Disrupt or Defend

Softup Technologies GmbH
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In the age of AI, founders face a constant choice: disrupt the market—or defend what they’ve built. Disrupt or Defend is a weekly podcast for startup founders, CTOs, and tech builders who want to stay ahead without losing focus on people and purpose. Host Daniel Kazani, co-founder of Softup Technologies, talks with founders and experts who are shaping the next wave of software innovation. From AI agents and low-code tools to scaling dev teams and building products that last, each episode explores the decisions that define a company’s future. If you’re building in tech and want real stories, practical lessons, and honest conversations about the balance between boldness and focus—this show is for you. Subscribe and join the community of builders defining what comes next in tech.

  1. 5D AGO

    AI in Fintech: Investor Explains Trends, Defensibility and How to Stand Out | Ep. 21

    The bottleneck in software is no longer building the product: it is getting it into the hands of users. As artificial intelligence compresses development timelines, distribution and go-to-market strategies are becoming the true competitive advantages. ㅤ Host Daniel Kazani, co-founder at Softup, sits down with Ben Robinson, CEO of Aperture.co, to examine this shift. Ben explains how his firm acts as an operational VC, embedding growth teams directly into startups to solve the complex challenge of selling to large financial institutions. They look at why the standard subscription model is losing ground to variable and outcome-based pricing, and how embedded finance opens new monetization paths for software founders. ㅤ Daniel and Ben also discuss the remaining defensive lines in tech. They emphasize that proprietary data, network effects, and deep-rooted trust are what protect companies in an increasingly fast-paced market. ㅤ 👤 Guest Bio Ben Robinson is the CEO and Co-Founder of Aperture.co, a Swiss-based growth and investment partner for the financial services sector. Before starting Aperture, Ben worked as Chief Strategy Officer at Temenos, where he launched the Temenos MarketPlace to connect banks with complementary fintech scale-ups. Today, Ben and his team invest in early-stage European B2B fintech companies. They operate differently from traditional venture capital by running hands-on go-to-market projects and embedding product and marketing experts directly into their portfolio companies. ㅤ 📌 What We Cover How artificial intelligence compresses venture capital timelines by making it faster and cheaper to build software.Why distribution and go-to-market execution are replacing development as the main bottleneck for startups.The necessary shift from fixed subscription billing to variable, outcome-based pricing models.Why embedded finance changes the way non-financial companies monetize their core products.The most common mistake founders make when scaling their sales teams and stepping away from direct selling too early.Why network effects, proprietary data, and regulatory licenses remain strong defensive positions.The importance of building trust in financial services and how neobanks succeeded by starting with simple wedge products. ㅤ 🔗 Resources Mentioned Aperture.coTemenos MarketPlaceRevolutStripeOpen SolarPayTechEasyJet

    41 min

  2. MAR 26

    From Copilots to Culprits: The Legal Reality of AI | Ep. 20

    Autonomous AI agents promise massive productivity gains, but with autonomy comes severe financial and legal risk. If an AI system deployed in banking falls victim to a prompt injection attack, it could falsify compliance records or authorize illegal transactions. A human might notice a mistake after one or two errors, but an AI could execute thousands of false transactions per second, potentially bankrupting a financial institution. ㅤ Host Daniel Kazani sits down with Patrick Munro to examine the legal implications of this technology. Patrick shares a cautionary tale about the dangers of disabling safety features and granting full autonomy without human oversight. They discuss the difference between human-in-the-loop systems and autonomous agents from a legal perspective. ㅤ The conversation also touches on data sovereignty, the challenges of running on-premise servers, and why the healthcare sector remains hesitant to adopt automated tools. Daniel and Patrick highlight the need for a pragmatic approach to risk and the importance of establishing clear usage policies. ㅤ Guest Bio Patrick Munro is a technology lawyer operating at the intersection of artificial intelligence, cybersecurity, and IT regulatory compliance. He serves as Legal Counsel for Financial Services at Capgemini and as Of Counsel at the IT law boutique planit//legal. Patrick acts as a dual Subject Matter Expert for AI and Cybersecurity, actively developing legal technology tools like compliance dashboards and contract review assistants. He believes that AI gives lawyers better tools to focus on judgment-intensive work rather than replacing them completely. ㅤ What We Cover The financial risks of agentic AI and the dangers of prompt injection attacks.How a single hijacked AI agent could impact compliance records and sanction screenings.The monoculture risk of multiple banks deploying the same vulnerable AI models.Legal liability differences between human-in-the-loop decisions and fully autonomous smart contracts.Personal liability implications for managing directors under the NIS2 Directive.Data privacy concerns with US hyperscalers versus the logistical hurdles of on-premise AI servers.Why highly regulated sectors like healthcare are hesitant about AI adoption due to strict criminal implications for data leaks.The need to define clear use cases and usage policies before implementing AI within a company. ㅤ Resources Mentioned Capgeminiplanit//legalSoftupMINDMASH MunichAnthropic Claude and Claude CodeCOBOLAmazon BedrockMistralNIS2 DirectiveDigital Operational Resilience Act (DORA)EU AI ActEU Omnibus Proposals

