Podcasts about Layer

In this sponsored episode of The Bad Crypto Podcast, Joel and Travis welcome back Markus Levin, co-founder of XYO Network, a project first featured on the show back in the ICO days of 2018. Unlike many projects from that era, XYO is still building. The conversation centers on a huge problem in both crypto and AI: digital systems are often blind to the real world. Smart contracts, AI agents, apps, and autonomous systems can process data, but they do not automatically know whether that data is true, where it came from, or whether someone tampered with it. That is where XYO comes in. Markus explains how XYO has evolved from a proof-of-location network into what the team describes as a truth layer for real-world data. Using devices, mobile phones, sensors, NFC tags, cryptographic proofs, and its own data-focused Layer 1 blockchain, XYO is working to verify events, actions, assets, and real-world information so AI systems and blockchain applications can operate with greater certainty. Joel, Travis, and Markus also dig into the COIN app, which allows users to earn rewards for contributing real-world data, and the broader XYO ecosystem, including the XYO token, XL1 token, proof of origin, zero-knowledge privacy protections, and the newly announced AI infrastructure verification partnership with Setter Labs. The big idea: as AI becomes more powerful, the question may not be whether a model can generate an answer. The question is whether it can prove where that answer came from. Topics Covered Why AI agents and smart contracts are still “blind” to the physical world How XYO began as a proof-of-location project in 2018 Why GPS and location data can be spoofed The role of blockchain in verifying real-world events What “proof of origin” means and why it matters How XYO collects and verifies real-world data Why bad data may be one of AI’s biggest problems How verified data could reduce AI hallucinations The COIN app and how users can earn rewards for data collection XYO’s Layer 1 blockchain and the XL1 token The difference between XYO, XL1, COIN, and other ecosystem assets How zero-knowledge proofs help preserve privacy Why decentralized physical infrastructure networks may become increasingly important How XYO is moving into AI infrastructure and AI agent verification The new XYO AI SDK and what developers can build with it Why long-term survival matters in crypto Joel’s reminder that sponsored projects must still pass Bad Crypto vetting Featured Guest Markus LevinCo-founder of XYO Network Links Mentioned XYO Network: https://xyo.networkCOIN App: https://coinapp.coBuild with XYO: https://xyo.network/buildPartnership inquiries: partnerships@xyo.network Disclosure This is a sponsored episode of The Bad Crypto Podcast. Joel and Travis were compensated to feature XYO Network, but the project passed their vetting process before being brought to the Bad Crypto audience.Support the show: https://badcryptopodcast.comSee omnystudio.com/listener for privacy information.

"With animal welfare, we're basically waiting till the roof falls in — when the animals are at the shelter, that's the roof falling in. We have to catch them earlier." This episode is sponsored-in-part by Maddie's Fund, OcuTrap, and The Kitten Conference. What if the animal welfare system stopped waiting for families to walk through the shelter door — and started showing up before they ever got there? That's the question driving BJ Adkins, disabled veteran and founder of Animal Angels Foundation (AAF), a prevention-first nonprofit serving seven counties in central Alabama. After years of fostering and watching intake numbers refuse to budge, BJ decided to stop patching the system and start rebuilding its missing layer. AAF isn't a rescue organization. It's prevention infrastructure: programs designed to solve the problems that force pet surrender before surrender ever becomes an option. Those programs include SNIP, a spay/neuter assistance initiative with a $100 stipend for income-qualifying owners; The Bridge, which addresses the financial and housing barriers that most often precede surrender; Finder-to-Foster; Adoption Boost; Landlord Partnership; and Sniff and Greet. Connecting it all is the Animal Welfare Resource Network (AWRN) — a shared technology platform that replaces organizational silos with real-time coordination across shelters, rescues, vet clinics, and community partners. Three participation levels and no cost to join means even change-resistant organizations can get on board. To measure what's working, BJ is partnering with a University of Tennessee researcher to build the evidence base for prevention-first animal welfare — while already fielding calls from Colorado, Tennessee, and the Canadian SPCA. The data is being collected. The network is growing. And if BJ has anything to say about it, the roof won't have to fall in anymore. Press Play Now For: Why BJ compares the current animal welfare system to waiting for the roof to fall in — and what "upstream" intervention actually looks like A breakdown of AAF's six core programs and how each one targets a specific point of failure before shelter intake How the Animal Welfare Resource Network (AWRN) replaces organizational silos with a shared, real-time coordination platform The SNIP program's $100 stipend model and why removing financial friction matters for low-income pet owners BJ's strategy for bringing change-resistant organizations into the network — with three levels of participation and no cost to join How AAF is partnering with University of Tennessee researchers to build a data-driven case for prevention programs Practical advice for new nonprofit founders: research first, build relationships, and find the gap nobody else is filling Resources & Links Animal Angels Foundation Website Animal Welfare Resource Network (AWRN) Maddie's Pet Forum (where Stacy and BJ connected)

Agentic AI is not just a model problem. It is exposing gaps in how teams store, share, retrieve, and coordinate context across applications, agents, and people.In this episode, Amir talks with Karthik Ranganathan, cofounder and co CEO at Yugabyte, about why databases are under new pressure as AI moves from model serving into agentic workflows. They discuss Yugabyte's evolution, the limits of today's data infrastructure, and why memory, knowledge, and shared context may become central to how agentic systems actually work.Practical takeaways• Agentic workloads push databases beyond simple relational access because agents may need relational, vector, graph, NoSQL, scale, and multi tenant support in the same workflow.• A query can be optimized inside each data store and still be slow, expensive, or wasteful when the work spans multiple systems.• Context sounds simple to humans, but it becomes messy when it includes private memory, shared project knowledge, conversation history, team collaboration, and agent actions.• Human handoffs can erase much of the speed promised by agents when teams have to copy outputs, re explain reasoning, and manually reconcile conflicts.• Yugabyte is working on Meko as a data infrastructure layer for agents, with a focus on memory, knowledge, context quality, and shared learnings.Timestamped highlights00:43What Yugabyte does and why critical data needs to survive infrastructure change04:08How databases evolved from mainframes to internet apps, mobile, cloud native systems, and now AI09:42Why agentic workloads create new demands across relational, vector, graph, NoSQL, and multi tenant data12:29Why the current agentic data stack is still in the messy middle15:24Why context becomes hard when agents, people, teams, and permissions collide21:50How agent collaboration can fall back to human speed24:34How eeko aims to capture memory, knowledge, learnings, and reasoning across agent workflowsOne Line That Stuck“We have killed the velocity of agentic development and brought it back to human speed.”Practical signals for teams building with agents• Do not treat context as one generic blob.• Decide what should stay private, what should be shared, and what should become reusable project knowledge.• Watch for hidden cost when agents query across separate systems.• Pay attention to agent collaboration, not just single agent output.• Build for memory and knowledge flow before team size makes the gaps harder to fix.Follow The Tech Trek for more conversations with technical leaders building modern teams, products, and infrastructure around AI, data, and engineering execution.

Ep. 213 features Gregory Tolmochow, Founder & CEO of Trendline Labs, a startup building what it calls the “Bloomberg Terminal for prediction markets.”    Hear them discuss: Gregory's journey from sports betting analytics and The Betting Insider to founding Trendline Labs Why prediction markets represent a major evolution beyond traditional sports betting The pivot from an AI-powered sports analytics tool to a unified prediction market terminal Building a platform that aggregates pricing, liquidity, and data across multiple prediction market exchanges How Trendline's Optimus AI model helps users understand market pricing and identify opportunities The company's vision to become the trusted information source for prediction markets Monetization plans through premium subscriptions and transaction-based trading fees Regulatory considerations, including obtaining an Introducing Broker (IB) license to enter the U.S. market The ongoing debate around prediction markets, sportsbooks, market makers, and retail traders Trendline's roadmap, fundraising plans, and long-term goal of democratizing access to market intelligence   Catch the video version of this episode here.   Learn more

Welcome to Navigating Bitcoin's Noise, the show where we cut through the clutter and bring you the clearest insights on Bitcoin. I'm your host, Kane McGukin, and today I'm joined by Nik Bhatia, author of Layered Money and visiting fellow at the Bitcoin Policy Institute.  In this conversation, we break down Nik's landmark paper on stablecoins and statecraft and why the GENIUS Act may be one of the most strategically important pieces of legislation in decades.  We get into how the Eurodollar system quietly exported dollar governance offshore, how stablecoins are designed to bring it back, and why the end of China's deflationary unsystem is forcing America's hand. We ask the question that matters: are stablecoins just a fintech product, or are they America's most powerful tool for our next money layer?  If you're tired of hype and want a first-principles breakdown of how dollar dominance actually works, and what the U.S. is building to protect it, this episode is for you. So sit back, relax, and let's get started.  Kane McGukinX: https://twitter.com/kanemcgukinSubstack: kanemcgukin.substack.com Nik Bhatia X: https://x.com/timevalueofbtcThe Bitcoin Layer: https://thebitcoinlayer.com/Bitcoin Policy Institute: https://www.btcpolicy.org/authors/nik-bhatiaPaper: https://www.btcpolicy.org/articles/stablecoins-as-statecraft-reclaiming-us-financial-sovereignty-in-the-eurodollar-market

The meeting covered updates on Glamsterdam DevNet 4, discussions on target gas limit PRs, and the introduction of a new tool called Disruptor. The conversation also delved into EIP 7684 and EIP 8148, addressing the custom sweep threshold for validators and the return deposits for distinct credentials. The conversation covers a range of EIPs and their potential impact on stakers, validators, and node operators. It also discusses the proposal to change the timing of the ACDC call to accommodate participants from different time zones.TakeawaysGlamsterdam DevNet 4 issues and investigationsDiscussion on target gas limit PRsIntroduction of Disruptor tool for reorgs and network forksEIP 7684 and EIP 8148 for validators and return deposits EIP 8148 is supported by solo stakers, small operators, and institutional stakers due to its predictable cash flow benefits.EIP 8148's configurable cap is seen as useful for institutional stakers to manage risk limits and for solo stakers to consolidate into zero X02 validators.EIP 8148's automatic sweep mechanism is preferred for seamless reward accounting and better user experience.EIP 8061's increase in exit and consolidation churn is already implemented and tested, making it a candidate for SFI.The proposal to change the timing of the ACDC call to accommodate participants from different time zones is being considered for the next ACDC call as a trial.The decision to change the timing of the ACDC call will be based on the turnout and engagement of participants in the next call.Chapters00:00 Glamsterdam DevNet 4 Update13:02 Discussion on Target Gas Limit PRs21:35 Introduction of Disruptor Tool38:10 EIP 7684 - Custom Sweep Threshold for Validators48:08 EIP 8148: Predictable Cash Flow and Configurable Cap53:24 EIP 8148: Automatic Sweep Mechanism59:14 EIP 8148: Support from Node Operators01:08:22 EIP 8080: Exits Using the Consolidation Queue01:15:28 EIP 7688: Forward Compatible Consensus Data Structures01:21:25 ACDC Call Timing Change Proposal

Brendan Foody is the Founder and CEO @ Mercor, one of the leading data providers to the largest labs on the planet including OpenAI. In the last two years, Brendan has scaled the company to $1.5BN in ARR and a valuation of $10BN.  AGENDA:  True or False: Mercor lost Meta and OpenAI as a customer with the hack? Mercor has been poaching competitor talent, paying them millions?  Mercor revenue is not real revenue and is only GMV? 12:56 Would Brendan sell Mercor for $30 billion?  14:23 Why everyone is wrong that AI will lead to labor displacement? 15:59 We will create many new jobs that do not exist with AI.  16:59 Why training agents will be a massive labor category that does not exist today  19:51 Will we see the data provider market unbundle and specialize into verticals?  22:24 Is the stated revenue really revenue or is it really GMV?  27:55 How a 1 million ARR company secured one of the best investors in the world with a helicopter ride  29:41 How Felicis secured the deal of the decade with a race track and a set of Ferraris  32:59 Which investment round felt like the highest price to grow into?  34:49 Why will value accrue to the infrastructure layer, not the application layer, in the next 12 months?  35:46 Why the model is the product and why application layer companies should be scared as a result  37:22 Why network effects will be the determinant of value creation  38:46 Why the forward-deployed motion, not the GTM motion, will determine true value creation.  41:59 Why token spend within organizations is going to continue to increase  43:54 Why agent evaluation to commoditize the model layer will be a massive business for enterprises?  51:13 Why we should have increased capital gains tax  01:01:31 How to compete with $20 million a year from Meta?  01:08:49 Will Mercor go public and when?  

Kenny Wood is the newly appointed CEO of Sleepagotchi, the Solana-based platform building what it calls the intelligence layer for the wellness economy. A two-decade veteran of the games industry, Wood cut his teeth as an artist on Mattel's Barbie titles before working on chart-topping franchises including Mat Hoffman's Pro BMX, Transformers, Formula 1 and World Rally Championship, later moving into ship-simulation work at VSTEP in the Netherlands and serving as CTO of AI world-generation startup Moonlander prior to its acquisition by Alpha 3D. Why you should listen Sleep is the foundation almost every other health metric rests on, and that is precisely why Wood argues it is the right wedge into a much larger market. Fix sleep and mood, energy and recovery tend to follow; neglect it and the deficit cascades through everything else. Sleepagotchi began life as a gamified sleep-to-earn app, but under Wood the thesis has sharpened: the real prize is not the streak mechanic but the data exhaust it generates. The company reports that roughly three-quarters of users open the app within ten minutes of waking, and its Telegram-based Lite version has touched two million all-time users, the kind of daily habit loop most wellness startups never achieve. The question Wood keeps returning to is who should capture the value of all that biometric signal. The product architecture he describes is ambitious. Rather than a single sleep score, Sleepagotchi runs four cooperating AI agents: a sleep coach that explains causally why a night went the way it did, a wellness agent that checks in on mood, diet, caffeine and alcohol through the day, a meal planner that turns those insights into recipes, and a shopping agent that sources the ingredients or supplements and can have them delivered. If you are tired despite doing everything right, the system might infer low iron and nudge you toward leafy greens, then route that recommendation downstream into an actual basket. A built-in marketplace lets vendors offer supplements, courses and the like, knitting recommendation and commerce into one loop. It is a bold attempt to make wellness advice actionable rather than merely informational, and it leans on integrations with Whoop, Oura and Apple Watch to pull in the raw signal. The thornier and more interesting argument is about ownership. Wearable terms of service generally bar reselling raw device data, a constraint Wood acknowledges candidly, but he draws a line between that raw feed and the processed, AI-derived record of a person's life built on top of it, which he believes the user should own and, eventually, permission or monetize on their own terms via the platform's $SLEEP token. Wood inherits the company from founding CEO Anton Kraminkin, now a strategic advisor, and a cap table that includes Sfermion, 6th Man Ventures, Inception and others. In a relaxed closing stretch, he talks up the strength of the underlying game IP, its outsized following across Japan, the Philippines and Korea, and the new levels arriving in the months ahead, while staying refreshingly honest about the work still to do. The result is a conversation that doubles as a preview of where the AI agent economy and personal health data may be heading. Supporting links Stabull Finance Sleepagotchi Sleepagotchi on Twitter Andy on Twitter Brave New Coin on Twitter Brave New Coin If you enjoyed the show please subscribe to the Crypto Conversation and give us a 5-star rating and a positive review in whatever podcast app you are using.

