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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 8, 2026

The Pro-Quantum Argument w/ Tyler Whittle

The Gwart Show

Crypto
Key Takeaways:
  1. The theoretical certainty of quantum computing, coupled with accelerating engineering breakthroughs, means the digital asset space must proactively build "crypto agility" into its core protocols. This ensures systems can adapt to new cryptographic standards as current ones become obsolete.
  2. Secure your Bitcoin by ensuring it resides in unspent SegWit or P2SH addresses, as these keep your public key hidden until spent. This provides a temporary shield against quantum attacks.
  3. Quantum computing is not a distant threat but a near-term risk with a 20% chance of moving Satoshi's coins by 2030. Ignoring this could lead to a systemic collapse of the "store of value" narrative for Bitcoin and other digital assets, forcing a costly and painful reset.
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February 8, 2026

If Bitcoin doesn't quantum-proof it will be EXPENSIVE

The Gwart Show

Crypto
Key Takeaways:
  1. The crypto industry must shift from viewing quantum as a distant threat to an imminent engineering challenge requiring proactive, coordinated defense.
  2. Ensure any long-term Bitcoin holdings are in SegWit addresses never spent from, as these public keys remain hashed and are currently more resistant to quantum attacks.
  3. A 20% chance of Satoshi's coins moving by 2030, and near certainty by 2035, means delaying upgrades is a multi-billion dollar bet against Bitcoin's core security narrative.
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February 7, 2026

Do We Still Need L2s Now That Ethereum Has Scaled? - Uneasy Money

Unchained

Crypto
Key Takeaways:
  1. Ethereum's L1 scaling redefines L2s from pure throughput solutions to specialized platforms, while AI agents introduce a new, autonomous layer of on-chain activity.
  2. Investigate L2s that offer unique features or cater to specific enterprise needs beyond just low fees.
  3. The future of crypto involves a more performant Ethereum L1, specialized L2s, and a burgeoning agentic economy.
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February 8, 2026

Want to Hire an AI Agent? Check Their Reputation Via ERC-8004

Unchained

Crypto
Key Takeaways:
  1. The rapid rise of autonomous AI agents demands a decentralized trust layer. Blockchains, initially an "internet of money," are now becoming the foundational "internet of trusted agent commerce," providing verifiable identity and reputation essential for multi-agent economies. This shift moves beyond simple payments to establishing a credible, censorship-resistant framework for AI-driven interactions.
  2. Integrate ERC-8004 into agent development. Builders should register their AI agents on ERC-8004 to establish verifiable on-chain identity and reputation, attracting trusted interactions and avoiding future centralized platform fees or censorship.
  3. The future of AI commerce hinges on decentralized trust. ERC-8004 is the foundational primitive for this, ensuring that as AI agents become more sophisticated and transact more value, the underlying infrastructure remains open, fair, and resistant to single points of control. This is a critical piece of the puzzle for anyone building or investing in the agent economy over the next 6-12 months.
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February 8, 2026

Hash Rate - Ep.157 - Mining Bittensor with OpenClaw

Hash Rate Podcast

Crypto
Key Takeaways:
  1. Agentic AI is not just a tool; it's a new layer of abstraction for decentralized networks. It shifts the barrier to entry from deep technical and crypto-specific knowledge to strategic prompting and resource allocation, accelerating network participation and value accrual.
  2. Experiment now. Deploy a hosted agentic AI like OpenClaw (via seafloor.bot) with a small budget to understand its capabilities in a controlled environment. Focus on automating complex setup tasks within decentralized AI protocols like Bittensor to gain firsthand experience before others.
  3. The rise of agentic AI agents will fundamentally reshape how individuals and organizations interact with and profit from decentralized AI. Those who master agent orchestration and "skill" development will capture disproportionate value as these systems become the primary interface for programmable intelligence and capital.
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February 7, 2026

Crypto’s Reality Check | Roundup

Bell Curve

Crypto
Key Takeaways:
  1. AI's gravitational pull on talent and capital is forcing crypto to mature beyond speculative tokenomics, transitioning focus from "meme value" to demonstrable product-market fit and real-world utility.
  2. Identify and invest in projects building at the intersection of crypto and AI, or those creating "net new" applications that abstract away crypto complexity for mainstream users, especially in areas like identity or fintech.
  3. This bear market is a necessary, albeit painful, reset. It's a time for builders to focus on creating tangible value and for investors to seek out projects with genuine utility, as the era of easy speculative gains is over.
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