    39 min

  3. MAR 19

    Protecting authors rights in the age of AI | Ep. 19

    Artificial intelligence models are hungry for high-quality human knowledge. For years, developers scraped this data without asking permission or compensating the creators. Now, massive lawsuits are forcing the tech industry to rethink how it acquires training material. ㅤ Host Daniel Kazani of Softup sits down with Julie Trelstad to discuss how authors can protect their intellectual property and earn money in the modern era. They explore the shift from unauthorized scraping to legitimate licensing agreements. The conversation covers the critical differences between European and United States copyright laws regarding machine training. ㅤ They also examine how specialized, peer-reviewed data is becoming a premium asset for new software applications. Finally, Daniel Kazani and Julie discuss how writers can instruct digital assistants to act as collaborative editors rather than replacements for genuine human creativity. ㅤ 👤 Guest Bio Julie Trelstad brings over 35 years of experience to the publishing industry. Starting her career editing technical and architecture books, she navigated major technological shifts from desktop publishing to the rise of digital distribution. Today, Julie serves as the Head of U.S. Publishing at Amlet AI, a public registry dedicated to text and data mining rights. She also runs Paperbacks & Pixels, an author-support studio that helps writers build sustainable businesses and structured sales systems. ㅤ 📌 What We Cover The ethical and legal fallout from training large language models on pirated books.How Amlet AI uses the International Standard Content Code to create a digital fingerprint for written work.Why most authors are currently opting out of machine training licensing due to wildly fluctuating payments.The structural differences between creator compensation laws in Europe and the United States.How peer-reviewed research will become a premium asset for developers building highly specific software tools.Practical methods for instructing tools like Claude to slow down and preserve an author's original writing style.The future of publishing contracts, in which machine language training becomes a standard secondary right. ㅤ 🔗 Resources Mentioned Amlet AIPaperbacks & PixelsInternational Standard Content Code (ISCC)StreetLibClaudeChatGPTFraunhofer Institute

    28 min

  4. MAR 12

    AI-Powered Smart Home Search | Ep. 18

    Traditional real estate systems often come with rules, limitations, and legacy baggage that can stifle creativity. Host Daniel Kazani speaks with Bobby Bryant, M.Ed.x2 about building a solution that bypasses the MLS entirely. Bobby explains the strategy behind hōmhub.ai: a peer-to-peer, AI-powered Real Estate Operating System. They discuss why he chose a non-MLS approach to allow for features like digital offers and commission transparency. Bobby also details the launch of the Global Agent Exchange to unify agents across borders and his plans to bring voice-activated home search to the world. ㅤ 👤 Guest Bio Bobby Bryant, M.Ed.x2 is the CEO of DOSS Group, INC. and the founder of hōmhub.ai. A veteran with over 25 years in the industry, he became the first African American to create and franchise a real estate brokerage brand. His work is backed by Amazon and Google. Bobby holds two Master’s Degrees in Education and previously served as a contributor to Forbes. ㅤ 📌 What We Cover Why hōmhub.ai operates as a non-MLS platform to avoid data restrictions and allow for more creativity.The concept of a property-agnostic marketplace: handling sales, rentals, and wholesale properties in one unified system.How the team applies a "Steve Jobs" philosophy by designing for the consumer experience first and working backward to the technology.The specific features of their AI search: users can speak in over 100 languages or visualize new wall colors and flooring instantly.Creating a "Carfax for homes": allowing owners to upload warranties, receipts, and documents directly to a property profile.The Global Agent Exchange (GAE): a listing service built to standardize real estate practices for modern agents.Plans to expand the platform into international markets like Canada, the UK, and New Zealand.Using data to answer hyper-local questions about neighborhoods: from noise levels to air quality. ㅤ 🔗 Resources Mentioned hōmhub.aiBobby Bryant on LinkedIn