Eunice Giarta, Co-Founder and General Manager at the Monad Foundation, joined me to discuss how Monad, as a high-performance Layer 1 blockchain, is aiming to address the scalability limitations of existing networks such as Ethereum. Recorded on February 5th, 2026.Brought to you by

I sat down with Kamal, President of the Board of the Hashgraph Association, to unpack how Hedera Hashgraph is taking a different approach to Web3 , one built around trusted governance, enterprise readiness and real-world use cases. Kamal shares how his journey started at EY Switzerland in 2015, led to co-founding Swisscom Blockchain, and eventually brought him to leading ecosystem development for one of the most institutionally backed Layer 1s in the space. We talk about AI and Web3 convergence, why polyglot platforms are the future, and the projects already live today , from microfinance in North Africa to customs automation with AirAsia's parent company. If you're a founder, builder or enterprise leader trying to understand where Web3 is heading, this episode is packed with signal. Disclaimer:Nothing mentioned in this podcast is investment advice and please do your own research. It would mean a lot if you can leave a review of this podcast on Apple Podcasts or Spotify and share this podcast with a friend. Be a guest on the podcast or contact us - https://www.web3pod.xyz/

Episode summary In this episode of Healthcare Beans, James speaks with Paula Muto, MD, founder of UBERDOC, about the barriers patients face in accessing specialty care and how direct-pay models may help reshape the healthcare system. Paula shares the story behind UBERDOC, discusses the growth of the platform, and reflects on broader themes including patient autonomy, price transparency, rural access, the shortcomings of managed care, and the role of technology in modern care delivery. What we cover Why Paula Muto founded UBERDOC The access and affordability problems the company was built to address How direct-pay specialty care can strengthen the doctor-patient relationship Why traditional healthcare systems often create friction and delay The rise of direct primary care and adjacent care models Managed care, patient autonomy, and the consequences of delayed treatment Price transparency as a tool for patient empowerment New approaches to rural healthcare access Technology's role in improving navigation and care delivery Direct pay, Medicare innovation, and new ideas around appointment access Chapter breakdown 00:00 Introduction to UBERDOC and Dr. Paula Muto01:20 The birth of UBERDOC: solving for access and affordability04:38 The growth of UBERDOC: from 40 to 5,000 doctors07:18 Empowering patients through the doctor-patient relationship09:43 Technology's role in modern healthcare11:35 The inefficiencies of traditional healthcare systems14:17 The rise of direct primary care17:04 The challenges of managed care and patient autonomy18:23 A personal story: the consequences of delayed care19:17 The exodus in healthcare20:47 Price transparency and patient empowerment23:24 Innovative solutions for rural healthcare25:56 The role of technology in patient care27:33 Challenges in the medical profession29:04 Direct pay and Medicare innovations31:31 Appointment banking and patient access Guest bio Paula Muto, MD is the founder of UBERDOC, a platform designed to improve access to specialty care through transparent, direct-pay appointments. A practicing physician and healthcare entrepreneur, she has focused her work on reducing barriers between patients and doctors while rethinking how care can be delivered more efficiently and affordably. Key takeaways Access remains one of the most persistent failures in healthcare delivery. Direct-pay specialty care offers an alternative to traditional referral and reimbursement pathways. Price transparency can give patients more agency and reduce confusion. Technology can improve care access, but only if it supports stronger doctor-patient relationships rather than more bureaucracy. New care models may not fully replace the current system, but they can expose where the system is no longer working well. Godspeed.. James

We continue “The Matrix” series with Layer 3 — The Financial Matrix, an unflinching examination of central banking, fiat currency, inflation, debt slavery, digital currency systems, corporate monopolies, and the growing consolidation of financial power. This episode follows the money trail through institutions like the Federal Reserve, BlackRock, Vanguard, Wall Street banking giants, and the international financial architecture shaping modern society from behind the scenes. We explore how inflation acts as hidden taxation, how consumer debt creates dependency, why endless consumption culture keeps populations distracted, and how economic fear can be used as a mechanism of control. From credit score systems to the emerging push toward centralized digital currencies, this episode asks a difficult question: has the modern financial system become a structure designed not to create freedom, but dependence? Featuring Scripture including Book of Proverbs 22:7 and concluding with the legendary lecture by G. Edward Griffin on Jekyll Island meeting, this is one of the deepest and most hard-hitting installments of the series so far.Email: thefacthunter@mail.comSupport us via Zelle: 719-651-0642

Bryce Harper of the Phillies squirts toothpaste directly into his mouth when he brushes his teeth so we asked you about the totally normal things you do in a really weird way. Plus, today's Weekend Oopsie after a long weekend has chemical burns and a cop sitting in a cop car. Catch up on everything you missed from today's show on The Morning Mix Podcast!Listen to The Morning Mix weekdays from 5:30am – 10:00am on 101.9fm The Mix in Chicago or with the free Mix App available in the Apple App Store and Google Play.Follow The Mix: The MixstagramGet the Free MIX App: Stream The MixSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

If you've ever rebuilt the same staff training from scratch, paid for a speaker who inspired everyone for two weeks and then disappeared, or stayed up late wondering what to train on next — this episode is for you.Chanie breaks down the four training patterns that keep school leaders stuck in activity instead of infrastructure, explains why most staff culture problems are predictable skill gaps (not personality issues), and introduces the Staff Culture Infrastructure Vault — a decade of field-tested, ready-to-use training assets available to only 100 schools before it's permanently retired.In this episode:- The four training traps and why none of them build lasting culture- Why one-time events don't change behavior — and what actually does- The teachable skills most teachers were never formally trained on- What training infrastructure looks like and how to deploy it across your school yearTune in and stop reinventing the wheel.Resources Mentioned:Get Chanie's book, This Can't Be Normal: https://thiscantbenormal.comExplore the Staff Culture Infrastructure Vault: https://schoolsofexcellence.com/vaultApply for Leadership HQ: https://schoolsofexcellence.com/applyFollow Chanie on Instagram: https://www.instagram.com/chaniewilschanski/Join the Schools of Excellence Lounge on Facebook: https://www.facebook.com/groups/schoolsofexcellenceloungeMentioned in this episode:Staff Culture Infrastructure VaultTrain your team on the fundamentals most teachers were never formally taught. $2,273 of proven staff training tools — yours for just $347: https://discovered.thrivecart.com/the-school-culture-foundations-vault/

In this episode, Arnold Amrhein, VP of Investments at CREO Capital, shares the idea behind his widely discussed article "The Anticipation Layer." He explains why data is becoming an asset, what hoteliers lose every time a booking comes through an OTA, and how AI could eliminate the long-standing trade-off between scale and soul in hospitality. A thoughtful conversation on the future of hotel operations, investment, and guest experience.Listen to our previous episode: Hospitality Works Best When Owners Think Like Operators - Arnold Amrhein A few more resources:If you're new to Hospitality Daily, start here. You can send me a message here with questions, comments, or guest suggestionsIf you want to get my summary and actionable insights from each episode delivered to your inbox each day, subscribe here for free.Follow Hospitality Daily and join the conversation on YouTube, LinkedIn, and Instagram.If you want to advertise on Hospitality Daily, here are the ways we can work together.If you found this episode interesting or helpful, send it to someone on your team so you can turn the ideas into action and benefit your business and the people you serve!Music for this show is produced by Clay Bassford of Bespoke Sound: Music Identity Design for Hospitality Brands

Most AI conversations focus on models. The better conversation focuses on systems. In this episode, we continue our interview with Matt Levenhagen, exploring a practical challenge many developers are facing: integrating AI into business operations without creating costly chaos. The answer is not buying more AI tools. The answer is building an intentional AI Workflow Architecture. About Matt Levenhagen Matt is the founder and CEO of Unified Web Design, a web development agency focused on custom solutions, WordPress development, e-commerce, memberships, and business systems. His background as both a builder and agency owner gave him a unique perspective on where AI creates real leverage instead of superficial automation. Follow Matt on LinkedIn. AI Workflow Architecture Starts with Context Control One of the most important operational realities Matt discussed was token usage. Businesses rushing into AI often underestimate cost scaling. Every interaction with large models consumes resources, and poorly managed context windows dramatically increase operational expenses. Instead of treating AI like unlimited compute, Matt focused on controlling context intentionally. That included: Monitoring token usage Limiting unnecessary memory loading Structuring retrieval systems Using different models for different tasks Preventing oversized prompts This is a systems-thinking problem, not merely a coding problem. Developers who ignore architecture end up with bloated workflows that become financially unsustainable. The fastest way to make AI unprofitable is to send unnecessary context into every request. Why Retrieval Matters More Than Raw Memory A major breakthrough Matt discussed was implementing Retrieval-Augmented Generation (RAG). This matters because AI systems do not need all the information all the time. They need the right information at the right moment. That distinction completely changes system design. Without retrieval architecture: Costs increase Performance slows Outputs become less accurate Hallucinations increase Operational complexity grows RAG allows systems to retrieve semantically relevant information instead of dumping entire databases into prompts. This transforms AI from brute-force processing into intelligent retrieval. The future of AI operations will likely depend less on giant models and more on efficient information orchestration. AI Workflow Architecture Requires Layer Separation Another valuable concept from the conversation involved separating operational layers. Matt described balancing: Local storage Business memory External AI APIs Workflow automation SaaS integrations This layered architecture creates flexibility. Instead of locking the business into one AI provider, workflows remain adaptable. Different models can handle different workloads depending on cost, complexity, and accuracy requirements. This becomes increasingly important as pricing models fluctuate. Businesses relying entirely on one provider risk operational instability if pricing changes dramatically. Layer separation reduces that risk. The businesses that survive AI cost volatility will be the ones architected for flexibility instead of dependency. Why Embedded AI Features Often Disappoint Matt also discussed the growing wave of SaaS AI integrations. Every platform now markets AI capabilities: Project management tools Communication platforms CRM systems Design software Documentation systems Yet many users feel underwhelmed. The reason is architectural isolation. These tools only understand limited slices of operational context. They automate micro-tasks but rarely improve larger workflows. That creates a false impression that AI itself lacks value when the real issue is fragmented systems. AI becomes more useful as the organizational context becomes more connected. This is why developers building custom operational layers still maintain an enormous strategic advantage. AI Workflow Architecture Is an Operational Discipline The strongest insight from these episodes may be that AI implementation is becoming operational engineering. Success now depends on: Information structure Retrieval design Workflow sequencing Context prioritization Cost management Human oversight This moves AI away from novelty experimentation and toward infrastructure planning. Businesses that treat AI casually will likely accumulate technical debt quickly. Businesses that approach AI architecturally will build scalable operational leverage. AI is no longer just a development tool. It is becoming an operational systems discipline. Developers Must Learn Economic Thinking One overlooked topic in AI discussions is economics. Matt repeatedly referenced balancing capability with cost. This becomes critical because AI pricing models are still evolving rapidly. Businesses that ignore usage economics may accidentally build systems that become financially impossible to scale. Developers now need to think beyond: Can this be built? They also need to ask: Can this be sustained? Can this scale economically? Can context costs remain controlled? Can cheaper models handle simpler tasks? This represents a major evolution in modern software architecture. Review your current AI workflows and identify where unnecessary context or oversized prompts may be increasing costs. Conclusion AI Workflow Architecture is rapidly becoming one of the most important technical disciplines for modern developers. Matt Levenhagen's approach demonstrates that successful AI implementation is less about chasing the newest model and more about designing sustainable operational systems. The companies that gain long-term advantage from AI will not necessarily be the companies using the largest models. They will be the companies with the best architecture. Stay Connected: Join the Developreneur Community

The conversation covers updates on the Glam Amsterdam DevNet 4 launch, delegate inclusion on field calls, an update on EIP 7904, EAP 8188 discussing state tiering, and EAP 8182 proposing private transfers to Ethereum. The conversation covers innovative authentication methods, ZK proof and hardware wallets, credential proof separation, risk mitigation, synchronous composability, security and soundness mitigation, gas costs, supply side work, deactivation of self-destruct, and client feedback on execution API cases.TakeawaysGlam Amsterdam DevNet 4 launch updatesDelegate inclusion on field callsUpdate on EIP 7904EAP 8188: State tieringEAP 8182: Private transfers to Ethereum Innovative authentication methods allow users to bring their own authentication, ZK proofs enable hardware wallet authorization, and credential proof separation ensures synchronous composability.Deactivation of self-destruct functionality requires careful consideration of potential impact on existing contracts and use cases.Chapters00:00 Glam Amsterdam DevNet 4 Launch18:42 Update on 790437:30 EAP 8182: Private Transfers to Ethereum43:15 Credential Proof Separation57:17 Deactivation of Self-Destruct01:11:23 Client Feedback on Execution API Cases

In Episode 105 of the Cybersecurity Readiness Podcast Series, Dr. Dave Chatterjee is joined by Andrei Robachevsky — Technical Director of the Internet Integrity Program at the Global Cyber Alliance, founding contributor to MANRS (Mutually Agreed Norms for Routing Security), former CTO of RIPE NCC, and former Senior Director of Technology Programs at the Internet Society — to examine a cybersecurity risk that almost no enterprise security team is governing: the internet routing layer.Opening with the June 2024 Cloudflare 1.1.1.1 BGP hijack incident — where two Brazilian network operators' routing mistakes propagated to over 300 networks across 70 countries, silently rerouting traffic for several hours without triggering a single enterprise security alert — Dr. Chatterjee frames the episode's central challenge: organizations with excellent perimeter controls, clean firewalls, and healthy identity systems can still have their user traffic redirected to unintended destinations by failures occurring on networks they have never heard of, in countries they have no operations in, governed by routing norms they have never been asked to consider.Drawing on the February 2026 MANRS Report, Robachevsky explains that the Border Gateway Protocol (BGP) — the foundational routing system across nearly 80,000 autonomous networks — has no built-in authentication. Routing incidents occur 200 to 300 times per month, most of which are invisible to enterprise security teams, manifesting as unexplained outages or performance degradation rather than as identifiable threats. The implications range from SLA breaches and erosion of customer trust to man-in-the-middle exposure of silently rerouted traffic.Analyzed through Dr. Chatterjee's Commitment–Preparedness–Discipline (CPD) framework, the conversation delivers a clear and actionable message: routing security is not a network engineering problem — it is a supply chain governance problem. The tools already exist. RPKI exists. MANRS exists. MANRS+ is nearly here. The gap is entirely on the governance side, and it is closeable. The organizations that will not find themselves in the next routing incident are the ones that start with a map of their connectivity supply chain and a single question to every provider: Are you MANRS+ certified?To access and download the entire podcast summary with discussion highlights - https://www.dchatte.com/episode-105-the-invisible-layer-governing-routing-security-as-a-supply-chain-risk/Connect with Host Dr. Dave ChatterjeeLinkedIn: https://www.linkedin.com/in/dchatte/ Website: https://dchatte.com/Books PublishedThe DeepFake ConspiracyCybersecurity Readiness: A Holistic and High-Performance ApproachArticles & Cases PublishedChatterjee, D. (2026). Root: Automating the Remediation Gap, Ivey Publishing, Jan 7, 2026.Ramasastry, C. and Chatterjee, D. (2025). Trusona: Recruiting For The Hacker Mindset, Ivey Publishing, Oct 3, 2025.Chatterjee, D. and Leslie, A. (2024). “Ignorance is not bliss: A human-centered whole-of-enterprise approach to cybersecurity preparedness,” Business Horizons, Accepted on Oct 29, 2024.Isik, O., Chatterjee, D., and Lourenco, D.A. (2024). “Getting Cybersecurity Right,” California Management Review — Insights, Accepted for Publication, July 8, 2024. Chatterjee, D. (2023). “Mission critical – How American Cancer Society successfully and securely migrated to the cloud amid the pandemic,” I by IMD, March 13, 2023.Chatterjee, D. (2022). “Preventing security breaches must start at the top,” I by IMD, September 28, 2022, Institute for Management Development, Lausanne, SwitzerlandChatterjee, D. (2022). “Making Cybersecurity Readiness Mainstream,” Executive Blog Post, NETSPI, March 1, 2022Benz, M. and Chatterjee, D. (2020). “Calculated Risk? A Cybersecurity Evaluation Tool for SMEs,” Business Horizons, available online from May 4, 2020Chatterjee, D. (2019). “Should Executives Go To Jail Over Cyber Attacks,” Journal of Organizational Computing and Electronic Commerce, Vol 29, Issue 1, pp. 1-3.Abraham, C., Chatterjee, D., and Sims, R. (2019). “Muddling through cybersecurity: Insights from the U.S. healthcare industry,” Business Horizons, July 2019.

Most fintechs treat cross border payments as a cost centre. George Davis built a business that treats it as the $100B infrastructure opportunity nobody else is rebuilding, and grew 55X in 12 months doing it.In this episode I speak with George Davis, Co-Founder and CEO of Lorum, a global clearing and settlement infrastructure business serving financial institutions across the Middle East, Europe, Asia, and beyond. George is a serial founder who previously co-founded BVNK before leaving to rebuild the layer of the payments stack that big banks have left untouched.Key takeaways:The payment system isn't broken; banks running it are wrongly incentivisedWhy stablecoins add friction to cross border payments rather than removing themHow mid market fintechs can access wholesale treasury rates and turn FX into a profit centreWhat access to clearing infrastructure actually means for remittance, payroll, and import-export businessesWhy Lorum 55X'd in 12 months by going after the bottom of the payments stackGeorge also shares the founder mindset behind Lorum's growth: first principles thinking, radical adaptability, and hiring for obsession over experience.

