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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 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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