    26 min

  5. MAR 5

    Optimize Manufacturing with AI | Ep. 17

    Manufacturing generates massive amounts of data, yet many factories still run expensive machinery on settings that have not changed in a decade. Daniel Kazani sits down with Dr. Jonathan Spitz, Founder and CEO of GaussML, to discuss why having data does not always mean having information. ㅤ Jonathan explains his "small data" approach to industrial optimization. Instead of requiring months of data cleaning and massive data lakes, his team focuses on rapid experimentation. By running a few targeted tests, operators can find the ideal parameters for processes like laser cutting and injection molding in a single day. Jonathan shares real-world examples, including how a 0.5-gram adjustment saved Coca-Cola 20 tons of plastic a year and how job shops eliminated Saturday shifts by increasing efficiency. The conversation also covers the role of the human operator as a pilot rather than a bystander. ㅤ Guest Bio Dr. Jonathan Spitz is the Founder and CEO of GaussML. Before launching his own company, he served as a Research Scientist at the Bosch Center for Artificial Intelligence, where he applied machine learning algorithms to industrial optimization. He holds a PhD in Mechatronics, Robotics, and Automation Engineering from the Technion - Israel Institute of Technology. Jonathan specializes in "small data" solutions that help manufacturers improve efficiency without complex integration. ㅤ What We Cover The difference between being data-rich and information-poor in manufacturingWhy traditional deep learning often fails in factory settings due to the need for massive datasetsHow the "small data" approach works: finding optimal machine settings with minimal experimentsReal-world wins: Reducing cycle times by 50% in machining and saving raw materials in bottle productionThe Coca-Cola case study: How a tiny weight reduction per bottle resulted in massive material savingsThe "Copilot" philosophy: Why AI should augment the operator's intuition rather than replace itOvercoming the "worker gap" by making expert-level machine operation accessible to newer employeesWhy is failing during the testing phase necessary to find the true limits of a machine ㅤ Resources Mentioned GaussML (Official Website)Optimyzer (Product)Dr. Jonathan Spitz (LinkedIn)Daniel Kazani (LinkedIn)Softup TechnologiesBosch (Company)TRUMPF (Company)Coca-Cola (Company)

    29 min

  6. FEB 26

    GenAI In Real Estate | Ep. 16

    Real estate runs on data, but most of it is trapped in PDFs, lease agreements, and siloed legacy systems. In this episode, host Daniel Kazani sits down with Dr. Nino Paulus, Co-Founder and CPO of AlphaPrompt, to discuss how generative AI is bringing order to this chaos. Nino explains how his team moved from building simple dashboards to creating an AI that functions like a senior analyst—capable of reading entire data rooms, extracting complex lease terms, and spotting risks that humans might miss. ㅤ They discuss the reality of deploying AI in a traditional industry, sharing a story in which their software identified 7 active leases for a property the owner didn't even know they still owned. Nino also opens up about his "live demo" sales strategy and shares his thoughts on the future of autonomous AI agents, including the emergence of "Moltbook," a social network where bots communicate with each other. This is a practical look at how Softup and other tech builders can learn from AlphaPrompt's approach to automation and data structuring. ㅤ 👤 Guest Bio Dr. Nino Paulus is the Co-Founder and Chief Product Officer of AlphaPrompt. He holds a PhD from the IREBS International Real Estate Business School, where his research focused on Natural Language Processing (NLP) in the real estate sector. At AlphaPrompt, he leads the development of GenAI solutions that automate due diligence and data structuring for asset and property managers. His work bridges the gap between academic AI research and the practical, messy reality of real estate documentation. ㅤ 📌 What We Cover The Data Problem: Why the biggest challenge in real estate isn't a lack of data, but the fact that it is unstructured and stuck in "silos" that don't talk to each other.Automating "Monkey Work": How AlphaPrompt uses GenAI to handle the tedious tasks—like typing out rent rolls or checking lease addendums—so analysts can focus on decision-making.The "Live" Sales Pitch: Nino explains why he throws a prospect's actual data room into the tool during sales calls instead of using a canned demo.Red Flag Reports: Moving beyond just data extraction to "risk alerts," such as spotting a break clause that allows a tenant to leave early.The "Lost" Property Story: A case study where the AI found seven active leases in a small German town that the portfolio owner thought they had exited years ago.Bottom-Up Adoption: Why AI initiatives fail when they are top-down mandates and why you need to involve the people doing the daily work to make it stick.The Future of Agents: A look at "Moltbook" (Moltbot), a social network for AI agents, and what happens when bots start communicating and learning from one another without human input. ㅤ 🔗 Resources Mentioned AlphaPrompt (Guest Company)Moltbook (AI Agent Social Network mentioned by Nino)