Episode Highlights With KatieWhat humic and fulvic minerals actually are ... and why they're not electrolytesThe difference between fulvic (small, cellular) and humic (larger, gut-supportive)Why these minerals used to come from rich soil… but don't anymoreHow humic minerals bind toxins gently without stripping nutrientsHow fulvic minerals improve mineral absorption & mitochondrial signalingTheir role in gut health, microbiome balance, and gut lining repairHow they help move sodium, potassium, magnesium into the cellWhy they're crucial for detoxification in a modern environmentHow humic/fulvic increase cellular voltage and hydrationHow to take them: liquids, drops, powders & when they're most helpfulWhy these aren't “either/or” ... they are a both/and with electrolytesResources MentionedBEAM MineralsHiyaHiya created a super powered chewable vitamin for kids that packs twelve organic fruits and vegetables plus fifteen essential vitamins and minerals into every dose. Try it at hiyahealth.com/wellnessmama for 50% off your first order.BioptimizersI love and use so many products from them, but I especially love the magnesium and digestive enzymes. Visit bioptimizers.com/wellnessmama and use wellnessmama15 at checkout to get the best deal

The most expensive AI mistake of 2026 won't show up on any invoice.

Hosted by David Cowen | Careers and the Business of Law Everyone's talking about Harvey, Legora, Spellbook, and Ivo. Nobody's talking about what they ride on top of. Tom Baldwin - founder and CEO of Entegrata, former CIO at Foley, Sheppard Mullin, Reed Smith, and Cadwalader - argues the real story is data infrastructure. Without a single source of truth, every AI tool in your firm is working from a partial picture. WHY THIS MATTERS? If your firm is buying AI tools without auditing the data underneath them, this is your warning shot. Tom's framing: toaster ovens need an electrical grid. KEY TAKEAWAYS AI tools work on narrow tasks, not whole-firm intelligence. 50 asset purchase agreements? Great. 200 million documents? No. Pulling documents out of your DMS strips away the metadata that makes them valuable - judge, opposing counsel, area of law, industry. That context is what AI actually needs. Business-of-law use cases (lateral prediction, cross-sell, client attrition, FP&A) are wide open. Practice of law got all the attention. A data lakehouse unifies data across 20-40 systems. Snowflake popularized it; Azure/Databricks/Fabric are the modern stacks.  Cost is roughly the same at 200 lawyers or 2,000 - six figures, ongoing. Compute and storage are cheap; talent is the investment. Firms move from "nice to have" to "must have" after a near-miss. Tom's example: a firm almost fired an associate because their FTE calc didn't account for maternity leave. The chief data officer is becoming a real C-suite role. Sidley's among the early movers. Watch the forward-deployed legal engineer trend. Harvey is hiring practitioners for these roles. PEOPLE MENTIONED David Cowen - Host Tom Baldwin - Entegrata founder & CEO Andrew Sieja- Founder of kCura/Relativity; Entegrata's first angel investor Renee Morris, Katrina Dittmer, Glenn LaForce - Data leaders Tom mentioned COMPANIES AND TOOLS MENTIONED Entegrata - Turnkey data lakehouse in Azure Snowflake, Azure, Databricks, Microsoft Fabric - Data platform stacks Harvey, Legora, Spellbook, Ivo - Practice-of-law AI tools Sidley Austin - Early adopter of the chief data officer role

Ep. 211 features Filip Michalsky from Soap Payments, an AI-native orchestration layer designed to simplify the complex payments stack for real-money gaming operators. Hear them discuss: Filip's path from professional squash in the Czech Republic to Harvard AI data science and Fidelity Investments. The "iceberg" of payments: Navigating the hidden layers of issuing banks, acquiring banks, and convoluted funds movement. Using AI agents to slash payment onboarding times from months to a single week. How unified stablecoin rails enable "instant settlement," allowing operators to receive funds in five seconds. Protecting operators against "bad actors" with specialized defenses that maintain a 0.2% chargeback rate book-wide. The "vibe coding" vs. review approach: Scaling to 30+ customers with a lean, seven-person team. Moving beyond gaming: Early traction and expansion into the massive online health vertical. Strategic funding from Antler, AeroPay, and Astralis Capital ahead of an upcoming larger seed round. The five-year vision: Becoming a global payment orchestrator alongside category leaders like Stripe.   Listen to Business of Betting, the premier podcast covering the business of the sports betting industry featuring host Jeff Edelstein, on Spotify, Apple Podcasts and YouTube   Catch the video version of this episode here.   Learn more

