AI Podcasts

January 5, 2026

Welcome to AIE CODE - Jed Borovik, Google DeepMind

AI Engineer

AI
Key Takeaways:
  1. The transition from general-purpose LLMs to specialized coding agents that operate on the entire codebase rather than isolated snippets.
  2. Audit your current stack for agentic readiness. Prioritize tools that integrate with Gemini 3 or similar high-reasoning models to automate repetitive pull requests.
  3. Code is the substrate of the digital world. If you control the means of AI code generation, you control the speed of innovation for every other industry.
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January 5, 2026

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

AI Engineer

AI
Key Takeaways:
  1. The industry is moving from "Chat-as-Interface" to "Computer-as-Interface" where models operate directly on file systems.
  2. Replace your complex list of fifty tools with a single Bash tool and a secure sandbox.
  3. The winners in the agent race will not build the best prompts. They will build the best infrastructure for models to execute code.
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December 31, 2025

Infinity, Paradoxes, Gödel Incompleteness & the Mathematical Multiverse | Lex Fridman Podcast #488

Lex Fridman

AI
Key Takeaways:
  1. The move from a singular "Universe" view to a "Multiverse" perspective mirrors the transition from centralized monoliths to fragmented, interoperable ecosystems.
  2. Build systems that fail gracefully when hitting Gödelian limits.
  3. Truth is a vast ocean while proof is a small boat. Your roadmap must account for the reality that your system will eventually encounter truths it cannot verify.
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December 31, 2025

AI in 2026: 3 Predictions For What’s To Come (a16z Big Ideas)

a16z

AI
Key Takeaways:
  1. The Macro Pivot: Outcome-Based Intelligence. We are moving from AI as a Service to Results as a Service where software value is tied to revenue generation rather than seat licenses.
  2. The Tactical Edge: Verticalize the Data. Build in sectors with non-public outcome data to create a compounding moat that resists commoditization by foundation models.
  3. The winners of 2026 will be those who use AI to solve core human needs for connection and discovery while building defensible, data-rich business models.
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December 31, 2025

AutoGrad Changed Everything (Not Transformers) [Dr. Jeff Beck]

Machine Learning Street Talk

AI
Key Takeaways:
  1. The Macro Transition: Moving from "Big Model" monoliths to "Lots of Little Models" where distributed Bayesian assets represent specific physical objects.
  2. The Tactical Edge: Prioritize "Object-Centered" architectures that track uncertainty. This allows robots to "phone a friend" when encountering novel data.
  3. The LLM era is hitting a wall of implicit representation. The next 12 months belong to those building explicit, causal world models grounded in physics rather than language.
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December 31, 2025

[State of Post-Training] From GPT-4.1 to 5.1: RLVR, Agent & Token Efficiency — Josh McGrath, OpenAI

Latent Space

AI
Key Takeaways:
  1. The move from "bigger is better" to "smarter is cheaper" as token efficiency becomes the primary metric for agentic success.
  2. Prioritize building on models that demonstrate high performance on "graph walk" evals to ensure your long-context applications actually work.
  3. Utilitarian and efficient models that prioritize task completion over cheery personality will dominate the developer market.
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December 31, 2025

[State of Evals] LMArena's $100M Vision — Anastasios Angelopoulos, LMArena

Latent Space

AI
Key Takeaways:
  1. The Macro Trend: The transition from static benchmarks to live human-in-the-loop evaluation. As models saturate fixed tests, the only remaining signal is subjective human preference at scale.
  2. The Tactical Edge: Monitor secret model drops on Arena to spot frontier capabilities before official releases. This provides a lead time advantage for builders choosing their tech stack.
  3. The Bottom Line: Arena is the new kingmaker. If you are building AI products, their expert-tier data is the most reliable map for navigating the frontier.
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December 31, 2025

[State of Context Engineering] Agentic RAG, Context Rot, MCP, Subagents — Nina Lopatina, Contextual

Latent Space

AI
Key Takeaways:
  1. The move from small models to medium models (15B to 70B) suggests that reasoning capability is outstripping the desire for low-latency edge deployment.
  2. Implement instruction-following re-rankers to prune your context window. This prevents the model from getting confused by irrelevant data.
  3. Stop building toys. The next year belongs to those who can build full agentic systems that handle billions of tokens without losing the plot.
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December 31, 2025

[NeurIPS Best Paper] 1000 Layer Networks for Self-Supervised RL — Kevin Wang et al, Princeton

Latent Space

AI
Key Takeaways:
  1. The wall between RL and self-supervised learning is crumbling, leading to a unified "representation-first" approach to AI.
  2. Swap your reward-heavy objectives for contrastive representation learning to access deeper, more stable architectures.
  3. If you aren't planning for RL models with 100x the current depth, you're building for the past.
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Crypto Podcasts

February 16, 2026

Does Bitcoin Win or Lose In The Great AI-Tech Shakeout?

