Build What’s Next: Digital Product Perspectives

Method
  • 5.0 (6)
  • Tech News
  • Bimonthly

The process of developing digital products and experiences can be a daunting task organizations often find themselves wondering if they are solving the right problems the right way hoping the result is what the end user needs. That’s why our team at Method has decided to launch Build What’s Next: Digital Product Perspectives.Every week, we’ll explore ways to connect technology with humanity for a simpler digital future. Together, we’ll examine digital products and experiences, strategic design and product development strategies to help us challenge our ideas and move forward.

  1. Oct 13

    The AI Paradox: Why Faster Coding Isn't Solving Your Productivity Problem

    In this episode of Build What's Next, host Jason Rome is joined by Hersh Tapadia, Founder and CEO of AllStacks, to explore the real-world impact of AI-native software delivery. While AI tools have dramatically accelerated code generation for individual developers, many organizations are struggling to see those speed gains translate into overall business productivity and ROI. Jason and Hersh discuss: The AI Productivity Disconnect: Why individual efficiency gains don't automatically scale to team or organizational performance.Downstream & Upstream Bottlenecks: How rapid code generation shifts the strain to code reviews, QA testing, and product specification.The Three Pillars of a Great Spec: Why effective AI-assisted engineering requires narrative intent, experiential context ("vibes"), and strict acceptance criteria.Building a Context-Rich Harness: How to keep AI agents grounded in existing codebases and focused on actual product outcomes rather than just output.Tune in to learn how product and engineering teams can move past the hype and build a scalable framework for AI-enabled delivery. Subscribe and Follow: Don't miss an episode—subscribe to Build What's Next for weekly deep dives into digital product perspectives. Check out more resources and tech talks at method.com. Episode Resources: Jason Rome on LinkedIn: /jason-rom-275b2014 Hersh Tapadia on LinkedIn: /in/hershtapadia Method Website: method.com Allstacks Website: allstacks.com

    The AI Paradox: Why Faster Coding Isn't Solving Your Productivity Problem

  2. Sep 16

    The AI Shift: Rethinking ROI and Product Fluency in the Enterprise

    Is the "SaaSpocalypse" here, or is the industry just getting started? In this episode of Build What's Next, host Jason Rome is joined by Ken Yagen, Principal and Operating Executive at Norwest, to explore the seismic shifts happening in software engineering and product development. Ken shares his pragmatic, "on-the-ground" perspective on the transition from AI copilots to agentic coding and the imperative for teams to pivot toward a systems-thinking mindset. We dive deep into the new financial realities of the AI age—specifically how product teams are adopting "FinOps" roles to manage token costs—and discuss why "token-per-unit-of-value" is the new metric for ROI. Key Topics Covered: The Shift to Agentic Workflows: Moving beyond simple assistance to specialized, loop-based engineering agents.Token Economics & ROI: How to treat tokens as investment capital and avoid the "token-maxing" trap.The Evolving Product Manager: Why domain expertise, AI fluency, and rapid prototyping are the new "must-have" skills.Modernizing SaaS: How companies can reinvigorate legacy products, leverage data moats, and build durable, outcome-oriented software in an AI-first world.Whether you're a product leader, a systems engineer, or just trying to navigate the rapid pace of change in the enterprise, this conversation offers actionable insights on building more effectively in the AI era. Subscribe and Follow: Don't miss an episode—subscribe to Build What's Next for weekly deep dives into digital product perspectives. Check out more resources and tech talks at method.com. Episode Resources: Jason Rome on LinkedIn: /jason-rom-275b2014 Ken Yagen on LinkedIn: /in/kenyagen Method Website: method.com Norwest Website: norwest.com