The future of war has been evolving before our eyes in Ukraine, yet the west still plans to fight the last war. In this special episode, guest host Noah Smith (@noahpinion) and Brandon Anderson sit down with Yaroslav Azhnyuk (@YaroslavAzhnyuk), a serial tech founder who went from building PetCube to founding The Fourth Law, one of the world's most advanced AI-guided drone companies. Over two hours we cover the technology, tactics, and geopolitics of drone warfare, and why the modern battlefield has already left the West behind:* Yaroslav's personal history and the Ukraine war [00:01:04 – 00:14:01]* The modern drone tech stack: why FPV drones are the new god of war, the future of the rifleman, fiber optic vs. AI, five levels of autonomy, and the eight dimensions of the autonomous battlefield [00:14:01 – 01:05:13]* The geopolitics and economics of drones: China's manufacturing advantage, the drone race, Western defense readiness, countermeasures, and why the gap is widening [01:05:13 – 01:58:57]For those looking for Noah Smith's commentary, it really gets going around the 00:51:31 mark.Yaroslav Azhnyuk / The Fourth Law:* X: https://x.com/YaroslavAzhnyuk* LinkedIn: https://www.linkedin.com/in/yaroslavazhnyuk/* The Fourth Law: https://thefourthlaw.aiNoah Smith:* Substack: Noah Smith * X: https://x.com/noahpinionTimestamps00:00:00 Cold Open: China's 4 Billion Drones and the Cameras-to-Explosives Pipeline00:01:04 Introduction: Brandon, Noah Smith, and Yaroslav Azhnyuk00:05:41 From Tech Entrepreneur to Defense: PetCube, Brave One, and the D3 Fund00:10:42 The Ethics of Building Weapons: Dual-Use Technology and the Wolf at the Door00:14:01 The Tech Stack: Cameras, Autonomy Modules, Interceptors, and a Semiconductor Fab00:18:47 Fiber Optic vs. AI: The Radio Horizon Problem and $32/km Cable00:25:32 FPV Drones: The New God of War — 70–80% of Frontline Casualties00:28:28 The Five Levels of Drone Autonomy: From Terminal Guidance to Full Autonomy00:41:37 The Eight Dimensions of the Autonomous Battlefield00:45:32 AI Safety and the Morality of Autonomous Weapons00:51:31 The End of the Rifleman? Noah's 2013 Prediction vs. Battlefield Reality01:05:13 China's Manufacturing Advantage and Western Vulnerabilities01:24:21 Policy Advice for Western Defense: Defense Valley and the Widening Gap01:32:54 The Drone Race: Who's Ahead, Category by Category01:41:57 Countermeasures: Shotguns, Jammers, Lasers, and Fishnets01:58:19 The Wedding and Final Takeaway: Be Prepared for WarTranscriptCold Open: China, FPV Drones, and the New Warning SignYaroslav [00:00:00]: Think about this. Last year, Ukraine produced 4 million FPV drones. Ukraine is not the most industrious nation in the world. China can produce 4 billion of these FPV drones.Noah [00:00:10]: Would you say that right now China is now the supreme conventional military power on Earth, given its ability to manufacture and deploy drones in the quantity and quality that you just described?Yaroslav [00:00:20]: I don't think we have all the information to claim that but we cannot count it out, and that alone should be a big warning sign. As I say, at some point in my life I went from making cameras that fling treats to pets to cameras that fling explosives to the occupiers. So that's the short story. And when you think about what your nation, what your patriots are going through, you realize that's the only morally right thing to do is to fight back, and it is immoral not to fight back, and then the choice becomes very clear.Introduction: Yaroslav Azhnyuk, Petcube, and the Last Flight into KyivBrandon [00:01:04]: Welcome to Latent Space. I'm Brandon. I normally do science podcasts, but today we're going to do something a little bit different. I'm joined by Noah Smith of Noahpinion on Substack and Twitter. And he has lots of interesting things to say about drones. And as a guest, we have Yaroslav Azhnyuk, founder of The Fourth Law and several other, drone-related startups. To get started, it is February 23rd, 2022. You are running a pet startup. You're connecting pets with their owners. Let's go in just a little bit of background. How did you get started in tech, and what were you working on before the Ukrainian war started?Yaroslav [00:01:50]: Good to be here. Thank you. On February 23rd, late in the evening, 11:00 PM Kyiv time, my wife and I landed in Kyiv. Actually, then she was a fiance. We came from Lviv, where we were looking at a church, where our wedding should have taken place. And we got into this cab ride from the airport to our home, and the driver was like, “You crazy. Like, everyone's leaving Kyiv. Why do you come?” We're like, “What? Nothing's going to happen. Dude, chill.” And then obviously, eight minutes later, or eight hours later, the bombs fell in the city. It was quite surreal. We probably landed on the last flight that landed in Kyiv, or one of those last flights. My background, I'm a tech guy. Studied applied mathematics in Kyiv Polytechnics, born and raised in Kyiv. My parents are old PhDs from academia, and grandparents too. Like, everything, from linguistics to nuclear physics. And I'm an entrepreneur, so I've built a bunch of companies. Petcube is the one you were referencing. So I lived in San Francisco 2014 to 2020, building Petcube, which is one of the leading, pet device companies in the world, selling lots of pet cameras. And then, yeah, as I say, at some point in my life I went from making cameras that fling treats to pets to cameras that fling explosives to the occupiers. So that's the short story.February 24th: Leaving Kyiv as the Invasion BeginsNoah [00:03:28]: February 24th, I guess a few hours after you, go to check out your wedding chapel, what do you do?Yaroslav [00:03:37]: We had a plan for this situation. So my parents and family live in Kyiv, and we're like, “Okay, this has actually started. The worst has, come true.” And so we basically packed our belongings and got in the car and spent 17 hours driving west. And that was pretty sure most people in our audience watched at least one apocalyptic movie in their life, so that was exactly like that. Like, felt exactly like that. Missiles are falling. Like, there was smoke in Kyiv. Like, my dad and I went, like, to central part of the cities. It's probably, likeYaroslav [00:04:20]: 800 meters from presidential office, to pick some stuff up at his workplace. Because he's, like, the head of an academic institution, so he had to get some of the things with him. And super surreal. Like, the streets are empty. Like, the gas stations are out of gas. Like, we found some gas station. We didn't have, like, spare canisters with us, so we're like, We figured out, like, the car was diesel, so like, we figured out, if it's diesel, you can actually store it in plastic, canisters, and we bought some window wash for the cars. We poured it out of the canisters, and we poured the diesel into that. Yeah, so it was like that. And then, like, helping friends get out, like my friend and his dog. Like, we found Like, my brother was also, like, riding in a separate car. We found a place for my friend who didn't have a car. It was like, yeah, it was like, totally surreal. And we didn't know of course, and you didn't know this will last for so long. You didn't know whether Ukraine will be able to defend Kyiv. And it was like, yeah, very little information and very little insight into future.From Pet Cameras to Defense Tech: Building for Ukraine and the Free WorldNoah [00:05:42]: What are your thoughts with regards to how do you, defend, Ukraine? So you eventually start building drones Like, what is the process to get from there from where you were building, devices that connect owners with pets to building drones, and what other things did you do to help the war effort in the process?Yaroslav [00:06:07]: It's definitely non-trivial, right? Like, I didn't go, to I didn't get any, like, military education when I was a student. Like, normally, in Ukraine, you would, you would go to like, this military school even if you're getting higher education in any other, sphere. I decided to skip that which is like, an unusual way to go. And I never thought that I will be somehow engaged in a war effort. Like, what is war? Of course, wars are over. It's the end of history. So one thing you got to understand about, like, many Ukrainians and like, I guess, it's also true about most of the people I met here in the US, that your who you are in terms of your nationality is a big part of your identity. So when that gets under attack, it's something deeper than just the country you live in gets under attack, right? And I Day one, I figured I'm going to I'm going to fight back with everything I can, right? But I didn't think on day one that I'm actually going to do, weapons. And a bunch of things. We were reaching out to a number of American, congresspeople and senators, and basically advocating for support of Ukraine, for voting for lend lease, which has happened in May 2022, but didn't actually work as expected. We helped start, Brave One, which is now a very important defense innovation cluster, sort of like a DIU here in the US. We helped start, a fund called D3. It's like, it was started or co-started by Eric Schmidt, former CEO of Google. So a bunch of these odd things, but then eventually I was like, “Okay,”by 2023 it was obvious this thing, A is going to last a lot more time, and B, that the whole world is shifting and that there's going to be a new arms race, that the warfare is redefined by drones as platforms. And for the first time in history, you have a platform that is software defined, that can increase your battlefield capabilities, in a in a step change just overnight. So it's like if you were able to push a software update and get all of your Roman legionnaires a new helmet? That has never been possible before. It's the first time in the history of war this is possible. So all of that and many other things like, supply chain fragilization, and the impact that AI is going to have on all of this all these things have become evident to me in 2023, and it's like, “Okay, I should do what I do best, or what I know how to do best, start a tech company, and sort of leverage the global techno capitalist machine, to provide, defensibility to Ukraine and the free world.” So that's literally the mission of the company, increase defensibility of Ukraine and the free world. And then there was some sort of soul-searching and like, asking yourself. It's like, “Okay, am I Actually, I know nothing about weapons. Am I actually, like, ready to make, things that other people use to kill other bad people?”Yaroslav [00:09:36]: When you think about what your nation, what your Compatriots are going through And think about all the terror of places like Bucha, the occupied cities in the east and south, the abducted children, the raped women, all the economic damage that's being done, and the intention to destroy a whole nation, to genocide the people of Ukraine, you realize that's the only morally right thing to do is to fight back, and it is immoral not to fight back. And then the choice becomes very clear. And look, we're just passing the ammunition. We're not doing the actual job. The actual fighters and defenders and heroes are people in the armed forces. We're just support.The Moral Question: Weapons, Responsibility, and Fighting BackNoah [00:10:33]: I have so many questions. Actually, I know you seem to have a question. Do you want to ask anything?Yaroslav [00:10:38]: No, I'm just listening. Go ahead.Noah [00:10:40]: I do want to talk about, some of let's say, the moral issues, like you just said. You endYaroslav [00:10:50]: I think there are no issues there.Yaroslav [00:10:52]: What would an example of a moral question be in this case?Noah [00:10:55]: No, I mean Okay. As you just said, you are creating the tools, but others are using them.Noah [00:11:05]: I was maybe thinking of having this conversation later, but one of the questions is like, is it actually you are going to be building them for your homeland, which you are building it for your homeland, which is I think, very a strong morally defensible position, but this technology is not going to stay with you, right?Noah [00:11:26]: This you will probably be selling these to other people Yeah. So the future is really where the moral issues may come into playYaroslav [00:11:38]: The this question becomes, easier and more complete if we ask this not about a particular technology or particular weapon, if we think that this question actually applies to any kind of technology Right? So -Knife or fire. You can use knife to do surgery and save people's lives, or you can use it as a weapon to take people's lives.Noah [00:12:06]: Cut tomatoes, too.Yaroslav [00:12:08]: Cut tomatoes too.Noah [00:12:09]: Yes, knife.Yaroslav [00:12:09]: That's helpful.Noah [00:12:10]: In Japan, sword and knife, they, call the same word.Yaroslav [00:12:14]: It's like, it's with any technology. Large language models, right? Look at how powerful they are and yet they're available to anyone in North Korea or in Russia.Yaroslav [00:12:29]: That's one side of the argument. The other side is As a maker, what is your responsibility for how the tools you're creating, will be used? There's definitely some responsibility, right? Then How should the decision process look like? Should you, like, try to calculate all the possible scenarios before starting to work on something? Or do you create something that is needed now to save people's lives, and then think about, addressing the unwanted edge cases later? In ideal world where there's like, or okay, it's not ideal world. In a mythical world where there is some one governing party and it gets to decide everything, and there is no other country, that can, decide on their own, you could say, “Well, we need to calculate for all the consequences, and only then, maybe build this building, by replacing this park because, maybe we need this park in the city,”right? So that kind of situation. But when you're in a situation where you're in a forest, in front of a wolf, you first going to deal with the wolf that wants to eat you, and then you're going to go consult Greenpeace. So that's kind of situation that Ukraine is in.The Fourth Law, Odd Systems, and Ukraine's Drone StackNoah [00:13:59]: Enough. Because this is a tech podcast, I did want to spend some time talking about, sort of the tech in that you've developed and what you've been working on. So can you explain, I guess, first of all, like, the problem that you were trying to solve from a technical standpoint? And I think, and then maybe, like, go into some of the solutions and some of the design process that led you from designing, little laser-guided, guiding lasers with a with an iPhone versus Having drones.Yaroslav [00:14:34]: Like, it so happened, that my partners and I, we sort of So I started one company called The Fourth Law, and its goal was and is to Make, massively scalable on-drone autonomy. And then In parallel with that together with my, Petcube co-founders, partners, and friends, we started another company called Odd Systems Which, was focused on making thermal cameras. Cameras, thermal cameras are seeing thermal radiation and are used to see at night. And we're now sort of those companies are getting closer and closer together and we're probably going to merge them. And this group of companies is currently the leading, team in on-drone AI and thermal imaging on the Ukrainian battlefield, and Likely one of the leading, if not the leading in the world. So We have these, like, three sort of business units, which are cameras, drone autonomy, and drones. So the cameras and drone autonomy sell daytime and nighttime cameras and different types of drone autonomous modules to other drone manufacturers, over 200 drone manufacturers in Ukraine. And then the UAV, business unit sells the drones themselves to the armed forces of Ukraine, Ukrainian government. And there are different types of drones. Those are sort of front strike, as we call them, so those are sort of FPV strike drones and the bombers, and then interceptors. And there are different kinds of interceptors. We do Shahed interceptors and we do ISR interceptors. We don't do the deep strike-FPV Drones, Interceptors, and Battery-Powered WarfareNoah [00:16:32]: What's an ISR interceptor?Yaroslav [00:16:33]: ISR is stands for intelligence, surveillance, reconnaissance, and those are basically drones which are which, Russians are using to watch over positions and then communicate where, the targets are coming.Noah [00:16:48]: It's a reconnaissance.Yaroslav [00:16:48]: That's, the ISR is sort of a classical term for a for a reconnaissance drone.Noah [00:16:53]: Are all of these battery-powered drones that you just described? ‘Cause I know that the sort of deep strike drones still have, like Some sort ofYaroslav [00:17:01]: Internal combustion engine?Noah [00:17:02]: Internal combustion engine. Are all the things you're talking about battery-powered?Yaroslav [00:17:06]: What we're working on is all battery-powered, right? We don't do the deep strikes, right? And then in terms of autonomy-Noah [00:17:12]: You can catch a Shahed with a battery-powered thing. It's not Fast to catch.Yaroslav [00:17:17]: No, absolutely. Look, Shahed interceptor, like ours, it's called Zero, it goes up to 326 kilometers per hour.Noah [00:17:26]: For reference, how fast is a Shahed?Yaroslav [00:17:28]: Eight, like, in internal phase it could be 280, but in cruise phase it's, like, 220-ish.Yaroslav [00:17:36]: Yeah. And sorry, I'm not like you can convert that into miles if you're interested.Noah [00:17:41]: No, that's fine.Noah [00:17:41]: Multiply by two thirds or point six or something.Yaroslav [00:17:44]: That's easy. Yeah, I was saying that for autonomy modules, right, we, -We make systems, autonomous systems for frontline, for interceptors and some for deep strikes as well, and then different levels of autonomy. So from terminal guidance, which is like lasts 500 meters, give or take, to autonomous bombing, to autonomous target detection, to autonomous navigation and all of that across day and night, different terrains, different time of the year, different platforms like quadcopters and fixed wing, and maybe some other platforms. So it's quite a wide variety of products. We also have like our own simulation. We have our own training school for the war fighters. And we're about to start construction of two, semiconductor plants to make, sensors for thermal cameras. So that's super exciting for me as a computer science guy is Doing semiconductors. Super cool.Noah [00:18:49]: Like in terms of kind of core drone technologies, you basically are one is an FPV replacement without fiber optics, and the other isYaroslav [00:18:59]: YouNoah [00:18:59]: Signal tracking with interceptorsYaroslav [00:19:00]: With or without fiber optics. Fiber optics Is just like, sort of a communication module.Yaroslav [00:19:05]: You can, you can use classical analog, video link and radio link. Those would be two separate radios. You can do digital, or you can do fiber optic, and then fiber optic Has its own advantages but also adds weight and decreases, the distance and decreases, how fast you can, sort of turn and With a drone. Yeah.Noah [00:19:33]: Do you need AI for fiber optic drones?Yaroslav [00:19:36]: Like you can use AI for fiber optic drones. AI replaces a human, right? Fiber optic is making your communication link more resilient. So those are slightly different goals. Like if you want, you can have, AI controlling hundreds of fiber optic drones instead of having 100 operators for each.Fiber Optics, Radio Horizons, and Terminal GuidanceNoah [00:20:03]: I guess I thought that the key reason that people moved to fiber optic drones was for like electronic, countermeasures. Or I guess to counter those.Yaroslav [00:20:13]: I think that's a correct assessment from sort of a public awareness standpoint. In practice it's somewhat more difficult Because besides electronic countermeasures, you have these issues of a radio horizon For FPV drones, which means that asYaroslav [00:20:36]: I believe Earth is round Some people disagree. But basically if you fly a drone and you have a land station over here and a drone flying over hereYaroslav [00:20:49]: If your drone is flying high, you have good direct radio visibility. If your drone goes low, and usually, Russian infantry and vehicles, they're on the ground and you want to hit them, you need to go low. Lower you go, maybe you'll get behind a hill or behind a forest, and if you're far enough, you'll just get behind the curvature of the earth. You get into what's called a radio shadow. And then That is a real bummer because for the last, be it 60 or 20 meters, you won't be able to see anything and it will be very difficult to hit the target. So to counter that what-- And then the distances that these FPV drones, act on they're, they can be quite large. So for example, here in the US there was this drone dominance program competition, and in drone dominance the furthest distance was about 10 kilometers.Noah [00:21:44]: What was drone dominance? What was that competition?Yaroslav [00:21:47]: Drone, the drone dominance is a is a program started, by the US government, to accelerate the development of drone technology here in the US.Noah [00:21:57]: Got it. And the longest range thing they were using was 10 kilometers.Yaroslav [00:22:00]: Was 10 kilometers, right. In Ukraine, like if your drone doesn't fly at least 20, 25, it just, no one's interested in it, and the usual hits are happening. It was like, okay, many hits are happening between 30 and 40 kilometers, and that's what expected from a regular 10-inch, FPV drone. So at that distance, even at altitudes of like 60 to 100 meters, you might start losing, the link. So some of the earlier AI technology that was fielded in FPV drone was this terminal guidance technology. That was the first product that we ever, launched that helped you as an operator, once you see the target from two, three, 500 meters, you lock onto the target and then, it just, drives the drone towards the target no matter what, even after you lost the visual connection. So optic fiber solves that. However, if you want to go like 20 kilometers with optic fiber, that will add an extra three kilos, of useful weight to your drone. SoNoah [00:23:12]: ‘Cause the cable that you have to unspool as you go weighs.Noah [00:23:15]: It is heavy.Yaroslav [00:23:15]: At first, like the spool is about 800 grams, so a bit less than a kilo, and then, and then think about 10, 10 kilometer optic fiber is another kilo, something like that. That takes away from your useful mass and then now you have like, you need a 15-inch drone and it can only carry maybe one or two kilos of explosives if you want to go, 20 kilometers. If you want to go to 30 or 40, like 30 is probably max. 40 is like very problem problematic on optic fiber. And then the problem with optic fiber is it's actually getting super expensive. So and why? Because of all the data centers for AI. That's literally the same optic fiber-Noah [00:24:01]: We're running out of centersYaroslav [00:24:02]: That's being used there.Yaroslav [00:24:02]: Like when Ukrainians and Russians come to Chinese factories to buy the optic fiber, they're like, “We're out. We sold it out to the Americans.”? That's the craziest thing. So optic fiber went up in price from like, $4 per, kilometer to like, $32 per kilometer in a few months in the beginning of this year. And I'veBrandon [00:24:26]: Claude Code is stopping the Russian drone effort here.Yaroslav [00:24:30]: Ukrainian as well. Yeah.Brandon [00:24:31]: Ukrainian. But I read somewhere that the Russians had grown more dependent on fiber optic drones relative to the Ukrainians, and that's one reason why the Ukrainians have sort of regained the initiative in drones recently.Brandon [00:24:42]: How accurate's that?Yaroslav [00:24:43]: The Russians were the first ones to scale that. I think by as of now, Ukraine has caught up. I think, like, as of maybe three months ago, Ukraine is mostly caught up on fiber optic. Yeah.Brandon [00:24:57]: What percent of damage would you say is in terms of FPV drone damage would you say is now fiber optic versus, like autonomous?FPVs as the New God of War: Tanks, Artillery, and Cost per KillYaroslav [00:25:07]: For our, for our audience, I actually, I cannot answer that question. Like, it's like I know the answer, but I would not disclose that. But for our audience, I think another interesting fact is out of all the casualties on the front line Between 70 and 80% are done by FPV drones.Brandon [00:25:30]: FPV drones are the new weapon of universal weapon of warfare.Yaroslav [00:25:34]: It'sBrandon [00:25:35]: Land warfare, anywayYaroslav [00:25:35]: They used to say that artillery is a god of war because artillery used to cause, like 80% of casualties, and now On that ranking-Brandon [00:25:46]: FPVYaroslav [00:25:47]: FPV drones rule.Brandon [00:25:48]: FPV drones are the god of war.Yaroslav [00:25:51]: Sort of. Dethroned artillery. But it's not to say that artillery is not useful, is not needed. Like, all of these systems are needed. Maybe except cavalry, although Russians still use it. I know, have you seen the videos of Russians using mules and horses?Brandon [00:26:09]: What is the usefulness-Yaroslav [00:26:10]: It'Brandon [00:26:10]: Of a tank in the in the modern-Yaroslav [00:26:11]: That's where we need Greenpeace to say a word, but they're silent. Yeah.Brandon [00:26:15]: What's the use of a tank on the modern battlefield?Yaroslav [00:26:21]: It's diminishing.Brandon [00:26:22]: Diminishing.Yaroslav [00:26:22]: However, I think there might be technologies which will, revive the tank. Look, tank still provides you armor, and armor is important. Like, you still need to armor and firepower, right? Like, you can be an armor personal carrier that provides you, armor. The challenge that currently exists is armor is not very well protected against incoming drones. However, there are ways to do to protect it. We were previously talking about this before the podcast. The CEO of Rheinmetall, recently sort of ridiculed, Ukrainian drone industry, saying that like, there is nothing interesting there, no real innovation, no to stand Compared to like, Rheinmetall or Boeing, and it's all made by housewives. There was like, obviously a ton of memes about this people ridiculing the CEO of Rheinmetall. And one of the best quotes, I heard on this topic is from my friend, Alexey Babenko, who's, the head of and founder of VIARI Drone, which is one of the largest manufacturers of FPV drones. They're our partner. They're using our autonomy. So he said that the drones we manufacture in one day will be more than enough to destroy all the tanks Rheinmetall manufactures in a year.Yaroslav [00:27:52]: Then, yeah, cost-wise, of course, a drone is like, $500 and a Rheinmetall tank is what, probably 5 million-ish or maybe more.Brandon [00:28:00]: Don't mess with those housewives.Yaroslav [00:28:03]: Drone wives.Brandon [00:28:04]: Drone wives.Yaroslav [00:28:06]: That's it.Noah [00:28:06]: There's a classic saying that everyone always fights the last war.Noah [00:28:12]: Yet do How did So from your standpoint, how did we get to the point where tanks became irrelevant in at least for now In a matter of just a few years?Yaroslav [00:28:24]: Look, I think it's the same way, how do we get to the point that calculators become irrelevant?Yaroslav [00:28:31]: Now we have iPhones. Like, why would you need a calculator? Technology progresses and its influence grows non-linearly. It's all exponential. So I can tell you that full autonomy, when you put it on a drone Look, so if you, if you think about a tank and a like, it's not a direct comparison, but even, like, a drone and a artillery shell or like, sort of cost per kill, an artillery shell for 155 caliber, which is a standard NATO caliber Currently market price is about $4,000 per piece. So compare that to say, $400 per drone. That's 10 times more expensive. Account for the amortization of the artillery gun and for how vulnerable it is and what is the sort of tactical, capabilities it gives you as compared to a drone. You'll figure out that an FPV drone is maybe three orders of magnitude, more versatile, more useful, more capable than artillery and many of than a classic artillery. Many of Because there are different types of artillery. Not just, like, one 155. You have mortars, you have all that. But give or take, roughly three orders of magnitude maybe. Again, it doesn't have that firepower. It's not one-to-one comparison still.Yaroslav [00:29:53]: Now, take that FPV drone. When you put full autonomy on that FPV drone, which can be not very expensive, like systems that we're, producing are like, in hundreds of dollars of pure bombFull Autonomy: From Human Pilots to Smartphone-Directed Drone MissionsNoah [00:30:06]: Just interrupt. You said full autonomy Just a second ago you were saying that the autonomy here is guidance, right? It's not decision-making.Yaroslav [00:30:14]: No, I was I was saying that's the f-First and sort of easiest pieces of autonomy that was fielded by us. But if you, if you add full autonomy to a droneBrandon [00:30:24]: He, I think he's asking what does it can you, for the listeners, can you explain What the term full autonomy means?Yaroslav [00:30:29]: Basically, I think a good way to think about an FPV drone is like an iPhone of warfare. It's, like, very inexpensive, very mass producible, very versatile. You don't need a bunch of other things when you have a iPhone in your pocket. You don't have, need an MP3 player, you don't need a calculator, don't need other things. All right? So FPV drone is an iPhone. Or like, okay, Apple please don't sue me, is a smartphone. And then, when you add autonomy to it sort of becomes like Uber or ride sharing. Okay? So what it means is instead of actually being a trained pilot who has this complex remote controller device which requires a couple months of training to actually pilot the drone, and then having to pilot it for 30 minutes, flying towards the target, et cetera, et cetera, now you basically, you have your smartphone, you have a drone, you pick your smartphone, you say, “We are here. The bad guys are here. Go and get them.” And the drone goes up, flies in a given direction, localizes itself on the map, finds the dedicated area where they, the bad guys are supposed to be sees the bad guys, bombs them, return, like, watches, so does a damage assessment, returns back, sits down, and then you can pick it up and watch the video if you didn't have the radio link, right?Noah [00:31:59]: That's a bomber drone.Yaroslav [00:32:00]: That's full autonomy for a bomber drone, right?Noah [00:32:03]: You're saying that no human decision is made in this entire process?Brandon [00:32:06]: That's not, that's not what he's saying.Yaroslav [00:32:07]: A human decision was made at the beginning of the process-Noah [00:32:09]: I get it. I get itYaroslav [00:32:09]: The same way as you would fire an artillery.Yaroslav [00:32:12]: When you fire an artillery, you don't stop at like, 500 meters away from a target and ask it whether, you want to strike or not. That's exactly, a human decision is always made at some point. So when you do that's full autonomy, and such full autonomy is happening as we speak. And such full autonomy increases the capabilities of an FPV drone, which is already, like, three orders more powerful than an artillery shell. Full autonomy increases its capabilities by four orders of magnitude because now you can have 100 times as many people who can use it, because you don't need to train those people, and this is important. You can have 10 times, mission success rate, and you can have 10 times utility per drone because now instead of being one-way kamikaze, it's, it can be a bomber.Brandon [00:33:05]: Now wait, let's, you said 10 times mission success rate, which means that fully autonomous bomber drones succeed in their missions 10 times more often than human piloted bomber drones do. That's an important thing to know.Noah [00:33:17]: Maybe, to push back onBrandon [00:33:19]: They're super, they're superhuman. They're, they' 10X superhuman.Yaroslav [00:33:22]: They're not vulnerable to electronic warfare. They don't care about the radio horizon. They don't lose track during navigation. They are not susceptible to human error when, an artillery shell or