What does it really take to build a regulated fintech product from scratch—with a small team and a bootstrapped budget?

In this episode of Futureproof, Prakash Chandran sits down with Michael Konrath, co-founder and Chief Product Officer of Choice Digital, a fintech company that ensures customers—including the unbanked—actually receive the payments they're owed. Michael shares the full arc of building Choice Digital: from prototyping on Bubble in a co-working space to processing nearly $1 billion in payments today. Along the way, they dig into the realities of compliance in a regulated industry, the trade-offs of building fast versus building right, and how AI is starting to reshape the way his team ships software.

Topics covered include:

• Starting small with no-code: Why Choice Digital's first product was built on no-code tools in 30 days, processed $20 million in payments, and lasted far longer than expected—plus how that scrappy mindset still matters in the age of AI.
• Compliance as a foundation, not an afterthought: The case for investing in SOC 1 and SOC 2 frameworks early, how PCI compliance shapes product architecture, and why segmenting systems can simplify your regulatory journey.
• AI adoption in a regulated space: Why Choice Digital is taking a deliberate, human-in-the-loop approach to AI, focusing on deterministic processes and clear policies before letting models touch customer data.

Episode ID: 18983940-from-prototype-to-enterprise-grade-compliance-with-michael-konrath-choice-digital

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What if AI is just the latest Blockchain?

In this episode of Futureproof, Prakash Chandran sits down with Joshua Greenbaum of Enterprise Applications Consulting to explore the AI hype cycle. Josh reflects on his 30 years of technology consulting and examines whether AI is following the same trajectory as other technologies, where true value can get lost in the froth and frenzy of investors and founders trying to capitalize on it. Together, they explore the reality of whether SaaS really is dead, the criticality of standardizing data in the AI era, and the central question that all AI companies should be able to answer. 

Topics covered include:

• Technology history repeats itself. While technology itself changes constantly, the way it is received in the market doesn’t. From dotcom to Blockchain, the hype cycle has a pattern.
• The hard parts of SaaS. SaaS is certainly changing, but reports of its death have been greatly exaggerated. AI that can build prototypes is far from replacing companies like Salesforce, which have learned from years of on-the-ground work with real customers and real problems.
• The importance of data standardization. The value of AI will come down to how well it can access the information it needs. Standardization of data and logic is critical to this outcome, and one that companies have to get right before they can succeed with AI.
• The lone wolf developer. Developers aren’t going away, but developers that work in a vacuum may be. Building is a team sport even more than it was before, and the developers who can see and understand business problems are the ones that will build the future.
• The real question all AI companies need to ask. No business leader is waking up in the middle of the night thinking, “I need a large language model!” All companies, and AI companies in particular, must remain laser-focused on the actually important question: “What business problem am I solving?”

Episode ID: 18906617-dissecting-the-ai-hype-cycle-with-joshua-greenbaum-enterprise-applications-consulting

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If enterprises already have massive SaaS platforms, why would they build custom tools instead?

In this episode of Futureproof, Prakash Chandran sits down with Yvonne Lau, CEO of HR Verticals Inc., to explore the real tradeoffs of build vs. buy in technology—and what changes when AI and low-code tools enter the picture. Yvonne shares her journey from corporate HR practitioner to founder, tracing a career spent implementing global HR systems at scale before deciding to build her own. Together, they unpack why enterprise SaaS feels bloated for many organizations, how rapid prototyping with no-code and AI wins over skeptical buyers, and what it takes to sell custom-built software into compliance-heavy environments. They also discuss the shifting identity of non-technical founders, the importance of staying hands-on, and why the next generation of HR professionals may simply build the tools they wish they had.

Topics covered include:

• The SaaS bloat problem: Why enterprises pay for full suites but use only a fraction of the features—and how modular, custom-built tools offer a better fit.
• Rapid prototyping to win trust: How shipping an MVP in days using no-code and AI helps enterprise clients visualize what's possible and move past the subscription-only mindset.
• Compliance and IT collaboration: Why founders must bring IT into the conversation early, stay current on regulations, and anticipate security concerns—especially when AI is involved.
• AI as force multiplier: How Yvonne uses AI across operations and development to automate admin work, accelerate learning, and shorten build cycles.

Episode ID: 18799836-build-vs-buy-in-an-ai-first-world-with-yvonne-lau-hr-verticals-inc

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What if writing code isn’t actually the most important part of engineering?

