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AI Podcasts

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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December 26, 2025

How Claude Code Works - Jared Zoneraich, PromptLayer

AI Engineer

AI
Key Takeaways:
  1. The Macro Movement: The transition from AI as a feature to AI as a headless operator using terminal-based agents.
  2. The Tactical Edge: Replace complex classification DAGs with simple tool-calling loops to reduce technical debt.
  3. The Bottom Line: The future of software development is not better IDEs but better headless agents that treat the entire OS as a tool.
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December 26, 2025

Shipping AI That Works: An Evaluation Framework for PMs – Aman Khan, Arize

AI Engineer

AI
Key Takeaways:
  1. The transition from deterministic software to probabilistic agents requires a move from "vibe coding" to data-driven development.
  2. Build a "golden" data set of 50 hard examples. Use these to test every prompt change before pushing to production.
  3. Reliability is the only moat left in a world of commoditized models. Evals are the bridge to that reliability.
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December 27, 2025

AGI: The Path Forward – Jason Warner & Eiso Kant, Poolside

AI Engineer

AI
Key Takeaways:
  1. Software development is moving from a manual craft to an automated output of vertically integrated intelligence stacks.
  2. Monitor the public API release early next year to replace generic LLMs with specialized coding intelligence.
  3. The winners of the next decade will build on platforms that treat compute as a raw commodity and intelligence as the final product.
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Crypto Podcasts

February 6, 2026

Why Is Crypto Crashing? | Weekly Roundup

Empire

Crypto
Key Takeaways:
  1. Global liquidity expands, but new investment narratives (AI, commodities, tokens) grow faster. This "dilution of attention" pulls capital from speculative crypto, favoring utility or established brands.
  2. Focus on Bitcoin and revenue-generating crypto, or explore spread trades (long Bitcoin, short altcoins). Institutional interest builds in regulated products and yield strategies for Bitcoin.
  3. The market re-rates crypto assets on tangible value, not speculative hype. Expect pressure on altcoins without clear revenue, while Bitcoin and utility-driven projects attract smart money.
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February 6, 2026

Forecasting Crypto Market Regimes

0xResearch

Crypto
Key Takeaways:
  1. DeFi is building sophisticated interest rate derivatives that provide predictive signals for broader crypto asset prices. This signals a maturation of onchain financial markets, moving closer to TradFi's analytical depth.
  2. Monitor the USDe term spread on Pendle, especially at its extremes (steep backwardation or contango), to anticipate shifts in Bitcoin's 90-day return skew and underlying yield regimes.
  3. Understanding Pendle's USDe term structure provides a powerful, data-driven lens to forecast crypto market sentiment and interest rate movements, offering a strategic advantage for investors navigating the next 6-12 months as onchain finance grows more complex.
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February 6, 2026

Bittensor Novelty Search :: SN64 Chutes :: Serverless AI compute 🪂

The Opentensor Foundation | Bittensor TAO

Crypto
Key Takeaways:
  1. The Macro Shift: AI compute is commodifying, shifting from centralized, overcapitalized data centers to globally distributed, incentive-aligned networks. This decentralization drives down costs, increases resilience, and enables unprecedented privacy.
  2. The Tactical Edge: Builders should explore Chutes' TE-enabled agent hosting and "Sign in with Chutes" OAuth system for private, cost-effective AI applications. Investors should recognize the long-term value of protocols aligning incentives for distributed compute.
  3. The Bottom Line: Chutes is building the foundational, trustless intelligence layer for the decentralized web. Its focus on privacy, efficiency, and community-driven agent development positions it as a critical piece of the Bittensor ecosystem and a potential disruptor to traditional AI giants.
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February 6, 2026

Why Everything Broke at Once (Crypto, Tech, Gold) & What Happens Next...

Bankless

Crypto
Key Takeaways:
  1. The Macro Shift: Global markets are resetting crowded growth trades, with AI's disruptive force and shifting monetary policy impacting everything from tech stocks to crypto. This period is exposing underlying correlations and forcing a re-evaluation of long-held strategies.
  2. The Tactical Edge: Maintain psychological discipline and consider dollar-cost averaging into assets with strong fundamentals. Pay close attention to Ethereum's evolving technical roadmap, as specialized L2s and L1 scaling become central.
  3. The Bottom Line: This market downturn, while painful, is a crucible for conviction. For resilient investors and builders, it presents a rare opportunity to accumulate assets and build infrastructure that will define the next cycle.
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February 6, 2026

Vitalik Keeps Selling, Zhu Su maps the next cycle, Relay Raises $17M, Figure crosses $22B in HELOCs

The Rollup

Crypto
Key Takeaways:
  1. The "crypto casino" is giving way to "neo finance," where AI and traditional finance converge on blockchain rails. This means a fundamental re-evaluation of what constitutes "value" in crypto, moving from speculative tokens to real-world asset tokenization and critical infrastructure.
  2. Focus on infrastructure plays and real-world asset (RWA) tokenization platforms. Investigate projects that streamline institutional workflows or enable high-yield stablecoin products for retail, as these areas show sustainable growth independent of speculative market cycles.
  3. The next 6-12 months will see a continued bifurcation: the old speculative crypto market will consolidate, while the "neo finance" sector, powered by stablecoins, tokenized assets, and seamless cross-chain tech, will solidify its foundations. Position yourself to build or invest in solutions that bridge traditional finance with blockchain utility, rather than chasing ephemeral token pumps.
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February 6, 2026

The AI Privacy Problem No One's Talking About in AI with George Zeng

The Rollup

Crypto
Key Takeaways:
  1. The rise of powerful AI agents (like OpenClaw) creates an urgent need for secure, private compute. This isn't just about data protection; it's about enabling a truly decentralized, user-owned AI future, mirroring the internet's evolution from walled gardens to an open web. Centralized LLMs, even without ads, still collect and use sensitive user data, making confidential compute (TEEs) and local-first models essential for trust and control.
  2. Implement AI agents within confidential virtual machines (TEEs) and establish separate, quarantined accounts for them. This protects your core digital identity and assets from potential leaks or prompt injection attacks, allowing you to experiment with agent capabilities without exposing critical data. Consider open-source models for 90% cost savings and improved privacy.
  3. The next 6-12 months will see AI agents move from novelty to necessity. Builders and investors must prioritize privacy-preserving infrastructure and user-owned AI paradigms to capture this value securely. Ignoring these foundational security layers risks catastrophic data breaches and undermines the trust required for widespread agent adoption, making decentralized, confidential solutions a competitive differentiator.
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