other drone blows up besides you and you're like, “Hell no,”like, “I'm getting out of here.” Right? That doesn't happen to an autonomous drone. Like, all of those things. Like, we have, like, one of the brigades that's using our drones with just first level autonomy They literally said that their success rates-Brandon [00:33:53]: What's first level autonomy?Yaroslav [00:33:54]: First level autonomy is just the terminal guidance.Yaroslav [00:33:57]: By the way, we have video of that. We can watch that.Brandon [00:33:59]: Terminal guidance means a human gets it nearby and then the AI takes over.Yaroslav [00:34:03]: The human flies it all the way, like 30 kilometers towards the target, and obviously the target was probably given to that human by someone who's flying some ISR drone, some reconnaissance drone, right? So all the way to the target, and once you see the target from a distance of 500 meters, you do target lock, and from there drone flies autonomous. So just that feature alone, it has increased the guy's, his call sign is Grom, so it has increased his, mission success rate, like precision of mission, yeah, mission success rate from 20% to 71%, and it also increased his kill zone from three kilometers to 10 kilometers, which means there's certain area around the front line which is designated kill zone. Whenever enemy goes into that area, it's almost guaranteed to be to be destroyed by a drone. And then obviously the drones are not launched from like, the zero line. They're usually launched from like, minus 10 kilometer-Mission Success, Failure Modes, and the Five Levels of AutonomyBrandon [00:35:03]: What is a zero line?Yaroslav [00:35:05]: Zero line is sort of an imaginary line of control, of two conflicting forces.Brandon [00:35:14]: It's important to explain these things to a lot of the listeners who areYaroslav [00:35:17]: Thank you for askingBrandon [00:35:18]: Familiar with warfare.Noah [00:35:20]: Myself.Noah [00:35:20]: I'm one of those listeners.Brandon [00:35:20]: You said that level one autonomy, in other words just terminal guidance, just, like, human gets it to the finish line and then it goes over the finish line, increases mission success from 20 something percent to 71%, or something like that.Yaroslav [00:35:33]: Increases the kill zoneBrandon [00:35:34]: Increases the kill zoneYaroslav [00:35:34]: Three kilometers to 10 kilometers.Brandon [00:35:36]: Got it.Yaroslav [00:35:36]: On both parameters-Brandon [00:35:37]: What is full autonomy, dude? AndNoah [00:35:38]: Actually on real quick, can we define mission success and like, maybe in a way, what are the failure modes of missions?Brandon [00:35:44]: I have a guess what mission success is.Noah [00:35:46]: But I couldBrandon [00:35:47]: Get ‘em.Yaroslav [00:35:49]: No, but that's a very good question, in fact, because, even if you fly into the target, well, first the target can be damaged or destroyed. Those are two different modes. Then there can be different targets. A sole infantryman is one kind of target. A dugout where supposed there are some, enemies there is another kind of target, and a some mechanical equipment is another type of target. Radio emitting equipment, which, like, often, like, the targets that the military want to get more than anything else is the some enemy radio tower or something like that or some small radio dish that really makes life difficult in that area, in that combat area. So those are different targets, right? It can be destroyed, can be damaged.Then sometimes, the drone hits but doesn't explode. Like, that happens. And then, there are other failure modes. You didn't even reach the target because you were A jammed by electronic warfare; B, you lost the control over drone because of the radio horizon; C, you were jammed by a different type of electronic warfare that happens way before You hit the target area. It's, impacting your, video receiver. So like jamming on video or jamming on control are two different types of jamming. Then something malfunctioned on a drone, just a mechanical malfunction, maybe like a motor broke or like, whatever. So all of those are different failure modes. Yeah, or maybe you got lost, you're navigate navigating to your, to your target. That happens, too.Noah [00:37:41]: The Level one autonomy, basically you manage to point in a direction.Noah [00:37:49]: You go there, and then the last mile The drone taking over.Yaroslav [00:37:52]: We define this like, I define that but it sort of got picked up by the industry. We define five levels of autonomy. So level one is terminal guidance. It's what we just discussed. Level two is bombing. Level three is autonomous target detection and engagement decision. Level four is autonomous navigation. And level five is autonomous takeoff and landing.Noah [00:38:15]: Those are good things to knowYaroslav [00:38:16]: Those are five levels of autonomy. Now, if youNoah [00:38:19]: I have a question for you.Yaroslav [00:38:19]: Sorry. Like, let me finish withNoah [00:38:21]: SorryYaroslav [00:38:21]: Theoretical part.Noah [00:38:23]: What is Tesla running at right now?Yaroslav [00:38:25]: Tesla?Noah [00:38:25]: No, sorry.Yaroslav [00:38:26]: That's very good point. Like, it's exactly, it was inspired by the levels of self-driving autonomy.Noah [00:38:32]: Waymo's level five, right?Noah [00:38:35]: You just tell it where you want to go, it picks you up, and then you go there.Yaroslav [00:38:36]: I think, like, if you, if you look at the classic definitions of self-driving cars, Waymo is still, like, level four because it still requires even remote, but still, like, human control. It's like if Waymo gets in trouble, there is an operator who takes over and resolves this. So that would still be a level four. It doesn't map directly, but it's also five levels.Brandon [00:38:58]: Can I, can I interject a question here? In terms of an FPV drone that's like a suicide drone that'll just blow itself up killing something, how do what it hit? Like, does it, just transmit back, or do you sort of like, lose track of it and hope it hit? Like, what happens to that?Yaroslav [00:39:16]: That's a great question. SoBrandon [00:39:18]: You need another droneYaroslav [00:39:19]: Like, the current battlefield in Ukraine is saturated with different types of drones. So obviously you have all the FPV drones and last year alone, Ukraine manufactured about 4 million of these, and then Russia's maybe, like, 20% less than that. And for this year, the publicly voiced target was 7 million on Ukrainian side. So it's, like, serious numbers. We're getting in serious numbers here. And then besides those, there are different, reconnaissance drones, ISR as we call them, and there are sort of tactical level ISR where we, both Ukrainians and Russians usually use, Mavic, drone by DJI. And then there are a bunch of locally produced drones, which are sort of fixed wing drones that can stay in the air for much longer than Mavic, maybe, like, half an hour. And then, there are drones that can stay for many hours or even up to a day. And those drones have, are more expensive, have more expensive cameras, et cetera, et cetera. We hunt those drones that Russians launch. The Russians hunt our drones, and so on. But ideally, when you, are a group of soldiers operating an FPV, you'll have someone in your, company, or someone in your platoon who has an ISR asset that will do target designation for you. They'll say, “Oh, like, there's a Russian vehicle over there. Go and get him.”and you go there, you get it, and they're like, “Okay, confirmed.”Battlefield Surveillance and the Eight Dimensions of AutonomyBrandon [00:40:57]: Those guys are watching. They have their own drones in the sky.Yaroslav [00:40:59]: Target destroyed. They have, like, a carousel of drones because One Mavic cannot stay more than 30 minutes. ItBrandon [00:41:06]: They're constantly surveilling the battlefield.Yaroslav [00:41:07]: Almost every spot on the battlefield.Yaroslav [00:41:11]: It's not always the case. Sometimes you will not have a surveillance asset, so then you would launch another FPV just to confirm that there was a hit. Then if you see there was a hit and you're not sure if it completely destroyed, you maybe hit again for good measure.Brandon [00:41:26]: You double tap.Yaroslav [00:41:28]: That's how it works. But I was about to give you another sort of piece of taxonomy. So you have five levels of autonomy, right? Then you have sort of eight dimensions of autonomous battlefield. So what is eight dimensions? It's crucial to understand how autonomy evolves in a modern, battlefield environment. So dimension number one is level of autonomy. What are the capabilities that your asset has? Dimension number two is the platform you're operating on. So it can be a quadcopter, a fixed wing drone, different types of maybe, like, a long range drone or short range drone, but it can also be a missile. You can have autonomy even on an artillery shell or a ground vehicle or a sea vehicle. So all of those are different platforms. Level three would be domain. So it's ground to ground or ground to air as an intersection, or ground to sea or sea to air. They're all, like, all the nuances with different domains. Then level four, would be higher levels of autonomy, such as swarming, drone carriers, drone nests, et cetera.Brandon [00:42:39]: Now when you're saying level, you're talking about dimensions, not about-Yaroslav [00:42:42]: Sorry. YeahBrandon [00:42:43]: Autonomy levels. So dimension four.Yaroslav [00:42:43]: The dimension. Yeah, I used to say I was supposed to say dimension. I say dimension because each of them works with another, right? So you might have, like third level autonomy, fixed wing drone operating in land to air, and stuff like that right? And then operating in a swarm or operating from a nest. Right? Then you have, sort of dimension number five is environment. So is it day or night? Is it summer or winter? Is it, humid, cold, dry? What kind of target is it? Is your target hiding in a forest, or is it, behind a hill or within buildings? So all of that is environment. Then you have, dimension number six is command and control. How are you dealing with or like, tens of thousands of those assets around the battlefield? How are you coordinating that on the higher levels of command? How are you collecting data? All that.Yaroslav [00:43:44]: Dimension number seven would be infrastructure, so things like simulation, data collection tools, security, deployment mechanisms, et cetera. So all those systems have to be developed separately and integrate with all the others. And finally, dimension number eight is sort of distribution. Have you deployed 100 of these systems or 100,000 of these systems? Because those are two very different ballgames. So that now gives you a more broad overview of how autonomy propagates across the battle space.Targeting, Human Responsibility, and Rules of EngagementNoah [00:44:23]: As someone who has done machine learning and had gone out of distribution and had things, go horribly wrong, you were talking several of these, kind of axes of thinking about drone warfare seem like they could be very susceptible to some sort of distribution shift if you start making things autonomous.Yaroslav [00:44:41]: Like what?Noah [00:44:41]: I mean Well, first ofYaroslav [00:44:43]: If the I'm very interested Sort of sort of kinds of scenarios that you're thinking about.Noah [00:44:48]: Like the most obvious one is you, if I assume these are computer vision guided systems for at least the last mile, how do you ensure that oh, well, like you now have some fog roll in or something, and you, the drones just attack the wrong thing? Or maybe, it probably will not turn around and fly back and attack you, but youYaroslav [00:45:10]: Same, the same, the same question, how do you ensure that your mortar fire hits the right thing? Well, it's like mortar fire, give or take half a kilometer could be plus or minus. So maybe you fire one, and then you fire another. So drones are actually, much better in being precise in those scenarios. And I think, to your point, I think five to 10 years from now it will be immoral to use weapons without AI.Yaroslav [00:45:44]: ‘Cause weapons without AI will be more likely to cause, collateral damage or unwanted damage. Same way, it will be immoral to drive your own car manually on a public road because it's more likely to cause, unwanted damage.Noah [00:46:02]: Wow, I never considered that mightBrandon [00:46:04]: Really? That's definitely coming.Yaroslav [00:46:07]: Anyway.Brandon [00:46:07]: No, but that' I don't know, it's an obvious, an obvious thought. I agree with you.Brandon [00:46:12]: I, No, they, obviously they're not going to let you drive once most of the cars on the road are autonomous.Noah [00:46:17]: No, that one, don't I believe.Yaroslav [00:46:19]: No, I think you were you were talking about drones, right?Brandon [00:46:21]: The drones, right. Cool.Yaroslav [00:46:22]: The weapons, right?Brandon [00:46:23]: Friendly fire and collateral damage and stuff like that is all minimized with AI.Brandon [00:46:27]: Here's my question. Take all let's go to level six autonomy. Let's take all of the target selection. Let's take all the battlefield data, integrate it into one big AI, and have that big AI basically be in command of the battlefield And agentically do target selection.Yaroslav [00:46:44]: Be the general, right?Brandon [00:46:44]: It's a general. It's, you've cut humans out of the loop except maybe as dexterous robots, repairing drones and fastening things to drones or maybe something like that because you don't have those robots yet. How soon are we there? AI general.Yaroslav [00:46:58]: The most important thing to ask ourselves is who will be faster to that us or our adversaries?Brandon [00:47:07]: I assume us, but how fast will we be to that? I hope us.Yaroslav [00:47:11]: I hope so too.Brandon [00:47:12]: How fast can we Like when are we looking at that in terms of like horizons years?Yaroslav [00:47:18]: Like technically, it could be done now. The question is of course, there's, some engineering work to be done. The bigger challenge is deployment. Right? So okay, technically Like operation in Iran, right? They, the publicly, it was claimed that I think Palantir system was used for target designation, et cetera, et cetera. So it is not exactly as you say, the AI makes all the decisions, but basically AI goes through all the data you have, gives you these 1,027 different targets and says, “You-- To confirm, please press Okay.” And you look at the targets and you're like, “Yeah, sounds right. Press Okay.”so that's, I think that's where we are now already, or we were a couple weeks ago as we're recording this on April 10th. Another question is how massively deployable it is. Is it, like, every decision being made like that or is it, like, just some of the decisions made like that? And then different levels of command and control. There you have, like, the platoon, the company level, the battalion, et cetera, et cetera, et cetera. But the tricky thing here when we get into that territory, the tricky thing is If your enemy is getting advantage of being Thousand times faster than yourself by deploying such systems What do you do?Yaroslav [00:49:10]: You got to-Brandon [00:49:12]: The if the enemy is a thousand times faster than you at deploying those systems?Yaroslav [00:49:16]: Like, if enemy starts deploying level six autonomy, as you call And you have not started doingBrandon [00:49:22]: You're in troubleYaroslav [00:49:23]: Yes, exactly. So you have to catch up. So my point is that it is very important to think about the safety of these systems, but that thinking should not slow you down in developing them because they are critical for your existential, survival, right? And like, one person who doesn't think, doesn't get to think about the ethics of the war is a dead person. That person surely doesn't get to think about that.Brandon [00:49:52]: What would be the safety risk of such a system?Yaroslav [00:49:55]: Of course-Brandon [00:49:56]: Friendly fire?Yaroslav [00:49:56]: Just wrong decisions, right?Brandon [00:49:59]: I see.Yaroslav [00:49:59]: Maybe, these decisions-AI Command Decisions, Dead Zones, and Complex BattlefieldsBrandon [00:50:06]: Skynet AI decides it's going to useYaroslav [00:50:08]: No, these-Brandon [00:50:08]: Drone army to kill usYaroslav [00:50:09]: Decisions will not only be made about drones. They are likely to made about what the humans should do on your side as well. Then obviously some environments are more like Ukrainian-Russian war, where you haveBrandon [00:50:26]: It will have to choose to risk lives. It will have to choose to sacrifice human lives-Yaroslav [00:50:28]: Of courseBrandon [00:50:29]: On your side.Yaroslav [00:50:29]: Of course. And then some environments are just, like, dead, like, dead zones and there are no civilians there, or virtually no civilians close to the front line because, like, super dangerous. Everyone has evacuated from there. But there are other environments which are more like, okay, there's a counterterrorist operation. There's, like, a group of terrorists or a group of civilians. Or like, it's like the recent operations in Iran, I imagine that the US and Israeli forces do not want to harm civilians. They only targeted the military targets there, right? So in those situations, it's a different level of responsibility for that decision-making as well. And then there is just such a big variety of those military missions, and I'm not even, like, well-informed or well-educated in military science to tell you about all those scenarios. We would need to put some general besides me, and maybe a Ukraine general and American general would have told you very different stories about these things.Brandon [00:51:34]: Got it. Can I ask a few more questions? All right. So in 2013, I wrote one of my first, paid articles ever was about how the era of drones will change human society. I was just sitting around bored thinking about things.Yaroslav [00:51:54]: You were way ahead of your time.Brandon [00:51:55]: I said, I said, “The following will happen.”Yaroslav [00:51:57]: It's, this article is real. I've read it.Yaroslav [00:51:58]: It's actually-Brandon [00:51:59]: I said small autonomous, suicide drones, will cleanse the battlefield of human infantry. Human infantry will not be able to stand against swarms of AI-powered, suicide drones. That was I didn't even know about, like, AlexNet at the time, I think.Yaroslav [00:52:19]: You're just an avid sci-fi reader.Brandon [00:52:23]: I'm an avid sci-fi reader, but also, like, it's not Like, there will be a way to do that. It's a it's a nonlinear multidimensional search problem, and you get enough compute, you'll find some search algorithm that will get you there. And soBrandon [00:52:38]: I, yeah, I think that one sentence describes the bitter lesson right there.Brandon [00:52:41]: It's just like it's a multidimensional search space. You search it somehow. I don't know. Figure out some get a grad student-Yaroslav [00:52:47]: Sooner or laterBrandon [00:52:47]: To make a search algorithm.Brandon [00:52:48]: It's not that hard. Anyway, so but then, but I guess the point is The point is that human infantry on the battlefield will be will be gone at the end. I wrote that in 2013. Many people on social media laughed at me for that called me hysterical, said things like, “Electronic warfare will knock all the drones out of the sky.”like, “You need humans to hold ground.”that's something you still hear from a lot of people on social media today. I feel that this article that I've written has never been directionally wrong. It has gotten more and more right steadily over time, and that we're very reading the battlefield reports from Ukraine, where, human infantry are basically guy, like a few guys hiding in dugouts for months, and I'm not sure what they're doing.Yaroslav [00:53:35]: That's on Ukraine's side. On the Russian side, that's just like a zerg rush.Brandon [00:53:38]: The zerg rush, and then they just die. Then, but they have some guys in dugouts too, right? Like hiding in dugouts for months.Yaroslav [00:53:45]: They have. Yeah.Brandon [00:53:45]: Like, but that like, what are those guys doing in the dugouts? Are providing, like, frontline, like, reconnaissance? Like, what are they doing?Yaroslav [00:53:54]: If there is a guy in a dugout with some bullets and automatic weapon, the other guy cannot come and take the that dugout. That'Brandon [00:54:07]: I seeYaroslav [00:54:08]: They are they're establishing control over territory.Brandon [00:54:10]: I see. So that is so there still is a use for human infantry on the battlefield as of today.Yaroslav [00:54:15]: LikeBrandon [00:54:15]: How long will that last?Yaroslav [00:54:17]: I think it will last for a while. This is funny. There's this whole Layer of the modern culture, a modern Ukraine culture built around the war-related stuff. So there is this -Punk rock band, that is called SZC, I guess in English that would be. Which stands short for like a deserter or something like that. So anyhow, this band has a song titled “2030.” It's basically about the year 2030, and the war still goes on as like the whatever, third world war or whatever. And they basically, they, sang about the AI and like cyborgs and everything, but the simple infantry is still needed, and we're still, like, getting cold in those dugouts, and we're still doing our job. That's sort of the theme of the song. And it seems like that's actually what's going to happen. There areGround Robots, Simulation, and the Limits of World ModelsBrandon [00:55:30]: Ground robots will not replace humans in the dugouts soon.Yaroslav [00:55:34]: I'm very much interested in following the whole humanoid robot theme andBrandon [00:55:39]: What about like a dog robot?Noah [00:55:41]: Or just mobile controlled platforms or something.Brandon [00:55:44]: Spider robot, yeah.Brandon [00:55:45]: Everything evolves into a crab.Brandon [00:55:46]: You build a crab robot.Yaroslav [00:55:47]: A humanoid-Noah [00:55:48]: The carcinization of warfare.Yaroslav [00:55:51]: There is a lot of utility in humanoid robots because the world is designed around humanoids. So I would not, like, 100% disqualify the possibility that sometimes 10 years in the future, humanoid robots, will be actually fighting. So that's an actual Terminator kind of scenario.Brandon [00:56:14]: Yeah, in the first Terminator movie, you look at what they've got on the battlefield, they've got flying bomber drones and humanoid robots.Yaroslav [00:56:20]: Look, the cost of large language models of running them is getting so low, you can have basically an inexpensive computer running, what was a state-of-the-art model a year and a half ago, running it locally on a device with an open source model, which also means that the Chinese can have it, the Russians can have it, the North Koreans can have it, et cetera. So that is already possible. And with when we're looking at the acceleration of the neural nets, I would've, if not the acceleration of the large language models, I would've said that I don't think that humanoid robots will be able to be useful in the battlefield earlier than in 10 years. But if you account for the exponential, it might be five years or so. The problem with all of the autonomous systems, and it's like starts with self-driving cars and even with all the AI, like modern day AI agents, to make them really, useful, you have to solve such a long tail of edge cases, that it's really difficult to make them useful. Like we were promised, self-driving cars, what, like 2007, Sebastian Thrun and Google, and even before that all the challenges, everything. And Elon of course told us it's going to be one year from 2014, and now we still don't have self-driving Teslas everywhere. We have Waymos in SF and some other places, but they're still, like, not perfect. So I think, I expect something similar from self-flying drones and fully autonomous drones, and we saw that firsthand as with each level of autonomy that we're adding, there is a very wide distance between a prototype and something that is ready to be scaled to millions of units and something that has been scaled to millions of units. But the race with like AI coding tools is just insane. So things might accelerate very fast, faster than we can imagine.Noah [00:58:46]: I think your point is that with due to this long tail behavior Level one autonomy as you've defined it, is actually very natural. Like you basically are just solving an image recognition and tracking system.Yaroslav [00:59:02]: It's actually interesting that you say it that way, and I thought about this the very same way, and we have this joke that there are like 200 companies in Ukraine which are trying to solve last mile, targeting or terminal guidance. It seems like we're like the only company that actually solved that because even that problem-Noah [00:59:22]: I'm not saying it's, I'm not saying it's trivial, but it's at least something that you imagine given our current state.Yaroslav [00:59:26]: Like us and Eric Schmidt, like Eric Schmidt's companies are pretty good.Yaroslav [00:59:29]: Like, I actually have lots of respect to what they're doing, and they're, they have been practically influential and helpful on the battlefield, and they have good engineering.Noah [00:59:38]: I wasn't, I wasn't saying it's trivial. I'm just saying this is a something naturally adaptive based upon things that we know work, well. But some of the other domains that where you do have to make decisions and you have a long tail become much harder, and you worry about edge cases more.Yaroslav [00:59:57]: Like the more, the more complex behavior you're trying to simulate, the more edge cases there are right? The more ways to do it wrong there are. And then there are different approaches. It's like if you think about, if you read academic papers about robotics, right? You sort of the robot is represented as something that has the sort of sensor input, and then you have three, levels of sort of logics or decision-making, which are perception, planning, and control, and then you have actuators as output.So pre-neural nets, you would do perception output and control all with classic logics, right? Then, with AlexNet and computer vision, you could do perception with neural nets and the rest with logic. You cannot currently do each of those separately with neural nets, each of those separately with logics, or you can just have one huge neural net that just takes lots of sensory data. It's not just pixels. Could be sound, could be accelerometer, could be everything, as input, and just outputs the controls. And some of the self-driving car companies are doing that or like, experimenting between different ways of doing that. So you can also, like, think about that and the way you implement those features, also influences how much degrees of freedom the system would have, right? Like control, you can do it classical algorithmic control with common filters and PAD filter, PAD controllers, et cetera, or you can do a neural net, that was trained in a gym with a reinforcement learning, et cetera. And those would be two different behaviors of a system.Noah [01:01:53]: I-- Maybe my point was just much more high level. It'Yaroslav [01:01:56]: Or you can If you go even like, if you go high level, you can, you can like train to like have whatever, like Feifei Li and folks who are doing like physical, sortBrandon [01:02:08]: World modelsYaroslav [01:02:08]: World models, right, physical intelligence, they're trying to make these big models and sort of understand the world and then supposedly you have such model and you can tell a drone, “Okay, like, go over that hill and like, find the bad guys and then get them,”or “Make me a video, make me a photo of the guy smiling and get back to me.” Right? That's one way. Another way you have like these subsystems, like one is navigation, another is finding the person, another is like getting to them to take a photo. And those are again, very different behaviors. And then it's not that one is necessarily better than the other, and we might have more technological ability to do one or another. But all of those systems will exist. And then again, you should always keep in mind that it's only the not only the good guys that are developing these systems, the bad guys are developing these systems as well.China's Drone Supply Chain and the West's Manufacturing GapNoah [01:03:00]: I guess where I'm going with this back to Noah's original thought with the end of the end of the soldier. And so in order to replace-Brandon [01:03:10]: Or at least the end of the rifleman.Noah [01:03:11]: Or the end of the rifleman, yeah.Yaroslav [01:03:13]: I'm not seeing that very close, and it was like I'm, as much as I'm a lover of sci-fi and all of that and a technologist, the more I try to beYaroslav [01:03:27]: Like the I try to have certain humility about these things, and like the military, domain and there was just so much human history and blood and tears, dedicated to sort of understanding this art of war and perfecting it and so on. There is so much knowledge in there that I don't feel like I even started to comprehend, a lot of that. But one thing that I really understood is that even though drones are now making eighty percent of the casualties, you go to the actual officers, you talk to the actual, like, brigade commanders, corps commanders, and they explain to you, how all of it fits together, how when you're thinking about an operation that involves a couple thousand people to get this piece of land, out of the enemy's hands, deoccu deoccupy it, how it is so complex, it involves, dozens of different types of drones and then land operations and reconnaissance operations, psychological operations and then aviations and tanks and logistics and all kinds of these different assets. So modern warfare is really very complex, and the fact that the drones are the latest, coolest thing, and then the AI is latest, coolest thing, doesn't mean that now it's that and only that right? So yeah. Whoever's looking into that I think should realize that it's not just what the press talks about, that the reality is much more difficult, much more complex.Brandon [01:05:17]: Let's talk about China and China's manufacturing capabilities. So suppose that someone, like suppose the United States went to war with China. AndYaroslav [01:05:26]: I hope not.Brandon [01:05:27]: I hope not as well. And then but suppose that drones were very essential to that war of all the types of drones that we're talking about here, and that suppose that China said, “All right, well, you need X and Y and Z, to make those drones to fight us, and we control the production of X and Y and Z, so we're just going to cut you right off, and now you have no drones.”Brandon [01:05:47]: I know that a number of countries, including Ukraine and Taiwan, have been making moves to China-proof their drone productions that China couldn't do that. Examples of things they might be able to cut off might include rare earths, fiber optic cable that you were talking about before, various other things that where even if they don't control one hundred percent of the production, they control enough of the production that would be extremely expensive to produce it without relying on Chinese sources. Or the market's fragmented enough, et cetera. What do you see as China's key bottlenecks, and how easy are those to overcome in terms of China-proofing drone production in case of a war against China?Yaroslav [01:06:30]: Let me start with a saying that -Although China does not sell directly to Ukraine and it does sell directly to Russia, a lot of Ukrainian supply chains, they start in China, right?Yaroslav [01:06:49]: We're not in a conflict with China, and we would not want to be in a conflict with China. And we'd hope that China stays a neutral power between Ukraine and Russia and the US as well. That said, the scenario that you're describing, everything is much worse.Yaroslav [01:07:11]: Think about this. Last year, Ukraine produced four million FPV drones. Ukraine is not the most industrious nation in the world.Yaroslav [01:07:19]: China can produce four billion of these FPV drones.Yaroslav [01:07:23]: China can make them not drones with propellers, but fixed-wing drones, which go not forty kilometers far, but maybe two to three hundred kilometers inland.

