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AI Podcasts

December 31, 2025

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

Latent Space

AI
Key Takeaways:
  1. The transition from Model-Centric to Context-Centric AI. As base models commoditize, the value moves to the proprietary data retrieval and prompt optimization layers.
  2. Implement an instruction-following re-ranker. Use small models to filter retrieval results before they hit the main context window to maintain high precision.
  3. Context is the new moat. Your ability to coordinate sub-agents and manage context rot will determine your product's reliability over the next year.
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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 convergence of RL and self-supervised learning. As the boundary between "learning to see" and "learning to act" blurs, the winning agents will be those that treat the world as a giant classification problem.
  2. Prioritize depth over width. When building action-oriented models, increase layer count while maintaining residual paths to maximize intelligence per parameter.
  3. The "Scaling Laws" have arrived for RL. Expect a new class of robotics and agents that learn from raw interaction data rather than human-crafted reward functions.
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December 31, 2025

[State of AI Papers 2025] Fixing Research with Social Signals, OCR & Implementation — Team AlphaXiv

Latent Space

AI
Key Takeaways:
  1. The Age of Scaling is hitting a wall, leading to a migration toward reasoning and recursive models like TRM that win on efficiency.
  2. Filter your research feed by implementation ease rather than just citation count to accelerate your development cycle.
  3. In a world of AI-generated paper slop, the ability to quickly spin up a sandbox and verify code is the only sustainable competitive advantage for AI labs.
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December 31, 2025

[State of MechInterp] SAEs in Production, Circuit Tracing, AI4Science, "Pragmatic" Interp — Goodfire

Latent Space

AI
Key Takeaways:
  1. The transition from Black Box to Glass Box AI. Trust is the next moat, and interpretability is the tool to build it.
  2. Use feature probing for high-stakes monitoring. It is more effective and cheaper than using LLMs as judges for tasks like PII scrubbing.
  3. Understanding model internals is no longer just a safety research project. It is a production requirement for any builder deploying AI in regulated or high-stakes environments over the next 12 months.
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December 31, 2025

[State of Code Evals] After SWE-bench, Code Clash & SOTA Coding Benchmarks recap — John Yang

Latent Space

AI
Key Takeaways:
  1. The transition from completion to agency means benchmarks are moving from static snapshots to active environments.
  2. Integrate unsolvable test cases into internal evaluations to measure model honesty.
  3. Success in AI coding depends on navigating the messy, interactive reality of production codebases rather than chasing high scores on memorized puzzles.
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December 31, 2025

[State of Research Funding] Beyond NSF, Slingshots, Open Frontiers — Andy Konwinski, Laude Institute

Latent Space

AI
Key Takeaways:
  1. The center of gravity in AI is moving from closed-door pre-training to open-source compound systems that prioritize context management.
  2. Identify research teams with long histories of collaboration and fund them before they incorporate to capture the highest upside.
  3. Open research is the only way to maintain a democratic and competitive AI ecosystem against both closed labs and international rivals.
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December 29, 2025

Beyond the Code: The Books That Shaped the Minds of AI Leaders

Turing Post

AI
Key Takeaways:
  1. The transition from technology push to market pull requires builders to stop focusing on the stack and start obsessing over user psychology.
  2. Apply the Mom Test by asking users about their current workflows instead of pitching your solution. This prevents building expensive features that nobody uses.
  3. The next decade of AI will be won by those who understand the human condition as deeply as they understand the transformer architecture.
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December 29, 2025

Memory in LLMs: Weights and Activations - Jack Morris, Cornell

AI Engineer

AI
Key Takeaways:
  1. The Macro Trend: Moving from "In-Context Learning" to "Weight-Based Memory" to bypass the quadratic costs of attention.
  2. The Tactical Edge: Use synthetic data generation to augment your fine tuning sets and prevent the model from forgetting its base knowledge.
  3. RAG is a stopgap. The long term winners will be those who build "neural file systems" where the model inherently knows the data.
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December 29, 2025

Where does consumer AI stand at the end of 2025?

a16z

AI
Key Takeaways:
  1. The "Everything App" is a myth. We are moving from general chat boxes to agentic workspaces that operate across your entire software stack.
  2. Build opinionated. Use the current model quality to solve one specific, high-value workflow rather than competing for the general assistant crown.
  3. 2026 is the year of the builder. The infrastructure is ready, the compute tension is real for Labs, and the market is hungry for products with a soul.
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Crypto Podcasts

