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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

May 2, 2025

The US Treasury’s Stablecoin Report, TradFi’s Crypto Adoption, and Ethereum’s New Era | Roundup

Bell Curve

Crypto
Key Takeaways:
  1. Stablecoins Go Global: Prepare for a $2T market, fueled primarily by international demand, potentially reshaping banking competition.
  2. TradFi Bridge Built: Institutional adoption is accelerating (Schwab, BlackRock), creating a stark disconnect between strong fundamentals and current market sentiment—ripe for alpha hunters.
  3. Ethereum Adapts: ETH's deep liquidity anchors DeFi, but stablecoins and new L1s (like Thru) challenge its dominance, pushing ongoing evolution (Restaking, potential VM changes).
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May 1, 2025

Hivemind: Does Bitcoin Have More Fuel to Run?

Empire

Crypto
Key Takeaways:
  1. Bitcoin Pause Likely: Expect potential short-term consolidation for Bitcoin as positive news fuel runs low; macro risks remain, but new ATHs are anticipated later this year.
  2. Solana Strong Bet: SOL emerges as the preferred L1 alternative, driven by superior architecture, ecosystem growth, and significant treasury buying pressure on the horizon.
  3. Altcoins Demand Substance: Market rationalization favors projects with realistic valuations and fundamentals; high-beta focus shifts to SOL memes, select strong L1s/apps (SUI, Hype), or SOL ecosystem plays (restaking), competing with leveraged BTC exposure.
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May 1, 2025

Cambria: The Degen MMO With $1M+ Seasonal Prize Pools

Delphi Digital

Crypto
Key Takeaways:
  1. Real Stakes Drive Engagement: Integrating significant financial risk/reward ($1M+ prize pools) creates intense player engagement, emergent strategies, and social dynamics far exceeding traditional games.
  2. Off-Chain Flexibility is Crucial (For Now): While the dream is fully on-chain, managing multi-million dollar game economies necessitates off-chain components for exploit mitigation, balancing, and analysis, at least in the near term.
  3. Targeting Degens Works: Cambria proves there's a potent market at the intersection of crypto traders and hardcore MMO players who crave high-stakes, economically meaningful gameplay.
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April 30, 2025

Michael Saylor's Billion Dollar Bitcoin Trade

1000x Podcast

Crypto
Key Takeaways:
  1. **Saylor's Playbook Goes Viral:** The MSTR strategy of leveraging stock premiums to acquire Bitcoin is being actively replicated, potentially fragmenting demand but also increasing overall leveraged exposure.
  2. **Leverage Risk Amplified:** New MSTR-like vehicles often lack an underlying business, making them pure, high-risk leveraged bets on Bitcoin funded by debt, vulnerable to sharp price declines.
  3. **GBTC Déjà Vu:** The rise of these debt-fueled Bitcoin acquisition vehicles strongly echoes the dynamics of the ultimately disastrous GBTC premium trade, signaling caution is warranted as this trend accelerates.
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April 29, 2025

What's Driving Bitcoin Higher?

1000x Podcast

Crypto
Key Takeaways:
  1. **ETF Flows Are Legit:** The billions pouring into Bitcoin ETFs represent real, broad-based demand, not just arbitrage froth.
  2. **Beware the MSTR Clones:** The rise of leveraged Bitcoin-buying public companies is the biggest near-term systemic risk – watch those premiums.
  3. **RWAs Are Real AF:** Don't sleep on Real World Assets; platforms like Pendle and Maple show explosive growth and represent the next major crypto narrative.
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April 29, 2025

Should VCs Benchmark Against Bitcoin? | Jon Charbonneau

0xResearch

Crypto
Key Takeaways:
  1. Don't Benchmark VCs Against Bitcoin: It's comparing different asset classes with separate goals and risk profiles.
  2. Use Altcoin Baskets Instead: A weighted average of major altcoins (ETH, SOL, etc.) offers a more relevant performance yardstick for crypto VCs.
  3. Know Your Exposure: LPs seeking Bitcoin returns should buy Bitcoin directly; VC funds offer exposure to the venture-style growth potential of crypto beyond Bitcoin.
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