The Layer 8 Conference will have a full scope social engineering capture the flag (CTF) competition this year. This is an event that has been created by John Costa and Jordan Saleh. In this episode, we hear from John and Jordan about their experience in creating CTFs and their thought process in building this one. If you're interested in being a social engineer or love CTF competitions, you'll want to be at the Layer 8 Conference and compete in this event!

Something just changed. Most people still think Flare is a side ecosystem to XRP. Tonight we explain why that narrative may already be obsolete. Because Flare is no longer moving like a speculative Layer 1. It's starting to look like infrastructure. And this is where it gets interesting… While most of crypto is still chasing hype cycles and price candles, Flare just activated a completely different conversation: • value capture • programmable liquidity • XRPFi • AI-driven finance • smart accounts • autonomous settlement • network revenue infrastructure Now connect that to XRP. Now connect that to tokenized finance. Now connect that to AI agents moving toward autonomous economic coordination. That's not a coincidence. FIP.16 changes the game because it shifts Flare from emissions-first tokenomics… into a system capable of routing, capturing, burning, and reinvesting value back into the ecosystem itself. Not hype. Mechanics. The flywheel may have just turned on. Meanwhile the legacy system continues showing cracks: • collapsing institutional trust • geopolitical instability • rising populist movements • centralized financial pressure • global liquidity fragmentation And underneath all of it… new infrastructure is quietly going live. This changes the conversation completely. In tonight's episode of On The Chain, Jeff and Chip break down: • Why FIP.16 could become a major turning point for FLR • The shift from speculation → infrastructure • Why XRPFi matters more than most people realize • AI agents and programmable finance • Institutional liquidity rails and value routing • The hidden transition happening underneath the financial system • Why the “Too Late?” narrative is starting to emerge ━━━━━━━━━━━━━━

The conversation covers the agenda items for DevNet 4, including EIPs 70, 71, and 72, as well as the impact of the Engine API change on gas limit. It also discusses the limitation of deposit transactions on the EIA side, benchmarking and testing with Prism and Teku, and potential solutions for an overflow issue. The conversation covers the introduction of optional proofs for execution, collaboration with the broader community, sub-linear and stateless validation, opt-in proof generating and verifying modes, infrastructure and observability improvements, and standardizing the input for guest program execution. The discussion is divided into three main chapters: Introduction to Optional Proofs, Execution Proof Engine and API, and Execution Layer Specification.TakeawaysDevNet 4 includes EIPs 70, 71, and 72Discussion on Engine API change and its impact on gas limitLimiting the number of deposit transactions on the EIA sideBenchmarking and testing with Prism and TekuOverflow issue and potential solutions Optional proofs for executionCollaboration with the broader communitySub-linear and stateless validationOpt-in proof generating and verifying modesInfrastructure and observability improvementsStandardizing the input for guest program executionChapters00:00 DevNet 4 Agenda Items13:21 Engine API Change and Gas Limit39:22 Deposit Transactions Limit45:03 Overflow Issue and Solutions54:54 Execution Proof Engine and API01:23:15 Execution Layer Specification

Roberto shares notes from the course and what to watch for as the PGA Championship gets started, then talks with Kaitlyn Nelson about what the data is revealing from the early-week fan experience. Kaitlyn explains the tech stack, how the team connected various data sets, and the value that creates for the PGA of America, fans, sponsors, vendors, and more. Plus, predictions.

Two posts, same week, same effort. One hit 50,000+ impressions with zero pipeline. The other reached 800 people and closed €60K. If you measure them with the same metric, you'll write ten more of the wrong one.In this episode, I lay out the 6-Stage B2B Marketing ROI Framework I use with Microsoft, Marsh McLennan, Delta Holding, and 120+ other B2B companies — and why most teams are running 2012 e-commerce attribution on 2026 enterprise sales cycles.Inside:- Why attribution fails in B2B and what to do about it- Kill the MQL: the Inquiry / Opportunity rebuild that dropped leads 60% and lifted pipeline 40%- The 6 stages: Revenue, Pipeline, Active Focus, Future Pipeline, Cluster ICP, Brand- The software client one week from being shut down — and the €1.4M pipeline that was already building- Why LinkedIn reach dropped 50% YoY and pipeline still went up- ICP Density as the moat, and how to measure it with zero new tools- Q1 2026 search data: Reddit at #2, Wikipedia surging, where AI search actually sits- The 3 rituals that replace 80% of an enterprise marketing intel platform- Diagnostic for finding the one stage that's leaking- A 90-day starterThe best measurement isn't more granular attribution. It's measuring the right system at every stage with the right leading indicators.Everything else is data theater.More: funky.enterprises

Patch Tuesday. Global agencies update SBOM guidance. Iran-linked espionage group Seedworm breached a major South Korean electronics manufacturer. A telehealth platform breach affects 716,000. Foxconn confirms a cyberattack. Maria Varmazis has an update on orbital data centers. A lawmaker questions surveillance pricing. Brandon Karpf, friend of the show, is talking with Dave about "Japan's space systems face growing cybersecurity threats." Robotic lawnmowers on the cutting edge. Remember to leave us a 5-star rating and review in your favorite podcast app. Miss an episode? Sign-up for our daily intelligence roundup, Daily Briefing, and you'll never miss a beat. And be sure to follow CyberWire Daily on LinkedIn. CyberWire Guest Today Brandon Karpf, friend of the show, is talking with Dave about "Japan's space systems face growing cybersecurity threats." Selected Reading Microsoft Fixes 17 Critical Flaws in May Patch Tuesday (Infosecurity Magazine) Microsoft Patches Critical Zero-Click Outlook Vulnerability Threatening Enterprises (SecurityWeek) Adobe Patches 52 Vulnerabilities in 10 Products (SecurityWeek) Fortinet, Ivanti Patch Critical Vulnerabilities (SecurityWeek) Chipmaker Patch Tuesday: Intel and AMD   70 Vulnerabilities (SecurityWeek) ICS Patch Tuesday: New Security Advisories From Siemens, Schneider, CISA (SecurityWeek) Global Cyber Agencies Issue New SBOMs for AI Guidance to Tackle AI Supply Chain Risks (Infosecurity Magazine) Seedworm: Iran-Linked Hackers Breached Korean Electronics Maker in Global Spying Campaign (SECURITY.COM) 716,000 Impacted by OpenLoop Health Data Breach (SecurityWeek) Foxconn confirms cyberattack after ransomware crew claims it stole confidential Apple, Nvidia files (The Register) Congressman launches inquiry into how food retailers use surveillance pricing (The Record) Orbital Inference Data Center Bets On Space GPUs (IEEE Spectrum) Cowboy Space raises $275 million to launch AI data centers on brand-new rocket (Space.com) Yarbo responds to robot flaws that could mow down their owners (Malwarebytes) Share your feedback. What do you think about CyberWire Daily? Please take a few minutes to share your thoughts with us by completing our brief listener survey. Thank you for helping us continue to improve our show. Want to hear your company in the show? N2K CyberWire helps you reach the industry's most influential leaders and operators, while building visibility, authority, and connectivity across the cybersecurity community. Learn more at sponsor.thecyberwire.com. The CyberWire is a production of N2K Networks, your source for strategic workforce intelligence. © N2K Networks, Inc. Learn more about your ad choices. Visit megaphone.fm/adchoices