Unchained

Crypto
Key Takeaways:
  1. Bitcoin, once digital gold, is now frontier tech, vulnerable to broader tech sell-offs.
  2. Reallocate capital towards crypto assets benefiting from regulatory clarity and innovation: stablecoins, tokenized assets, privacy, prediction markets, perpetual futures.
  3. Bitcoin's short-term narrative is challenged, but its long-term tech thesis holds.
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February 17, 2026

Soft Jobs, AI CapEx Surge, and Institutions Move Onchain: Bits + Bips

Unchained

Crypto
Key Takeaways:
  1. Real-time data platforms are supplanting traditional economic reporting, forcing investors to re-evaluate their information sources, while AI's capital expenditure is creating a bifurcation between infrastructure providers and speculative model companies.
  2. Prioritize investments in blockchain infrastructure and stablecoin-centric payment solutions that cater to the emerging agentic economy, and leverage real-time data for a competitive information advantage.
  3. The convergence of real-time data, AI agents, and blockchain rails will fundamentally alter market dynamics and value capture over the next 6-12 months, rewarding those who understand the shift from centralized, lagging systems to decentralized, optimized ones.
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February 17, 2026

Bitcoin Is Either Going To Zero Or A Million

1000x Podcast

Crypto
Key Takeaways:
  1. The Macro Shift: AI is fundamentally reshaping corporate IT spending, driving a strategic pivot from external SaaS subscriptions to internal development, which will consolidate profits within mega-cap tech and pressure traditional software vendors.
  2. The Tactical Edge: Identify and invest in vertically integrated tech giants that can leverage AI for internal cost savings and new product development, while selectively shorting asset-heavy, midstream, or non-essential SaaS providers during strength.
  3. The Bottom Line: The current market is a re-evaluation of fundamental value across tech and crypto. Focus on companies with strong internal demand for compute and real-world utility, and understand that crypto's speculative cycles, while volatile, are driven by a unique social dynamic that will persist.
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February 16, 2026

MegaETH in 2026 & Ethereum's L2 End Game | Brett DiNovi & Lei Yang

Empire

Crypto
Key Takeaways:
  1. High-performance L2s are carving out new market segments by prioritizing user experience and speed over strict L1 equivalence, challenging traditional value accrual models.
  2. Builders should target L2s offering ultra-low latency and predictable costs for consumer-facing DeFi and gaming, as these environments enable novel, sticky applications.
  3. The next wave of crypto adoption hinges on L2s that can deliver real-time, seamless experiences, shifting value capture from L1 monetary premium to execution premium and innovative tokenomics.
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February 16, 2026

Lyn Alden: How to Survive The Gradual Print Era — Fed Chair Warsh, Gold & Bitcoin

Bankless

Crypto
Key Takeaways:
  1. The global monetary order is transitioning from a unipolar, dollar-dominant system to a multipolar one, driven by sovereign debt and geopolitical competition. This change elevates neutral reserve assets and challenges traditional financial institutions.
  2. Diversify your portfolio across high-quality equities (with an international and value tilt), hard assets (gold, silver, platinum, Bitcoin), and real-world assets like energy infrastructure. Maintain 5-10% cash for opportunities.
  3. The "gradual print" and ongoing monetary reordering mean sustained debasement of fiat currencies. Positioning in hard assets and resilient, undervalued real-world businesses is crucial for preserving and growing wealth over the next 6-12 months.
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February 16, 2026

As the AI Trade Cools Off, Are Bitcoin Miners Still a Buy?

Unchained

Crypto
Key Takeaways:
  1. The relentless demand for AI compute is transforming Bitcoin miners from speculative, commodity-dependent entities into stable, infrastructure-as-a-service providers. This pivot leverages their core asset—cheap power—to capture predictable, high-margin revenue streams.
  2. Evaluate Bitcoin mining stocks based on their AI contract pipeline, execution capabilities, and access to consistent power, rather than solely on Bitcoin price correlation. Prioritize those with colocation leases to minimize GPU capex risk.
  3. The strategic shift to AI offers a compelling de-risking narrative for Bitcoin miners, potentially leading to higher valuations and more stable cash flows. However, investors must monitor execution risks and political headwinds around power access over the next 6-12 months.
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