Complex Systems with Patrick McKenzie (patio11)

• Think like a trader, with Ricki Heicklen

  Patrick McKenzie (patio11) is joined again by Ricki Heicklen to discuss the evolution of her trading education business, Arbor, one year after their first conversation. They dive deep into the pedagogy of trading, exploring how simulated markets teach concepts like adverse selection, team dynamics, and risk management through hands-on experience. Ricki shares war stories from the bootcamp trenches—infinite loop bugs that mirror Knight Capital's disaster, WiFi outages that create unexpected trading opportunities, and that the most successful trading teams often focus on internal team communication even more than trade execution or technical acumen.See the full transcript: https://www.complexsystemspodcast.com/think-like-a-trader-ricki-heicklen/–[Patrick notes: Complex Systems now produces occasional video episodes.You can access them directly on YouTube: https://www.youtube.com/@patio11podcast. My kids inform me that I’m supposed to tell you to like and subscribe.]–Links:Trading Camp : https://trading.camp/Metagame: https://www.metagame.games/#tickets Story of Knight Capital: https://www.sec.gov/files/litigation/admin/2013/34-70694.pdf–Timestamps:(00:00) Intro(00:46) Ricki's journey from trading to teaching(01:25) The birth of Arbor and first bootcamps(03:32) Developing a trader's mindset(05:53) Understanding heuristics in trading(08:21) Adverse selection in everyday life(15:40) Insights from teaching trading bootcamps(21:07) Pedagogical approach: learning by doing(32:00) Handling mistakes and learning opportunities(36:17) Unplanned bugs and real-world lessons(39:47) Learning from Knight Capital's bug(40:24) Understanding exchange-side bugs(43:10) Risk limits and strategy separation(44:41) Importance of UI in trading bots(46:53) The Madagascar button(48:20) The big red button in manufacturing(49:45) Simulated trading and information aggregation(50:29) Sibling trading game explained(53:24) Modeling and hidden information(01:01:15) Trading behavior and market updates(01:04:38) Real-world applications and lessons(01:13:58) Surprises and market opportunities(01:16:24) Pedagogical approaches in trading education(01:17:08) Market dynamics and counterparty behavior(01:17:53) Retail vs. institutional order flow(01:19:23) Simplifying trading concepts for beginners(01:21:27) Introducing market characters and their roles(01:31:31) Team dynamics and communication in trading(01:39:13) The importance of redundancy in trading systems(01:47:52) Future of trading education and online classes(01:53:47) Wrap

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• Achieving results in the physical world, with Adam Jarvis of “Public Service”

  Patrick McKenzie is joined by Adam Jarvis, author of the Public Service substack and a New Zealand civil engineer and public sector veteran. They discuss how political capital constraints, funding misalignment across government levels, and accumulated regulatory "scar tissue" make infrastructure projects extraordinarily difficult. The conversation reveals why replacing a water pipe now costs more in planning than the entire project did a decade ago, and how talent sorting has drained capacity from public institutions. Despite these challenges, Patrick and Adam find reasons for optimism about reforming government capacity.Complex Systems now has video episodes as well. Watch this episode and subscribe at: https://www.youtube.com/@patio11podcast–Full transcript: www.complexsystemspodcast.com/achieving-results-in-the-physical-world-with-adam-jarvis-of-public-service/–Links:Public Service Substack: https://alethios.substack.com/ –Timestamps: (00:00) Introduction to Complex Systems (01:13) Understanding local government functions (03:41) Challenges in public sector project delivery (06:31) Funding complexities in public projects (09:14) The burden of regulatory and legislative constraints(17:04) Appreciating the infrastructure we take for granted (23:02) Historical and modern infrastructure challenges (30:04) Talent mobility and its impact on public sector (33:35) Public sector hiring practices (34:11) Agglomeration effects and brain drain (36:04) Aging population and resource allocation (36:59) Structural factors in public sector layoffs (37:49) Hiring and firing in the public sector (40:39) Labor mobility and job security (46:34) AI and automation in public sector jobs (52:56) Risk aversion and process overload (01:01:30) Optimism for public sector reform 

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• The AI infrastructure stack with Jennifer Li, a16z