    32 min

  7. FEB 19

    How AI Is Rewriting Brand Visibility | Ep. 15

    Brands are losing visibility because they rely on click-based attribution in a world moving toward answer engines. Daniel Kazani speaks with Malte Landwehr, CPO and CMO of Peec AI, about the reality of AI search. Malte explains why 25% of leads might come from LLMs even when tracking software shows 0%. They discuss the transition from SEO to GEO, why static dashboards are disappearing, and the hard truth that average marketing work is becoming valueless. ㅤ Guest Bio Malte Landwehr is the Chief Product Officer and Chief Marketing Officer at Peec AI. He has over 20 years of industry experience, including roles as VP of SEO at idealo and VP of Product at Searchmetrics. Peec AI helps marketing teams understand and optimize their visibility in LLM-based search engines. ㅤ What We Cover Why click-based tracking fails to capture the user journey inside ChatGPT and Perplexity.The specific role of "grounding sources" such as Reddit, YouTube, and LinkedIn in AI responses.How Peec AI simulates user behavior to track brand mentions and sentiment.The shift from static data dashboards to on-demand AI chat interfaces.Why is average marketing becoming free while top-tier marketers become exponentially more effective?The challenge of finding product managers with strong product taste in Europe. ㅤ Resources Mentioned Peec AIMalte Landwehr (LinkedIn)Daniel Kazani (LinkedIn)ChatGPTPerplexityGoogle GeminiGranolaHubSpot

    33 min

  8. FEB 12

    How AI is impacting Health Tech | Ep. 14

    Learn more about facial vital sign detection: shen.ai & caire.ai ㅤ Healthcare has historically lagged in digitalization, creating a significant opportunity for artificial intelligence to jump-start the industry. Host Daniel Kazani sits down with Dr. Lucas Mittelmeier, an investor at Heal Capital, to discuss why the sector's heavy administrative burden makes it a prime target for disruption. They explore the reality of "Shadow AI," where physicians bypass slow hospital IT systems to use tools like ChatGPT for daily tasks. Lucas explains how the industry is splitting into two distinct speeds: highly regulated clinical tools and agile administrative workflows. The conversation also highlights cutting-edge innovations, including facial analysis software that reads vital signs via a camera and vocal biomarkers that detect heart failure. ㅤ Guest Bio Dr. Lucas Mittelmeier is a physician-turned-investor at Heal Capital, a leading European healthtech venture capital firm. With a background bridging clinical medicine, strategy consulting, and startup leadership, he evaluates companies through both medical and business lenses. He is also the author of the Healthtech Off The Record newsletter, where he provides data-driven analysis of industry trends. At Heal Capital, he focuses on sourcing and leading deals from Pre-Seed to Series A. ㅤ What We Cover Why the lack of legacy digital infrastructure in healthcare might actually accelerate AI adoption.The phenomenon of "Shadow AI" and why doctors are using consumer tools despite strict hospital regulations.How administrative AI is moving faster than clinical diagnostic tools due to lower regulatory barriers.The potential for "facial parameters" in which video can detect heart rate, blood pressure, and oxygen saturation.Using vocal biomarkers to identify conditions like heart failure by analyzing fluid buildup in the lungs.How typing patterns on a keyboard can serve as early indicators for depression.Why specialized "AI Therapist" startups have struggled to compete with general Large Language Models.The four key moats for healthtech startups: data advantages, network effects, deep customer service, and brand trust. ㅤ Resources Mentioned Heal CapitalOpenAI (ChatGPT)Anthropic (Claude)WhoopCaire (Healthtech startup)Scale AI

    34 min
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About

In the age of AI, founders face a constant choice: disrupt the market—or defend what they’ve built. Disrupt or Defend is a weekly podcast for startup founders, CTOs, and tech builders who want to stay ahead without losing focus on people and purpose. Host Daniel Kazani, co-founder of Softup Technologies, talks with founders and experts who are shaping the next wave of software innovation. From AI agents and low-code tools to scaling dev teams and building products that last, each episode explores the decisions that define a company’s future. If you’re building in tech and want real stories, practical lessons, and honest conversations about the balance between boldness and focus—this show is for you. Subscribe and join the community of builders defining what comes next in tech.

Information

  • Creator
    Softup Technologies GmbH
  • Years Active
    2025 - 2026
  • Episodes
    21
  • Rating
    Clean
  • Copyright
    © Copyright 2026 Softup Technologies GmbH
  • Show Website
    Disrupt or Defend