In this episode of Futureproof, Prakash Chandran sits down with Aleksander Hakestad, CTO and co-founder at Apart Tech, to explore what it really takes to build software in an AI-native world without losing quality, craft, or control. Aleksander explains why the best leaders stay hands-on so they can evaluate quality, why depth of expertise beats climbing the career ladder, and why communication becomes the true bottleneck in modern engineering—especially across cultures and teams. Together, they unpack a pragmatic model for AI-assisted development where agents touch everything, humans own the architecture, and teams learn fast by setting clear standards, building tight feedback loops, and committing fully to a new way of working.

Topics covered include:

• AI-assisted development is still engineering: Why prompting is only the start—and disciplined iteration is what makes it reliable.
• Hands-on leadership and quality control: Why leaders must stay close enough to the craft to evaluate output and set the bar.
• Communication as the real bottleneck: How visual systems reduce misalignment across teams, languages, and cultures.
• From big teams to small, leveraged teams: How agentic workflows can create outsized throughput with a small core team.
• Depth over titles: Why mastering a domain matters more than career climb—and why expertise is more valuable than ever.

Episode ID: 18740056-ai-development-isn-t-an-easy-button-with-aleksander-hakestad-apart-tech

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What if your biggest AI advantage isn’t a model—it's how fast your team can learn together?

In this episode of Futureproof, Prakash Chandran sits down with Alfonso Quijano, CTO of Lean Solutions Group, to explore how Lean is becoming AI-ready by turning learning into a team sport. Alfonso explains how they create space for engineers to test new tools, teach each other what works, and build a culture where mentorship and experimentation fuel weekly shipping. Together, they unpack why speed comes from clarity and collaboration—not just new technology—and how leaders can design habits that help teams adopt AI confidently while staying grounded in real outcomes.

Topics covered include:

• Shared learning loops: How Lean creates internal sessions where engineers teach each other new tools and workflows.
• Weekly shipping as culture: Why fast MVP cycles and rapid iteration compound learning across teams.
• Hands-on leadership: How Alfonso builds trust by working alongside engineers and reinforcing experimentation.
• Tool experimentation with discipline: How Lean tests new vendors quickly while making deliberate long-term platform choices.
• Clarity over tooling: Why product thinking and communication—not shiny tech—ultimately determine velocity.

Episode ID: 18656694-building-an-ai-ready-team-with-alfonso-quijano-lean-solutions-group

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What qualities matter most for builders in an AI-native world?

In this episode of Futureproof, Prakash Chandran sits down with Karthik Puvvada (KP), Head of Community at Netlify, to explore how artificial intelligence is reshaping creation, careers, and community-driven growth. KP explains why the industry is moving away from rigid “developer vs. non-developer” labels toward a new divide of high-agency vs. low-agency builders, how AI is becoming a tutor and force multiplier, and why shipping real projects matters more than passive learning. Together, they make the case that we are entering an era of personal software, faster experimentation, and community flywheels where champions and curiosity determine who wins.

Topics covered include:

• High-agency builders: Why initiative and ownership now matter more than traditional credentials.
• AI as a learning engine: How models collapse skill gaps and accelerate cross-functional work.
• Shipping over tutorials: Setting concrete goals that force real-world iteration.
• Community as growth: Champion programs, authenticity, and “show, don’t tell” storytelling.
• The rise of personal software: Why n=1 apps may define the next wave of creation.

Episode ID: 18573101-high-agency-builders-personal-software-and-the-rebirth-of-developers-karthik-puvvada-netlify

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From Xano - The fastest way to create a production-ready backend for any app or agent. Xano unifies AI speed, code control, and visual clarity, so you never trade reliability for velocity. Sign up for free today.

Are engineering leaders asking the wrong questions when deciding what to build?

In this episode of Futureproof, Xano CEO Prakash Chandran talks with Chris Horn, SVP of Operations at Deriv, about what it takes to build AI inside a regulated, global software environment. Chris explains the difference between prototypes and proofs-of-concept, why data architecture is the real unlock, and how Deriv used a Shark-Tank-like model to introduce AI into internal operations. Together, they explore the mindset shift required for AI-native development — and why the most important question isn’t “Can we build it?” but “Should we build it?”

Topics covered include:

• Prototype vs. PoC: Why technical feasibility matters less than solving a real problem.
• AI as product work: The critical role of discovery, KPIs, and iteration in AI projects.
• Data as the foundation: How Deriv built a medallion architecture to get ready for AI.
• Internal AI first: Why customer-facing AI wasn’t the starting point (and what worked instead).
• Upskilling at scale: Building an AI-native culture through curiosity, training, and incentives.