  In this episode, Patrick McKenzie (@patio11) is joined by Jennifer Li, a general partner at a16z investing in enterprise, infrastructure and AI. Jennifer breaks down how AI workloads are creating new demands on everything from inference pipelines to observability systems, explaining why we're seeing a bifurcation between language models and diffusion models at the infrastructure level. They explore emerging categories like reinforcement learning environments that help train agents, the evolution of web scraping for agentic workflows, and why Jennifer believes the API economy is about to experience another boom as agents become the primary consumers of software interfaces.–Full transcript: www.complexsystemspodcast.com/the-ai-infrastructure-stack-with-jennifer-li-a16z/–Sponsor:  VantaVanta automates security compliance and builds trust, helping companies streamline ISO, SOC 2, and AI framework certifications. Learn more at https://vanta.com/complex–Links:Jennifer Li’s writing at a16z https://a16z.com/author/jennifer-li/ –Timestamps:(00:00) Intro(00:55) The AI shift and infrastructure(02:24) Diving into middleware and AI models(04:23) Challenges in AI infrastructure(07:07) Real-world applications and optimizations(15:15) Sponsor: Vanta(16:38) Real-world applications and optimizations (cont’d)(19:05) Reinforcement learning and synthetic environments(23:05) The future of SaaS and AI integration(26:02) Observability and self-healing systems(32:49) Web scraping and automation(37:29) API economy and agent interactions(44:47) Wrap

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• Getting better at LLMs, with Zvi Mowshowitz

  In this episode, Patrick McKenzie (patio11) recorded with Zvi Mowshowitz (TheZvi) live at the LessOnline conference. They explore practical strategies for getting better results from large language models. Zvi explains how to customize AI behavior through thoughtful system prompts, while Patrick shares techniques for using LLMs as writing partners and research assistants. They discuss the evolving relationship between content creators and AI training data, touching on the emerging field of "generative engine optimization" (GEO). The conversation also covers multimodal capabilities, recursive AI use, and strategies for avoiding common failure modes like hallucination and sycophancy. –Full transcript: www.complexsystemspodcast.com/getting-better-at-llms-with-zvi-mowshowitz/–Sponsor:  VantaVanta automates security compliance and builds trust, helping companies streamline ISO, SOC 2, and AI framework certifications. Learn more at https://vanta.com/complex–Links:Don’t Worry About the Vase https://thezvi.wordpress.com/ –Timestamps:(01:08) Understanding system prompts(02:04) Customizing LLM behavior(05:58) Memory features in LLMs(10:21) Generative Engine Optimization (GEO)(15:59) Sponsor: Vanta(17:17) Art and AI: Enhancing creativity(20:36) Recursive use of AIs(25:22) Addressing LLM frustrations(27:05) Checking for hallucinations in AI outputs(28:11) Experimenting with AI models(29:44) Optimizing AI prompts and outputs(31:19) Using AI for writing and editing(32:32) AI as a research and writing partner(33:26) Prompting AI and humans effectively(39:39) Balancing AI assistance with personal voice(51:03) Wrap

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• Machine learning meets malware, with Caleb Fenton

  Patrick McKenzie (patio11) discusses software reversing and AI's transformative impact on cybersecurity with Caleb Fenton, co-founder of Delphos Labs. They explore how LLMs are revolutionizing the traditionally tedious work of analyzing compiled binaries, the nation-state cyber warfare landscape, and how AI is shifting security from reactive to proactive defense. They cover the technical details of malware analysis, the economics of vulnerability detection, and the broader implications as both defenders and attackers gain access to increasingly powerful AI tools. –Full transcript available here: https://www.complexsystemspodcast.com/machine-learning-meets-malware-with-caleb-fenton/–Sponsor:  MercuryThis episode is brought to you by Mercury, the fintech trusted by 200K+ companies — from first milestones to running complex systems. Mercury offers banking that truly understands startups and scales with them. Start today at Mercury.com Mercury is a financial technology company, not a bank. Banking services provided by Choice Financial Group, Column N.A., and Evolve Bank & Trust; Members FDIC.–Links:Delphos Labs: https://delphoslabs.com/ Virus Total: https://www.virustotal.com/gui/home/upload “Thel fraud supply chain”, Bits about Money https://www.bitsaboutmoney.com/archive/the-fraud-supply-chain/ –Timestamps:(00:00) Intro(01:20) Understanding software reversing(03:52) The role of AI in software security(06:12) Nation-state cyber warfare(09:33) The future of digital warfare(16:45) Sponsor: Mercury(17:49) Reverse engineering techniques(30:15) AI's impact on reverse engineering(41:45) The importance of urgency in security alerts(42:47) The future of reverse engineering(43:21) Challenges in security product development(44:46) AI in vulnerability detection(46:09) The evolution of AI models(48:06) Reasoning models and their impact(49:06) AI in software security(49:49) The role of linters in security(57:38) AI's impact on various fields(01:02:42) AI in education and skill acquisition(01:08:51) The future of AI in security and beyond(01:12:43) The adversarial nature of AI in security(01:19:46) Wrap

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