November 7, 2025

Bull Market or Fakeout Top? Haseeb’s Crypto Cycle Take

Bankless

Crypto
Key Takeaways:
  1. AI Is The Only Game In Town: The crypto market is currently a passenger in a macro environment dictated by AI. Until that capital rotation shifts, crypto will likely remain highly correlated and susceptible to sell-offs when equities show weakness.
  2. Bitcoin’s Handover Is Bullish: Don't mistake consolidation for a bear market. Bitcoin is undergoing a healthy ownership transfer from early believers to new institutions, building a stronger, deeper foundation for its next leg up.
  3. Decentralization Is About Coercion, Not Paralysis: The ability of a chain’s validators to collectively intervene in a catastrophic hack is a feature, not a bug. True decentralization is measured by a network's ability to resist external pressure, not its inability to make collective decisions.
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November 6, 2025

Massive Selloff, Mamdani Wins, & Jonah Ditches His CryptoPunk

1000x Podcast

Crypto
Key Takeaways:
  1. System Over Gut. Max’s systematic models correctly identified the top and signaled a buy on the recent dip. In volatile markets, outsourcing conviction to an algorithm removes emotion and highlights clear entry/exit points.
  2. Turn Losses Into Liquidity. Jonah’s CryptoPunk sale demonstrates a crucial strategy: use tax-loss harvesting to turn underwater positions into immediate, deployable capital. A paper loss can become a real financial gain.
  3. Watch Politics, Not Just Charts. The biggest long-term threat to your portfolio isn’t a broken chart pattern; it’s a political paradigm shift. The rise of redistributionism is a slow-burn risk that could eventually dwarf any market cycle.
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November 6, 2025

How Ethereum Will Integrate Into TradFi Infrastructure with Vivek Raman

The Rollup

Crypto
Key Takeaways:
  1. ETH's Value is Foundational, Not Fickle. The core investment thesis is ETH as the digital economy's pristine collateral and store of value. Network revenue is just the icing on the cake.
  2. The Real Work is Boring (and Bullish). The next phase of growth depends on integrating Ethereum into the mundane back-office operations of TradFi. This is the key to irreversible adoption.
  3. Privacy is the Next Frontier. Compliant, ZK-powered privacy is the final gateway required to bring massive institutional capital on-chain.
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November 5, 2025

Massive Selloff, Mamdani Wins, & Jonah Ditches His CryptoPunk

1000x Podcast

Crypto
Key Takeaways:
  1. OGs are cashing out. Heavy selling pressure above $120k comes from early Bitcoin whales transferring wealth to "fair-weather" DAT holders, creating a fragile market structure.
  2. Politics now dictate portfolio risk. Zohran Mamdani’s rise signals a shift to redistributionist politics. If this trend goes national, it’s a clear signal to liquidate assets, as redistribution historically crushes asset prices.
  3. Invest in clean assets with real yield. In a market saturated with VC-owned tokens, assets like Hyperliquid (HYPE) stand out due to their airdrop-only distribution and fee-driven buy-and-burn mechanism, creating a direct link between platform usage and token value.
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November 5, 2025

Quadrillions: Unlocking Quadrillions | Don Wilson & Yuval Rooz

Empire

Crypto
Key Takeaways:
  1. **Privacy Isn't a Feature; It's the Foundation.** For institutions, confidentiality is non-negotiable. Any network aiming to attract serious capital must offer privacy that allows for compliance without broadcasting every move to the world.
  2. **Real Adoption Is a Long Game.** Chasing bull market hype is a losing strategy for enterprise adoption. Canton’s success with partners like Goldman Sachs, DTCC, and Citadel demonstrates the power of prioritizing utility and compliance over a premature token launch.
  3. **The Next Wave Is Tokenizing Everything.** The goal is to move beyond crypto-native assets. The real prize is upgrading the rails for the world's existing financial system—equities, bonds, and treasuries—by making them digitally native, 24/7, and instantly settleable.
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November 5, 2025

The Next Chapter For Blockworks | Empire

Forward Guidance

Crypto
Key Takeaways:
  1. Focus or Fade. As the industry matures, companies must shed non-core business units to become world-class at one thing. For Blockworks, that's data, not news.
  2. Buy the Theme. Public market investors will pay a massive premium for the only stock representing a major crypto trend (e.g., Securitize for tokenization), often making it a better trade than trying to pick winners among underlying assets.
  3. Growth is Subsidized. Major L1/L2 foundations are actively paying for enterprise adoption (e.g., Solana and Western Union). This is a standard business practice to kickstart network effects, but the long-term ROI remains unproven.
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