Marty sits down with Zach Herbert to discuss how Foundation Devices is building a microkernel operating system to bring Bitcoin-grade security principles to the AI era, why current AI permission layers are fake, and the urgent need to reinvent personal computing before autonomous agents overrun legacy operating systems. Zach on X: https://x.com/zherbert Foundation Devices: https://foundation.xyz/ GitHub: https://github.com/foundation-devices Presentation: https://x.com/OPNEXT2026/status/2052465451804836101 STACK SATS hat: https://tftcmerch.io/ Our newsletter: https://www.tftc.io/bitcoin-brief/ TFTC Elite (Ad-free & Discord): https://www.tftc.io/#/portal/signup/ Discord: https://discord.gg/yHGkvYxdqT Opportunity Cost Extension: https://www.opportunitycost.app/ Shoutout to our sponsors: Bitkey https://bitkey.world/ Aven https://www.aven.com/bitcoin CrowdHealth https://www.joincrowdhealth.com/tftc Unchained https://unchained.com/tftc/ Salt of the Earth: https://drinksote.com/tftc Join the TFTC Movement: Main YT Channel https://www.youtube.com/c/TFTC21/videos Clips YT Channel https://www.youtube.com/channel/UCUQcW3jxfQfEUS8kqR5pJtQ Website https://tftc.io/ Newsletter tftc.io/bitcoin-brief/ Twitter https://twitter.com/tftc21 Instagram https://www.instagram.com/tftc.io/ Nostr https://primal.net/tftc Follow Marty Bent: Twitter https://twitter.com/martybent Nostr https://primal.net/martybent Newsletter https://tftc.io/martys-bent/ Podcast https://www.tftc.io/tag/podcasts/

FREE Self-Scaling Business Workshop: https://getepicsuccess.com/registration-yt WORK With Me: https://getepicsuccess.com/ceo-org If you've ever: Had your team perform great when you're in the room… but standards slip when you step away Felt like your company culture depends on your presence instead of your processes Wondered why "good people" still make decisions differently than you would Tried to scale your team, only to feel like you're still the one holding the standard together This is why. In this episode of the Epic Success Podcast / Scaled CEO Show, I'm breaking down the 3-Layer Culture System that helps your team win the same way — whether you're in the room or not. Because culture doesn't scale when it's just a vibe. It scales when your team has clarity, capability, and a culture strong enough to self-correct without you carrying it every day. Inside This Episode: ● Why "good vibes" cultures break as you grow How founder-led standards drift when they aren't turned into clear systems ● The real reason your team lowers the bar when you're gone Why it's usually not a people problem — it's a clarity, capability, and culture problem ● Layer 1: Clarity How to define what winning looks like so your team isn't guessing ● Why values like "integrity" and "do no harm" aren't obvious How to translate company values into plain-language behaviors your team can actually execute ● Layer 2: Capability Why skill without authority creates task doers, not leaders ● How to put the right people in the right seats The difference between leadership tracks and expert/operator tracks ● Layer 3: Culture How to identify the behaviors you reward, tolerate, and eliminate ● How to build a team that self-selects, self-corrects, and self-recruits So your A-players help protect the standard without everything escalating back to you If You're a Business Owner Who: ● Has a team, but still feels like the culture depends on you ● Notices standards slip when you're not present ● Has great people, but too many decisions still come back to you ● Wants your team to own the mission, not just complete tasks ● Knows your business can't scale if you stay the backup brain and culture bearer This episode will show you exactly what's missing. The Real Shift: You don't need a better culture poster. You need a culture system. When your team knows what winning looks like, has the authority to execute, and understands which behaviors are rewarded, tolerated, or eliminated… they stop guessing. They start owning. And your business can finally grow without depending on your presence every day. Ready to Fix This for Real? Join me live for the Self-Scaling Business Diagnostic, where we: ● Score your CEO, Team, and Profit systems ● Identify where culture and ownership are breaking down ● Map your next 67-day sprint to reclaim time and scale

In this episode, David Edwards, Chief Technology Officer, Relatient, shares how improving connectivity is unlocking innovation, where AI is delivering measurable value today, and why voice AI is transforming patient access and operational efficiency. He also discusses responsible AI adoption in healthcare and the importance of aligning technology with real business problems.This episode is sponsored by Relatient.

Mike & Tommy dive into Databricks Genie and the growing hype around data agents, exploring whether the real challenge is natural language chat or the semantic layer underneath—and what Power BI teams must fix before any AI agent can deliver trusted, governed answers at scale.https://www.advancinganalytics.co.uk/blog/genie-is-a-semantic-layer-problem-not-a-chat-problem-1https://community.fabric.microsoft.com/t5/Fabric-Updates-Blogs/OneLake-catalog-is-now-natively-available-in-Foundry-Generally/ba-p/5178376https://community.fabric.microsoft.com/t5/Fabric-Updates-Blogs/Direct-Lake-on-SQL-with-Fabric-Data-Warehouse/ba-p/5177641https://community.fabric.microsoft.com/t5/Power-BI-Updates-Blog/Modern-Visual-Tooltips-in-Power-BI-Generally-Available/ba-p/5173946Get in touch:Send in your questions or topics you want us to discuss by tweeting to @PowerBITips with the hashtag #empMailbag or submit on the PowerBI.tips Podcast Page.Visit PowerBI.tips: https://powerbi.tips/Watch the episodes live every Tuesday and Thursday morning at 730am CST on YouTube: https://www.youtube.com/powerbitipsSubscribe on Spotify: https://open.spotify.com/show/230fp78XmHHRXTiYICRLVvSubscribe on Apple: https://podcasts.apple.com/us/podcast/explicit-measures-podcast/id1568944083‎Check Out Community Jam: https://jam.powerbi.tipsFollow Mike: https://www.linkedin.com/in/michaelcarlo/Follow Tommy: https://www.linkedin.com/in/tommypuglia/

Kise Shannon is VP of Business Development at Gridmatic, an AI-first power company helping Bitcoin miners and other flexible loads turn energy market volatility into opportunity. Drawing on more than 20 years in the US energy industry – starting in Texas the moment the state deregulated – Kise has built her career across both global energy majors and startups, and now leads Gridmatic's push into the Bitcoin mining vertical from her base in Houston. Why you should listen Most retail electricity providers evolved out of legacy utilities, and it shows: slow innovation, rigid contracts, and pricing models that punish flexibility. Gridmatic was built differently. The company applies foundational AI models – the same forecasting and optimization engine that powers its wholesale trading desk and its battery storage business across ERCOT and CAISO – to the question every miner is trying to answer in real time: when do I run, when do I curtail, and what is my true effective rate? Kise walks Andy through how that AI layer ingests hundreds of thousands of data points to forecast prices down to specific nodal locations, automating the financial trading between day-ahead and real-time markets while the miner stays focused on operations. It's a clear-eyed look at what "AI-powered energy optimization" actually means once you strip away the buzzwords. The conversation then turns to one of the most underdiscussed problems in mining economics: collateral. New mining LLCs have no trade history, which means traditional retail suppliers demand large upfront deposits at exactly the moment a miner is bleeding cash on land, interconnect, containers, and ASICs. Gridmatic has solved this through partnerships with OBM, Synota, and Satoshi Energy's Bitcurrent platform, all of which enable daily settlement in place of monthly invoices. Layer in Strike for Bitcoin-to-USD conversion and miners can effectively pay their power bill in BTC each day without parking working capital as collateral. Kise also explains why contractual flexibility matters more than ever as miners blend ASIC and AI compute on the same site – two very different load profiles requiring very different energy strategies. Kise makes a strong case for why Texas remains the best home for flexible mining despite tightening competition for interconnects. Abundant land, a state government that has actively welcomed the industry, deep renewable penetration, and natural synergies with the oil and gas sector all combine to make ERCOT uniquely suited to flexible loads. More importantly, Bitcoin miners are not just consumers of Texas power – they are critical grid resources, capable of fully shutting down when supply tightens in a way AI data centers (which often demand five-nines uptime) simply cannot. On the AI-versus-Bitcoin debate, Kise sees coexistence rather than replacement: miners with land and interconnects are partnering with AI customers, and new flexible load is still arriving in Texas. The hot take round closes things out with thoughts on a 10-year vision of Gridmatic as "the power company of the future," why every professional should be using AI now rather than fearing it, and a fitting May the 4th nod to The Martian. Supporting links Stabull Finance Gridmatic Andy on Twitter  Brave New Coin on Twitter Brave New Coin If you enjoyed the show please subscribe to the Crypto Conversation and give us a 5-star rating and a positive review in whatever podcast app you are using.

In this episode of the TFTP Podcast, Jason Bassler and Matt Agorist sit down with Allan Paul Roberts. Allan is an author and researcher dedicated to exposing the globalist agenda to deconstruct society. In his latest work, The Globalist Plan to Collapse Everything to Usher in a New World Order—In Their Own Words, he utilizes an innovative multimedia approach—including over 170 QR codes—to provide readers with direct evidence of the strategies being used to centralize global power. The conversation explores the origins of Allan's work, specifically the "revelation" that led him to identify the pillars of American society currently under systematic attack. The conversation pulls no punches, moving from the psychological warfare of "state-as-God" idolatry found in both political parties to the hard reality of the corporate-state panopticon. Roberts provides a "Liberty Perspective" on why the state is obsessed with replacing spiritual sovereignty with political loyalty, particularly in how it manufactures consent for global conflicts. We delve into the mechanics of the modern surveillance state, highlighting the massive 62-square-mile data center and power facility recently approved in Box Elder County, Utah, and its implications for national security and individual privacy. The discussion further examines the dual nature of Artificial Intelligence, weighing its potential for innovation against the risks of ethical erosion and mass surveillance. Turning toward solutions, we discuss the growing "privacy-focused" movement among the younger generation, including the rise of Layer-1 privacy blockchains like Zano, the use of VPNs, and the importance of "tokenization" in a digital economy. Practical steps for personal sovereignty are also covered, such as transitioning to non-tracking mobile devices and using physical privacy safeguards like camera covers. The episode concludes with a powerful call to action for listeners to reclaim their digital and physical independence through informed resistance and community-building. (Length: 1:06:21) Click Here to Support TFTP. Guest Information: Website: AuthorAPRoberts.com  Book: GlobalCollapseBook.com Free Chapter: Read the first chapter here: https://www.globalcollapsebook.com/read X: https://x.com/AuthorAPRoberts IG: https://www.instagram.com/authoraproberts/ Rumble: https://rumble.com/c/TheGlobalistPlan  Zano Privacy Tools: https://intro.zano.org/

If you feel like your body just isn't responding the way it used to, you're not imagining it. Most weight loss advice out there was never designed for women, especially not women navigating hormone changes in their late 30s, 40s, and beyond. The idea that you just need to eat less and move more sounds simple, but for many women, it actually makes things worse. When your body is under constant stress, whether from under-eating, over-exercising, or life in general, it shifts into a state where it holds onto fat instead of letting it go. A big piece of this comes down to hormones. As estrogen levels change, your body becomes less sensitive to insulin, which means it's easier to store fat even if you're eating "healthy." At the same time, muscle mass naturally declines if you're not actively working to maintain it, and that directly impacts your metabolism. Layer in chronic stress and rising cortisol, and now your body is even more resistant to fat loss. You might notice things like stubborn belly weight, low energy, poor recovery from workouts, or waking up in the middle of the night. These are all signals that your system is under strain. This is also why so many traditional approaches backfire. More cardio and fewer calories might have worked in your 20s, but now they can lead to muscle loss, a slower metabolism, and even more frustration. Your body isn't broken. It's just responding to a different set of internal signals. Instead of trying to force weight loss, the focus has to shift to supporting your metabolism. That starts with getting enough protein, often more than you think you need, and focusing on strength training to rebuild and maintain muscle. Walking and lower-stress movement can also support your system without driving cortisol higher. For many women, the real shift is understanding that you may need to build your body back up before it's ready to let weight go. That's how you create results that actually last. If you've been doing all the right things and still feel stuck, it's likely not about trying harder. It's about getting the right support for your body specifically. If this sounds like you, you can book a discovery call to get a clear, personalized plan for what your body actually needs: https://calendly.com/dr-beth-westie/program-discovery-call

Your labs came back clean. Your doctor says your blood work is “normal.” Your weight is “fine.” But your energy is dropping, your thinking feels slower, and there's a ceiling you keep bumping up against. This episode is for that specific situation. It's far more common among high-performing executives and founders than most people realize.Julian walks through exactly how he thinks about it: why standard blood work can't see what's actually happening, the four layers he maps before ordering a single test, and the phased approach he uses to create clarity before adding anything new. If you've been told everything looks normal, but you know something isn't right, this one is for you.— Episode Chapter Big Ideas (timing may not be exact) —0:00 – Welcome & the "normal labs but feeling off" situation 1:54 — Who Julian is & what Executive Health does2:37 — Why "normal" doesn't mean optimal 3:01 — What a standard annual physical actually measures 4:52 — What standard blood work doesn't measure6:15 — Why your TSH in range doesn't mean your thyroid is functioning optimally 7:37 — Why a single morning draw misses the full rhythm of cortisol 9:19 — Why fasting glucose isn't enough10:54 — Why health sovereignty matters 11:31 — The four diagnostic layers Julian maps first12:40— Layer 1: Energy Timeline14:03— What energy patterns actually signal15:13 — Layer 2: Cognitive Quality16:27 — Decision fatigue as an early signal of declining biological capacity18:03 — Layer 3: Lifestyle Load21:38 — Why accumulated stress without recovery creates a compounding deficit22:22 — Layer 4: Environmental Inputs:23:10 — Morning light, circadian rhythm, and why most executives are running a circadian deficit25:02 — Why seven hours of sleep can still leave you depleted25:59 — Overlooked signs of sleep debt26:45 — Constant stimulation and the cost of a nervous system that never downregulates28:34 — The three-phase approach overview: Stabilize, Signal Clarity, Targeted Testing29:23) Phase 1: Stabilize29:56 — Why sleep consistency matters more than duration31:36 — Why sleeping before midnight hits differently34:34 — Meal timing and sleep quality35:31 — Phase 2: Signal Clarity36:34 — Why layering more interventions buries the real problem further37:36 — Phase 3: Targeted Testing38:20 — What targeted testing actually looks like39:00 — Why hormonal health is the foundation40:18 — The skill of slowing down before speeding up40:49 —Why accomplished leaders stay stuck42:04 — Pattern 1: Trusting labs over lived experience43:28 — Pattern 2: Adding tactics instead of creating clarity44:58 — Why complexity feels like progress but often buries the real issue46:15 — Pattern 3: Normalizing subpar performance because external metrics are still moving47:55 — The cost shows up gradually…then suddenly49:11 — The gap between existing and thriving51:06 — How to work with Julian privately— Connect with Julian and Executive Health —LinkedIn — https://www.linkedin.com/in/julianhayesii/X — https://x.com/thejulianhayesDon't let your biology become the bottleneck to the enterprise you're building. Book a private call —https://www.executivehealth.io/contactWebsite — https://www.executivehealth.io/***DISCLAIMER: The information shared is not meant to treat or diagnose any condition. This is for educational, informational, and entertainment purposes. The content here is not intended to replace your relationship with your doctor and/or medical practitioner. Consult your provider before making any decisions.

