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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 17, 2026

FTX Changed Finance — Now Institutions Want What Crypto Built

The DCo Podcast

Crypto
Key Takeaways:
  1. Investigate platforms offering regulated perpetual futures on traditional assets. These venues are positioned to capture significant institutional flow by combining crypto's product innovation with TradFi's risk management.
  2. The global financial system is bifurcating, with a clear trend towards regulated, institutional-grade venues for all tradable assets, including novel ones like compute power.
  3. The future of finance involves crypto-native products like perpetuals, but their mass adoption by institutions hinges on robust regulation and superior risk management.
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February 17, 2026

AI Capex Meets SaaS Apocalypse, 18-Month Bear Market & Bitcoin vs Quantum

1000x Podcast

Crypto
Key Takeaways:
  1. The Macro Shift: AI's productivity gains are consolidating power and profits within vertically integrated tech giants, fundamentally altering the competitive landscape for software and infrastructure providers.
  2. The Tactical Edge: Re-evaluate SaaS investments, favoring mega-cap tech companies poised to absorb former SaaS revenues through internal AI-driven development. For crypto, identify and accumulate projects with genuine revenue generation during the bear market.
  3. The Bottom Line: Position your portfolio for a world where AI drives corporate insourcing, crypto valuations reset to fundamentals, and core digital assets like Bitcoin undergo necessary technical upgrades to survive future threats.
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February 17, 2026

VVV, CFTC and Morpho | Livestream

0xResearch

Crypto
Key Takeaways:
  1. Traditional finance is integrating with crypto, but often on its own terms, demanding more transparency from protocols while VCs continue to deploy significant capital into specific, high-potential crypto and AI intersections.
  2. Scrutinize institutional "partnerships" for concrete terms and evaluate protocols based on their true moat against easy forks or platform risk.
  3. The market is bifurcating: clear regulatory wins for specific crypto applications (like prediction markets) and innovative AI/crypto plays are attracting capital, while opaque TradFi deals and general L1 infrastructure face increased scrutiny. Position for clarity and genuine value accrual.
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February 17, 2026

RWA Looping, Crypto Market Structure Bill, & Vaults - Sean Kelley

The Rollup

Crypto
Key Takeaways:
  1. The digitization of finance is accelerating, with institutional capital now actively seeking onchain yield and efficiency. This is creating a competitive pressure cooker for traditional banks, while opening vast opportunities for nimble DeFi protocols.
  2. Focus on protocols building robust RWA infrastructure and those providing deep liquidity for tokenized treasuries. These are the picks and shovels for the coming institutional capital wave.
  3. The fight for stablecoin yield and institutional adoption will define the next 6-12 months. Position yourself to capitalize on the inevitable flow of capital from TradFi to transparent, yield-bearing onchain assets, even if it's just a fraction of the total.
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February 17, 2026

Neo Finance 'N7' Outperforming, Apollo x Morpho, Frax Joins The Show, Bullet Mainnet & Gmoney Calls

The Rollup

Crypto
Key Takeaways:
  1. Explore DeFi protocols in the N7 index (Morpho, Frax, Aave, etc.) for early exposure to institutional capital flows and RWA looping opportunities.
  2. Experiment with AI agents to automate content creation, research, and even software development, drastically cutting operational costs.
  3. The financial system is bifurcating into a "Neo Finance" layer where tokenized real-world assets are integrated with DeFi primitives, and an "AI-augmented" layer where autonomous agents supercharge individual and small team productivity.
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February 16, 2026

Doug Sillard: Taostats, Bittensor Dynamic TAO, Chain Buys, MEV Bots & TaoFlow Explained | Ep. 82

Ventura Labs

Crypto
Key Takeaways:
  1. Bittensor is transitioning from a purely experimental decentralized AI network to a performance-driven marketplace, demanding real-world utility and robust economic models from its subnets.
  2. Builders launching subnets must secure initial TAO liquidity and a clear, executable product roadmap from day one to navigate the competitive landscape and achieve emission.
  3. The network's continuous adaptation, from chain buys to MEV mitigation, signals a commitment to long-term stability and value.
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