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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

August 20, 2025

The Fed Isn’t in Charge of the Dollar. The Eurodollar System Is.

Bankless

Crypto
Key Takeaways:
  1. **The Dollar Isn't Being Debased; It's Deflationary.** The market is not pricing in inflation or debasement. Instead, key indicators like the interest rate swap market are emphatically signaling a future of much lower interest rates for much longer, which is characteristic of deflationary pressure and a strong dollar.
  2. **Asset Booms Are a Symptom, Not a Solution.** Rising stock and crypto prices are not evidence of a healthy economy or money printing. They reflect a K-shaped recovery where capital flees into financial assets as a hedge against systemic fragility, while the real economy for labor remains stagnant.
  3. **The Contrarian Play Is Long Bonds.** If the global system is starved for safe, liquid collateral and headed toward a deflationary recession, the best-performing assets will be long-duration U.S. Treasuries. Snyder’s advice is the polar opposite of the typical crypto portfolio: be long bonds.
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August 20, 2025

Crypto Credit Markets Will Rewrite Risk Management | David Grider

Forward Guidance

Crypto
Key Takeaways:
  1. **Alpha Is Now Risk Management:** In a maturing crypto market, outperformance comes from actively managing gross exposure and utilizing a diverse strategy mix (equities, credit, derivatives), not just holding beta.
  2. **Crypto Credit Offers Unprecedented Asymmetry:** Instruments like convertible bonds on DATs provide credit-like downside protection while retaining crypto-like upside, creating a compelling opportunity for risk-adjusted returns that is often cheaper than replicating with native options.
  3. **The DAT Playbook Is Evolving:** The next cycle’s drama won't just be about token prices. Watch for DATs using leverage, building out their own "yield curves," and the eventual distressed cycle where activists and acquirers step in to capture NAV discounts.
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August 18, 2025

One More Push Higher Before the Crash?

1000x Podcast

Crypto
Key Takeaways:
  1. The ETH Rally is an Illusion. Price action is dictated by treasury company flows, not fundamentals. Monitor their stock premium/discount to NAV as a leading indicator for the market top.
  2. Prepare for a "Stupid" Finale. The market is primed for one last FOMO-driven blow-off top. This is the signal to sell into strength, not add risk.
  3. Set Up the Next Home Run. The inevitable crash of treasury company stocks will present a massive opportunity. Prepare to buy these assets at deep discounts (30%+) to NAV when the market panics.
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August 18, 2025

What Liquid Funds Are Buying

Empire

Crypto
Key Takeaways:
  1. Concentrated Bets on Fundamentals Win. The era of "spray and pray" is over. The new meta is building highly concentrated portfolios (10-15 tokens) based on deep fundamental analysis of protocols with clear revenue models and product-market fit.
  2. Digital Asset Treasuries Are TradFi's On-Ramp. DATs are more than a short-term trade; they are the primary bridge for institutional capital to gain crypto exposure. Their marketing power is proving to be as crucial as their financial engineering.
  3. The 24/7 Market Is Coming. The tokenization of equities isn't a matter of *if* but *when*. This shift will create a fiduciary obligation for funds to move to on-chain assets, forcing a rapid, systemic evolution of financial markets.
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August 16, 2025

Why DATs Beyond BTC And ETH Are Risky

Empire

Crypto
Key Takeaways:
  1. **Concentrate on the Winners:** Bitcoin is the established store-of-value asset, and Ethereum is the dominant settlement layer for high-value digital assets. The data shows they have already won their respective categories.
  2. **The Rest is a Long Tail of Risk:** Investing outside of Bitcoin and Ethereum is a bet against powerful, gravity-like market forces. These alternatives are competing for a sliver of the market, increasing their risk of becoming obsolete.
  3. **Power Law is the Rule:** The market isn't about finding the "next" Ethereum; it's about recognizing that power laws are creating a duopoly where the vast majority of value will continue to accrue to the top two assets.
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August 16, 2025

Can ETH Keep Pumping Or Is It All Over?!

Steady Lads Podcast

Crypto
Key Takeaways:
  1. The New Game is Financial Engineering. The market's primary driver is the "Digital Asset Treasury" meta. Bitcoin leverages its "pristine collateral" narrative for debt financing, while Ethereum leverages native yield to justify its premium.
  2. Don't Expect a 2021 Redux. The institutional capital fueling this rally is not here to bid on your favorite altcoin. Their focus is on BTC, ETH, and treasury-related arbitrage, making a widespread, retail-driven altcoin season unlikely.
  3. De-Risk and Secure Profits. After a 3x run, seasoned traders are taking profits on ETH. The consensus is to refuse to round-trip your gains, pay down on-chain debt, and shift to scalping volatility rather than betting on a continued parabolic advance.
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