Green Bay's Draft Without Pick No. 1 The Detroit Lions Podcast put the NFC North under the microscope. Green Bay navigated the 2026 NFL Draft without a first-round pick. Inside the room, they essentially treated Micah Parsons as that missing top selection. It framed every other choice and every roster bet. That context matters for Detroit Lions fans sizing up the division. Scouting and process took center stage. The conversation cut through recycled big boards and highlighted year-round work. Senior Bowl trips. Shrine practices back when they were in St. Petersburg. Long lists stacked against real tape. Original evaluations, not echoes. That lens set up a blunt look at how Green Bay built its board and why. Micah Parsons and the Ten-Month ACL Clock The timetable was clear. The modern ACL return is a ten-month arc from injury to full snap load. Map that to the NFL calendar and the target becomes around Week Five. Expect a roster stash to start. The assumption is the PUP list to open the season, then a ramp-up to real usage. Expectations were once sky-high. A defensive coach even floated league-leading sack potential before leaving for the Miami job. Reality now lives in checkpoints, not headlines. That timeline shapes how Detroit prepares to block, chip, and slide protections when the calendar turns. It also mirrors a familiar Detroit thread. Brian Branch's earlier injury surfaced as a reference point for working backward from health, not hype. The New PUP Rule and Week Five Targets The NFL tweaked the PUP rules, and it changes the math. Previously, players on PUP could not practice with the team for four weeks. Now the no-practice window is two weeks. After that, teams can designate to return and build a two-week ramp while the player remains on PUP. For a contender, that is roster flexibility. For the Detroit Lions, it is a calendar to monitor across the division. Layer in Green Bay's broader injury picture. Devonte Wyatt is on track. Tucker Craft's timing aligns with the start of training camp, with Week One availability expected. Extension talks are in line for him. Jordan Riley ruptured an Achilles. That points to season-long IR unless there is a settlement. Given the severity, the incentive is to keep him around and let the rehab run its course. What It Means Around the North The Packers' first-round void, the Parsons clock, and the PUP tweak all converge on the same conclusion. September snaps will look different than October snaps. Week Five becomes a circle date. The Detroit Lions will plan protections and personnel with that in mind. The NFL is a timeline league. Health windows decide matchups as much as schemes. Today's recap keeps the calendar front and center for Detroit and the division. #detroitlions #lions #detroitlionspodcast #nflpuplist #packersdraft #micahparsonsacl #brandoncisse #keithabney #jagerburton #danidennis-sutton Learn more about your ad choices. Visit megaphone.fm/adchoices

Good morning! Let's bring all the pieces of your peace together. Today is Day 6 of our Vagus Nerve Reset, and we are focusing on Integration. We're learning how to "stack" our eye shifts, breath releases, and mudras to create a powerful, unified signal of safety for the brain. In This Episode: The Power of Layering: Why "stacking" somatic techniques is the fastest way to lower a high cortisol baseline. The Weaving of the Soul: How ancient practitioners used multi-sensory rituals to achieve deep states of presence. The Integrated Practice: A full 5-minute guided session combining every tool we've learned this week. A Daily Message for Your Heart Life often asks you to be ten different people at once. You are the business owner, the grandmother, the fixer, the dreamer. It's easy to feel scattered into a million pieces. Today, I want you to feel the relief of coming back into one piece. You don't have to be fragmented today. As you layer these breaths and these movements, imagine you are gathering all those scattered parts of yourself and bringing them home to your heart. You are a masterpiece of integration. You are steady, you are soft, and you are whole. I am so honored to be part of your symphony today. This is day 6 of a 7-day meditation series, "Vagal Tone Reset: How to Recover from Stress 50% Faster" episodes 3507-3513. THE WEEKLY CHALLENGE -  THE ARTIFACT HUNT Each day, find one physical object with weight and texture—a stone, a heavy book, a piece of wood— and hold it for 60 seconds to anchor your senses. THIS WEEK'S MEDITATION JOURNEY Day 1: VISUALIZATION: VAGUS NERVE TONINGVisualize peace flowing through your vagus nerve, strengthening your major organs. Day 2: AFFIRMATION:  "I am safe in my body, and I am home in this moment." Day 3: THE VAGAL BREATH  The Ocean Sigh -  Inhale for 4, imagining breath rising from the soles of your feet. Hold for 4, feeling the weight of your hips. Exhale for 8, sighing out the future. Day 4: PRITHVI (EARTH) MUDRA Touch the tip of the ring finger to the thumb. This encourages stability and physical healing. Day 5: ROOT CHAKRA (MULADHARA) Location: Base of Spine - Color: Deep Red - Quality: Feeling Safe & Secure Day 6: VAGAL NERVE TONING FLOW MEDITATION: Combining the week's techniques Day 7: WEEKLY REVIEW MEDITATION: Closure with a review of the week's highs and lows. SHARE YOUR MEDITATION JOURNEY WITH YOUR FELLOW MEDITATORS Let's connect and inspire each other! Please share a little about how meditation has helped you by reaching out to me at Mary@SipandOm.com or better yet -- direct message me on https://www.instagram.com/sip.and.om. We'd love to hear about your meditation ritual! WAYS TO SUPPORT THE DAILY MEDITATION PODCAST SUBSCRIBE so you don't miss a single episode. Consistency is the KEY to a successful meditation ritual. SHARE the podcast with someone who could use a little extra support. I'd be honored if you left me a podcast review. If you do, please email me at Mary@sipandom.com and let me know a little about yourself and how meditation has helped you. I'd love to share your journey to inspire fellow meditators on the podcast! All meditations are created by Mary Meckley and are her original content. Please request permission to use any of Mary's content by sending an email to Mary@sipandom.com. FOR DAILY EXTRA SUPPORT OUTSIDE THE PODCAST Each day's meditation techniques are shared at: sip.and.om Instagram https://www.instagram.com/sip.and.om/ sip and om Facebook https://www.facebook.com/SipandOm/ SIP AND OM MEDITATION APP Looking for a little more support? If you're ready for a more in-depth meditation experience, allow Mary to guide you in daily 30-minute guided meditations on the Sip and Om meditation app. Give it a whirl for 7-days free! Receive access to 3,000+ 30-minute guided meditations customized around a weekly theme to help you manage emotions. Receive a Clarity Journal and a Slow Down Guide customized for each weekly theme. 2-Week's Free Access on iOS https://itunes.apple.com/us/app/sip-and-om/id1216664612?platform=iphone&preserveScrollPosition=true#platform/iphone All meditations are created by Mary Meckley and are her original content. Please request permission to use any of Mary's content by sending an email to Mary@sipandom.com.Let go of repetitive negative thoughts. Music composed by Christopher Lloyd Clark licensed by RoyaltyFreeMusic.com, and also by musician Greg Keller.

For episode 724 of the BlockHash Podcast, host Brandon Zemp is joined by Samuel (Chad) Patt, Co-founder of OP_NET.OP_NET enables smart contracts directly on Bitcoin Layer 1, with no bridges, sidechains or Layer 2s. BTC is used as gas, keeping all security and liquidity native to Bitcoin. This unlocks stablecoins, lending, trading, staking and DeFi entirely on Bitcoin without wrapped assets or custodial risk.Samuel has always pursued opportunities that challenge conventional market cycles and push the boundaries of narrative. Coming from a punk background, his passion for Bitcoin stems from its decentralized architecture and anti-establishment ethos. In 2023, alongside his co-founders Danny and Anakun, Samuel began building toward a more productive Bitcoin - one capable of hosting smart contracts, institutional-grade infrastructure, and open financial applications.  

In this episode, we discuss shifting dynamics in crypto infrastructure, including Base moving away from Optimism, the evolving Layer 2 landscape, MegaETH's business model, and Jito's expansion into trading products with JTX. We also cover tokenized equities on Solana, frontend vs. backend monetization strategies, and Coinbase's layoffs and earnings miss. Thanks for tuning in! As always, remember this podcast is for informational purposes only, and any views expressed by anyone on the show are solely their opinions, not financial advice. -- Follow Blockworks Research: https://x.com/blockworksres Follow Danny: https://x.com/defi_kay_ Follow Boccaccio: https://x.com/salveboccaccio -- Subscribe on YouTube: https://bit.ly/3foDS38 Subscribe on Apple: https://apple.co/3SNhUEt Subscribe on Spotify: https://spoti.fi/3NlP1hA Get top market insights and the latest in crypto news. Subscribe to Blockworks Daily Newsletter: https://blockworks.co/newsletter/ -- Timestamps: (0:00) Introduction (2:22) Base Leaves Optimism (5:31) L2 Winners And Losers (10:01) MegaETH's Revenue Play (14:06) JTX Goes Upstack (35:11) Coinbase's Rough Week (45:43) Closing Comments -- Check out Blockworks Research today! Research, data, governance, tokenomics, and models – now, all in one place Blockworks Research: https://www.blockworksresearch.com/ Free Daily Newsletter: https://blockworks.co/newsletter -- Disclaimer: Nothing said on 0xResearch is a recommendation to buy or sell securities or tokens. This podcast is for informational purposes only, and any views expressed by anyone on the show are solely our opinions, not financial advice. Boccaccio, Danny, and our guests may hold positions in the companies, funds, or projects discussed.

FREE Self-Scaling Business Workshop: https://getepicsuccess.com/registration-yt WORK With Me: https://getepicsuccess.com/ceo-org If you've ever: Had your team perform great when you're in the room… but standards slip when you step away Felt like your company culture depends on your presence instead of your processes Wondered why "good people" still make decisions differently than you would Tried to scale your team, only to feel like you're still the one holding the standard together This is why. In this episode of the Epic Success Podcast / Scaled CEO Show, I'm breaking down the 3-Layer Culture System that helps your team win the same way — whether you're in the room or not. Because culture doesn't scale when it's just a vibe. It scales when your team has clarity, capability, and a culture strong enough to self-correct without you carrying it every day. Inside This Episode: ● Why "good vibes" cultures break as you grow How founder-led standards drift when they aren't turned into clear systems ● The real reason your team lowers the bar when you're gone Why it's usually not a people problem — it's a clarity, capability, and culture problem ● Layer 1: Clarity How to define what winning looks like so your team isn't guessing ● Why values like "integrity" and "do no harm" aren't obvious How to translate company values into plain-language behaviors your team can actually execute ● Layer 2: Capability Why skill without authority creates task doers, not leaders ● How to put the right people in the right seats The difference between leadership tracks and expert/operator tracks ● Layer 3: Culture How to identify the behaviors you reward, tolerate, and eliminate ● How to build a team that self-selects, self-corrects, and self-recruits So your A-players help protect the standard without everything escalating back to you If You're a Business Owner Who: ● Has a team, but still feels like the culture depends on you ● Notices standards slip when you're not present ● Has great people, but too many decisions still come back to you ● Wants your team to own the mission, not just complete tasks ● Knows your business can't scale if you stay the backup brain and culture bearer This episode will show you exactly what's missing. The Real Shift: You don't need a better culture poster. You need a culture system. When your team knows what winning looks like, has the authority to execute, and understands which behaviors are rewarded, tolerated, or eliminated… they stop guessing. They start owning. And your business can finally grow without depending on your presence every day. Ready to Fix This for Real? Join me live for the Self-Scaling Business Diagnostic, where we: ● Score your CEO, Team, and Profit systems ● Identify where culture and ownership are breaking down ● Map your next 67-day sprint to reclaim time and scale

Mikey Dickerson returns to The Great Battlefield podcast to talk about his firm Layer Aleph, which helps enterprises through technical crises, and his new book "Crisis Engineering: Time-Tested Tools for Turning Chaos Into Clarity".

The Emblem Show is hosted on Twitter Spaces and livestreamed across YouTube/X on Tuesdays and Thursdays at 1:00PM EST. The show focuses on news and events in the cryptocurrency industry, as well as inviting guests on from all sectors across DeFi, NFTs, AI, and interoperability.Adam McBride: https://twitter.com/adamamcbrideJake Gallen: https://twitter.com/jakegallen_Chris Devitte: https://twitter.com/chris_devvEmblem Vault: https://twitter.com/EmblemVaultMigrate Fun: https://x.com/MigrateFun

In this week's episode, both of our storytellers build shields to protect themselves and discover what happens when those defences fail.Part 1: As a lonely teenager searching for connection, Christopher Moncayo-Torres turns to an unlikely disguise—a giant Clifford costume—in hopes of bridging the gap between himself and the world around him.Part 2: JP Flores has always been the family's “smart kid,” a role that becomes his armor in college—until the pressure of living up to that identity begins to crack.Christopher Moncayo-Torres is an Ecuadorian-American writer, actor, teaching artist and live storyteller, born and bred in Queens, NY, and new-ish to living in LA. Most recently, he performed alongside his Ecuadorian father (yes, really) in "No Sabo", an award-winning, solo-ish show about rekindling their once estranged relationship, despite their language barrier. He's now working on a live-ish cooking show with his mother. He also hosts the monthly storytelling-workshop show, Fail Better Story Time at Studious Coworking Space in LA's Chinatown. More info can be found at www.failbetterarts.com He's an instructor and host for The Moth. He's also a 3x Moth StorySLAM winner who has been featured on The Moth Radio Hour podcast.JP Flores recently completed his PhD in Bioinformatics and Computational Biology from UNC Chapel Hill, where he studied how DNA folds in 3D space to control when, where, and why genes turn on. He calls this the origami of gene regulation. Originally from Los Angeles, he's also pursuing a Graduate Certificate in Innovation for the Public Good, blending his love for bridging science and society. He's a HHMI Gilliam Fellow, a podcast host (From Where Does It STEM?, a Spotify Next Wave Award winner), and is passionate about turning science communication into community connection. He is also a co-founder of the nonprofit organization, Science For Good. Outside the lab, JP plays guitar and gigs around North Carolina, and lives with his very opinionated and stubborn wiener dog, Vienna. As a first-gen college student, he's driven to make science more community-centered and for the public good.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In this episode, Chris Lacy, President at Priority Search Management, discusses building a search firm focused on the “missing middle” of leadership talent, the value of embedded partnerships with private equity-backed organizations, and how trust, clarity, and consistent execution drive long-term recruiting success.

The Mike Vrabel and Dianna Russini story has had a new layer added to it.Gov Tim Walz tries to take credit for a fraud crackdown that came from..........the feds.Kentucky man credits a Giants kicker for missing a FG and saving his life.No idea how but we get into the Vikings Love Boat scandal from 2005See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

The race for AI dominance has created a dangerous imbalance between business velocity and cyber resilience. In this episode, host Caleb Tolin is joined by Joe Hladik, Head of Rubrik Zero Labs, and Staff Security Researcher Amit Malik to break down the findings of their latest report on agentic adoption. The discussion centers on the Agentic Paradox. This is the technical reality that tools designed to automate high-level tasks are inherently built to find the most efficient path around obstacles, including existing security policies. A primary focus is implementing a three-layer framework for AI Operations. This model targets the Tool Layer, where agents interact with databases; the Cognitive Layer, which serves as the LLM brain; and the critical Identity Layer. The conversation explores stories in which agents, without malicious intent, have caused catastrophic data loss simply by following an optimized logic path. These instances prove that agents need not be sentient to be destructive when they lack proper human-in-the-loop checkpoints. Technical hurdles of Identity Resilience are also addressed, specifically the explosion of non-human identities that spin up and down like elastic cloud infrastructure. The episode examines the fear index regarding job security, noting that 92% of leaders fear for their roles post-breach. Joe and Amit join Caleb to explore the evolution of personal liability for CISOs and the urgent need to move from basic visibility to deep observability. This is a forward-looking briefing for leaders who recognize that, in an era of autonomous routines, the human must remain the ultimate command-and-control center. What You'll Learn Define the agentic paradox to understand why AI efficiency naturally compromises traditional security guardrails. Implement a three-layer framework to secure the tool, cognitive, and identity components of AI. Transition from basic visibility to deep observability to track autonomous decision-making in real time. Mitigate prompt injection risks by auditing the input and output flows of the cognitive layer. Utilize ephemeral containers to sandbox agentic tools and prevent unauthorized database alterations. Manage the elasticity of non-human identities to maintain control over rapidly spinning AI agents. Anchor AI operations with human-in-the-loop checkpoints to ensure integrity during high-stakes executions. Episode Highlights Defining the Agentic Identity and Autonomous Routines Revenue vs. Resilience: The Drivers of AI Urgency The Three-Layer Framework for Agentic Defense Shadow AI and the Rise of Invisible Insider Threats The Context Gap: Why Rolling Back AI Actions is Hard The CISO Fear Index and Personal Liability Post-Breach Visibility vs. Observability in Elastic Identity Environments Learn more about your ad choices. Visit megaphone.fm/adchoices