    The AI Shift: Rethinking ROI and Product Fluency in the Enterprise

  3. Aug 11

    The AI Development Lifecycle: How to Thrive in the SaaS Apocalypse

    Code is getting easier to produce, but the cost of building the wrong thing is about to get louder. Jason Rome sits down with Cory Voglesonger, Chief Product and Technology Officer at Aaron's, to unpack what’s actually changing as teams move toward AI-native delivery and an AI development lifecycle filled with coding agents and agentic workflows. We use Cory’s culture framework safety, clarity, urgency as a simple way to diagnose why some teams thrive with AI while others drown in noise. Urgency is not “move fast at all costs.” It is outcome thinking: knowing what business result you’re chasing, measuring it, and avoiding the trap of shipping a mountain of features just because AI makes output cheap. We also dig into why lean thinking, flow, and the basics of continuous delivery still matter, plus how a solid developer experience with a golden path and standard toolchain prevents AI-driven sprawl. Clarity is where AI turns the dial up to 1000. When you’re directing humans and eventually armies of agents, the work lives or dies on context engineering: guardrails, constraints, domain knowledge, and clear intent. We talk about getting closer to users, making knowledge less tribal, and using AI as adviser, assistant, and adversary to challenge bias, stress test ideas, and sharpen decisions before production feedback takes time. Safety closes the loop, from psychological safety around job fears to environmental safety around customer data and blast radius. If you want your team to adopt AI without burnout, this is the leadership work. Subscribe, share this with a teammate, and leave a review with the culture lever you’re focusing on next. Episode Resources: Jason Rome on LinkedIn: /jason-rom-275b2014 Cory Voglesonger on LinkedIn: in/cory-voglesonger-81907628 Method Website: method.com The Aaron’s Company Website: aarons.com

    The AI Development Lifecycle: How to Thrive in the SaaS Apocalypse

  4. Jul 9

    AI Only Helps When You Know Which Hill to Climb

    AI is everywhere, yet most teams still feel stuck between exciting demos and messy reality. Jason Rome sits down with Jon Webster, Chief Operating Officer at CPP Investments, to pressure test what has truly changed since their last conversation and what has not. We talk candidly about why generative AI adoption is starting to look like every other enterprise technology rollout: uneven, political, constrained by governance, and full of “we bought the licenses but we do not have the use cases” moments. We dig into the economics behind the hype: token pricing, subsidised plans, and why clear price signals matter if you want real ROI from enterprise AI. When AI feels cheap, sprawl is rational. When prices rise, leaders have to prioritise, measure outcomes, and decide where AI belongs in the operating model. From there we explore the human risks and skills that get exposed fast, including cognitive load, over-reliance, and the growing divide between people with strong mental models and those who skip straight to prompting. The conversation also goes deep on practical ways to work better: owning your outline before you generate, using AI as an adversary to challenge your thinking, and borrowing frameworks from great strategy writing to choose the right “hills to climb.” We close with predictions on where the next nine months may go, from more disciplined optimisation to shifts in SaaS, systems of record versus systems of action, and the leadership balance between IQ gains and EQ and empathy. If you found this useful, subscribe so you do not miss the follow-up, share it with a teammate who is wrestling with AI adoption, and leave a review with the most valuable AI habit you have learned so far. Jason Rome on LinkedIn: /jason-rom-275b2014 Jon Webster on LinkedIn: /in/jrwebster Method Website: method.com CPP Investments Website: cppinvestments.com

    AI Only Helps When You Know Which Hill to Climb

  5. May 4

    AI Field Guide: The Missing Middle - How to Build an End-to-End AI

    In this episode of Build What's Next, Theo Munoz, Miguel Ribeiro, and Natan Szczepaniak discuss Machine Learning Operations (MLOps) and why an estimated 80% of ML models built in notebooks never make it to production. The hosts argue that the failures stem less from technology and more from organizational issues like a lack of clear ownership, insufficient investment in data engineering, and poor data foundations. Learn how standardization, shared ownership between business and engineering, and robust model governance are crucial to scaling AI safely, especially as the industry shifts towards Gen AI. To find more episodes, visit method.com/insights/podcasts/ Episode Resources:  Method.com Theo Munoz on Linked-In: /in/theo-munoz-090a88151/ Miguel Ribeiro on Linked-In: /in/miguel-ribeiro-3439328a/ Natan Szczepaniak on Linked-In: /in/natan-sz/