Episode ID: 18501541-from-proof-of-concept-to-product-chris-horn-deriv

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From Xano - The fastest way to create a production-ready backend for any app or agent. Xano unifies AI speed, code control, and visual clarity, so you never trade reliability for velocity. Sign up for free today.

If AI becomes a creator, where do humans bring value to storytelling?

In this episode of Futureproof, Xano CEO Prakash Chandran talks with Sylvain Monterrey, founder and CEO of Animatix, an AI-powered film production platform used by leading advertising agencies and media studios. Sylvain shares his journey from fashion to AI — and explains how the creative production pipeline is being rebuilt on top of foundational models. Together, they explore what AI means for storytelling, why creativity still begins with humans, and how new workflows are transforming not just content creation — but company building itself.

Topics covered include:

• End-to-end creative pipelines in AI: Why the next era isn’t about standalone models — it’s about stitching them together so teams can go from brief to storyboard to finished film in a single workflow.
• AI as co-creator, not replacement: Technical barriers are collapsing, but the creative spark still comes from people — the message, meaning, and emotional arc.
• The rise of enterprise-grade AI filmmaking: Why big studios care about continuity, licensing, and digital actors — and how legal frameworks will shape adoption.
• AI-native organizational design: How team structure, roles, and product velocity change when everyone can build and iterate at real-time speed.
• Real-time personalization and the cultural question: Why “your own version of the movie” is coming — and why it could reshape culture, marketing, and identity.

Episode ID: 18454919-ai-and-the-future-of-creative-work-sylvain-montreuil-animatix

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What does it mean to be a builder in a time when AI can build all on its own?

In this episode of Futureproof, Xano CEO Prakash Chandran sits down with JJ Englert, founder of NoCode Alliance and community and education lead at Softr, creator, teacher, filmmaker-turned-builder, and a major voice in the no-code movement. JJ shares the unlikely journey from roofing to becoming a filmmaker, to finally discovering no-code — and now AI-powered coding. Together, they explore how AI is reshaping what it means to create software, why curiosity is becoming the most important developer skill, and how even seasoned engineers must adapt to avoid “legacy doubt.”

Topics covered include:

• The rise of the AI-literate builder: Why today’s advantage isn’t syntax — it’s understanding architecture, knowing what to ask, and working fluidly with AI as a coding partner.
• From no-code to full-stack with AI: How JJ went from “I don’t think I’m smart enough for this” to building full applications with real code in weeks, powered by no-code and, eventually, AI IDEs.
• The adoption gap inside companies: Why C-suites got excited, then cautious — and how organizations are slowly figuring out their AI-first vs. AI-layered strategies.
• Curiosity as survival skill: How both new makers and veteran engineers need the same thing: the willingness to experiment, learn, and challenge long-held assumptions.
• The future of multimodal computing: From personalized software that builds itself to real-time AR copilots — why the next leap goes far beyond chat.

Episode ID: 18356341-the-new-builder-mindset-jj-englert-nocode-alliance

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If AI can find the lead and write the email… what still separates the best GTM teams from everyone else?

In this episode of Futureproof, Xano CEO Prakash Chandran talks with Derek Evjenth, longtime go-to-market leader and current enterprise sales lead at Adobe, about what it really takes to build a successful GTM strategy in the age of AI. Derek draws on his journey from bootstrapped founder at Second Media to Salesforce enterprise rep, startup advisor, and now Adobe leader to explain why mastering fundamentals still beats chasing shortcuts. Together, they dig into how AI changes research and outreach, where human connection still wins, how to manage change inside sales orgs, and why maybe, just maybe, AI isn’t the secret to the last mile of selling. 

Topics covered include:

• Fundamentals over shortcuts: Why a clear sales process, ICP definition, and stage discipline matter more than any single AI tool.
• AI as a force multiplier, not a closer: How AI can collapse hours of research into minutes — but can’t replace real conversations, trust, and in-person connection.
• The new AI-literate seller: Why BDRs, SDRs, and AEs need prompt engineering, call recording, and data hygiene as part of their core skill set.
• Beyond the sale: How post-sale partnership, call insights, and customer success alignment turn wins into long-term, referenceable relationships.

Episode ID: 18298698-the-role-of-ai-in-gtm-derek-evjenth-adobe

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