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AI Podcasts

December 11, 2025

Can you prove AI ROI in Software Eng? (Stanford 120k Devs Study) – Yegor Denisov-Blanch, Stanford

AI Engineer

AI
Key Takeaways:
  1. Strategic Shift: AI ROI isn't about adoption, it's about intelligent adoption. The gap between top and bottom performers will widen based on measurement sophistication and codebase health.
  2. Builder/Investor Note: For builders, prioritize codebase hygiene and engineer training before or concurrently with AI rollout. For investors, scrutinize AI productivity claims; ask about code quality, rework rates, and specific measurement frameworks beyond simple usage.
  3. The "So What?": In the next 6-12 months, companies that master AI integration by focusing on quality, measurement, and environment will compound their gains, while those chasing superficial metrics risk significant tech debt and negative ROI.
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December 11, 2025

The State of AI Code Quality: Hype vs Reality — Itamar Friedman, Qodo

AI Engineer

AI
Key Takeaways:
  1. Strategic Implication: The next frontier of AI in software isn't just *generating* code, but *governing* its quality. This shift will redefine competitive advantage.
  2. Builder/Investor Note: Prioritize investments in AI-powered quality gates, intelligent code review, and dynamic testing. For builders, feed your AI tools rich, comprehensive context. For investors, look for companies building these "picks and shovels."
  3. The "So What?": The promised 2x-10x productivity gains are real, but they won't come from raw code generation alone. The next 6-12 months will see a scramble to implement agentic, context-aware quality workflows to unlock AI's true potential across the SDLC.
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December 12, 2025

Hard Won Lessons from Building Effective AI Coding Agents – Nik Pash, Cline

AI Engineer

AI
Key Takeaways:
  1. Strategic Shift: The competitive edge in AI agents is moving from clever architecture to superior model training data and robust RL environments.
  2. Builder/Investor Note: Prioritize raw model capability over complex agent stacks. Builders should contribute to open-source RL environments; investors should seek companies focused on generating and leveraging high-quality training data.
  3. The "So What?": The next 6-12 months will see a race to build and utilize real-world, outcome-driven benchmarks. Open initiatives like Client Bench could democratize model improvement and accelerate AI development significantly.
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December 12, 2025

Moving away from Agile: What's Next – Martin Harrysson & Natasha Maniar, McKinsey & Company

AI Engineer

AI
Key Takeaways:
  1. Strategic Implication: The "Agile" era is ending. AI demands a new, more fluid, and context-aware operating model for software development.
  2. Builder/Investor Note: Look for (or build) companies that are fundamentally redesigning their SDLC, team structures, and roles around AI, not just bolting on tools. This includes robust, outcome-based measurement.
  3. The "So What?": The next 6-12 months will separate the AI-native leaders from the laggards. Those who embrace this human and organizational transformation will unlock exponential value; others will be stuck with marginal gains.
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December 13, 2025

Proactive Agents – Kath Korevec, Google Labs

AI Engineer

AI
Key Takeaways:
  1. Strategic Implication: The market is moving beyond basic "copilot" functionality. The next frontier is proactive, context-aware AI that reduces cognitive load and integrates seamlessly into existing workflows.
  2. Builder/Investor Note: Focus on building or investing in multi-agent architectures that converge context across the entire product lifecycle (code, design, data) and prioritize human-in-the-loop alignment over pure autonomy.
  3. The "So What?": The fundamental patterns of software development (Git, IDEs, even code itself) are ripe for disruption. Don't be afraid to question old ways; the future of how software is built is being invented right now.
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December 13, 2025

Minimax M2 – Olive Song, MiniMax

AI Engineer

AI
Key Takeaways:
  1. **The "Small is Mighty" Paradigm:** Don't underestimate smaller, specialized models. M2 proves that smart engineering, real-world feedback, and iterative reasoning can outperform larger models in specific, high-value domains.
  2. **Builders, Embrace Iteration:** Design your agents with "interleaved thinking." The ability to self-correct and adapt to noisy environments is critical for real-world utility.
  3. **The "So What?":** The next wave of AI agents will be defined by their robustness, cost-effectiveness, and ability to generalize across dynamic environments. M2 is a blueprint for building practical, scalable AI that developers will actually integrate into their daily workflows.
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December 11, 2025

No Priors Ep. 143 | With ElevenLabs Co-Founder Mati Staniszewski

No Priors: AI, Machine Learning, Tech, & Startups

AI
Key Takeaways:
  1. Strategic Shift: The future of human-computer interaction is voice-first, moving from static content to dynamic, personalized, and agentic experiences.
  2. Builder/Investor Note: Defensibility in AI is increasingly found in deep product layers, specialized architectural breakthroughs (especially in audio), and robust ecosystems, not just raw model scale.
  3. The "So What?": Over the next 6-12 months, expect to see significant advancements in proactive AI agents, immersive media, and personalized education, with voice as the core interface.
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December 10, 2025

The Unicorn Founder Who Delegated Everything.

a16z

AI
Key Takeaways:
  1. The AI-Delegation Revolution is Here: Start experimenting with AI tools like ChatGPT for delegation now. The future involves proactive machine assistants deeply integrated into your workflow.
  2. Builders & Investors: Focus on "How to Delegate": The biggest constraint isn't finding assistants, but teaching clients how to delegate effectively. Tools and services that educate delegators will win.
  3. Reclaim Your Ambition: By offloading the mundane, you free up mental bandwidth to think bigger, pursue more ambitious goals, and ultimately, control your most valuable asset: time.
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December 12, 2025

AI Eats the World: Benedict Evans on the Next Platform Shift

a16z

AI
Key Takeaways:
  1. Strategic Implication: The AI bubble is inevitable. Focus on defensible positions: deep product integration, proprietary data, and distribution, rather than just raw model performance.
  2. Builder/Investor Note: The opportunity lies in productizing AI for specific "jobs to be done" within niche industries, creating intuitive UIs, and building in validation, not just building another foundational model.
  3. The "So What?": We're about to figure out the true "job to be done" for many industries. AI will unbundle existing businesses by exposing their hidden inefficiencies or non-obvious defensibilities.
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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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