    AI Field Guide: The Missing Middle - How to Build an End-to-End AI

  6. Mar 24

    AI Field Guide: How AI is Reshaping the Roles of Design and Engineering

    AI is reshaping the roles of design and engineering, emphasizing collaboration and how models can accelerate workflows without sacrificing quality. This week’s episode explores how designers like David Shackelford, Associate Director of Product Design for Method, use tools like Perplexity, UX Pilot, and Figma Make for rapid exploration, while Paul Rowe, Principal Software Engineer at Method, discusses the engineering reality check with tools like Claude Code and Google’s Anti-Gravity IDE. The key takeaway is a practical playbook for speed with guardrails, affirming that human judgment, taste, and accountability remain the multiplier. The Methodites cover where AI currently shines—producing accurate results for smaller, well-defined tasks—and where it struggles, often leading to code bloat and confusion with vague prompts, especially within massive enterprise codebases. Despite the excitement around "vibe coding," they stress that the core development workflow remains "build, validate, iterate," with human review being more critical than ever. Paul and David conclude that while AI is an efficiency tool that can blur traditional departmental lines and shift where time is spent, strategic roadmapping, quality assurance (QA), and deep, expert-level skill sets in both design and engineering are still indispensable. To find more episodes, visit method.com/insights/podcasts/ Episode Resources:  Method.com David Shackleford on Linked-In: /in/davidzshackelford/ Paul Rowe on Linked-In: /in/paulcullenrowe/

    AI Field Guide: How AI is Reshaping the Roles of Design and Engineering

  7. Mar 4

    How To Build A Scalable, Standards-Aligned Ecosystem That Teachers Actually Use

    Travis Barrs of Discovery Education discusses how K–12 is shifting from tool access to learning impact, focusing on building scalable, coherent learning platforms. This involves budget realities, teacher workloads, and consolidating tool sprawl. Key points include the return of core curriculum funding, the necessity of standards alignment, and balancing Discovery's diverse brands (DreamBox Learning, Mystery Science, etc.). The underlying architecture emphasizes seamless identity/access, roster sync, LMS integrations, and cross-product analytics for targeted student support. Organizational design uses a "quartet" model—product, design, engineering, and curriculum—to embed pedagogy and rigor from the start. AI implementation follows a measured roadmap, prioritizing teacher workflows (lesson planning, assessment, recommendations) before student-facing tools with strong guardrails. Internally, AI aids in prototyping, documentation, sales, RFPs, contract review, and curriculum drafting, all under strict governance. The future is focused on hyperpersonalization, workload-reducing classroom assistants, and provable efficacy. To find more episodes, visit method.com/insights/podcasts/ Episode Resources:  Method.com Travis Barrs on Linked-In: /in/travisbarrs/ Carol Rego on Linked-In: /in/carol-rego/ More episodes: method.com/insights/podcasts/

    How To Build A Scalable, Standards-Aligned Ecosystem That Teachers Actually Use

  8. 12/10/2025

    AI in Software Development: Designing & Delivering Real ROI

    Forget the AI hype and focus on real ROI in the Software Development Lifecycle (SDLC). This episode features Method's Jason Rome and Raj Sethi with ISG experts Ashwin Gaidhani and Tapati Bandopadhya, who trace a clear path from AI tools to measurable outcomes. They argue that coding speed isn't the bottleneck—specs, testing, pipelines, and change management are. We break down the mechanics of ROI: how specification elaboration unlocks downstream gains, the decision between human-in-the-loop vs. agent-in-the-loop, and integrating GenAI into CI/CD. We also discuss cost, risk-adjusted ROI (F1 score plus risk), and practical wins for legacy modernization, like AI-driven requirement discovery and service-oriented modernization. The conversation also introduces 'stability lanes' and covers what leaders get wrong (tooling without process change, microservices by default), advocating instead for platform thinking and a conductor's mindset to orchestrate micro-tasks for real lift. Episode Resources: Jason Rome on LinkedIn: /jason-rom-275b2014 Raj Sethi on LinkedIn: in/rajsethi Ashwin Gaidhani on LinkedIn: in/ashwin-gaidhani Tapati Bandopadhya on LinkedIn: in/tapatibandopadhyay Method Website: method.com GlobalLogic Website: globallogic.com ISG Website: isg-one.com

    AI in Software Development: Designing & Delivering Real ROI
See All (48)

Ratings & Reviews

5
out of 5
6 Ratings

About

The process of developing digital products and experiences can be a daunting task organizations often find themselves wondering if they are solving the right problems the right way hoping the result is what the end user needs. That’s why our team at Method has decided to launch Build What’s Next: Digital Product Perspectives.Every week, we’ll explore ways to connect technology with humanity for a simpler digital future. Together, we’ll examine digital products and experiences, strategic design and product development strategies to help us challenge our ideas and move forward.

Information

You Might Also Like