The Tech Trek

In this episode, Jeremy Whittington shares his journey of building a startup without relying on traditional venture capital. Instead, he leveraged alternative funding paths, including government grants and accelerators. We dive deep into the Small Business Innovation Research (SBIR) program, the I-Corps program, and how startups can secure non-dilutive funding to kickstart their business. If you're an entrepreneur looking for funding beyond VC, this episode is for you!Key Takeaways:🔹 SBIR Grants Can Fund Your MVP – The SBIR program provided Jeremy’s startup with $1.9M in non-dilutive funding, allowing them to build a prototype before taking on traditional investment.🔹 Government Funding Has Strings Attached – While the money is great, it comes with paperwork, strict reporting, and compliance requirements—be prepared for documentation!🔹 Accelerators Expand Your Network – Programs like Capital Factory and Deutsche Telekom’s hubraum helped Jeremy's team connect with investors and industry partners.🔹 Customer Discovery is Critical – Through the I-Corps program, Jeremy discovered that their original idea wouldn’t work commercially and pivoted to a more lucrative market segment.🔹 Alternative Funding Works Best for Certain Startups – If your company aligns with government priorities (e.g., cybersecurity, defense, healthcare, finance), alternative funding can be a game-changer.Timestamped Highlights:⏳ [00:02:00] – Jeremy introduces Illuma and how they developed voice biometrics for fraud prevention.⏳ [00:03:40] – How Jeremy’s co-founder discovered the SBIR program while researching funding options.⏳ [00:06:30] – The SBIR application process and how the phase-based funding structure works.⏳ [00:08:55] – Why alternative funding isn’t well known and how startups can find relevant grants.⏳ [00:11:20] – The challenges of working with government funding—compliance, reporting, and restrictions.⏳ [00:14:00] – How I-Corps helped them pivot from securing government cell phones to working with financial institutions.⏳ [00:18:00] – Jeremy’s experience with accelerators like Capital Factory & hubraum and how they helped with industry connections.⏳ [00:21:06] – Would Jeremy take alternative funding again? His take on SBIR vs. VC for early-stage startups.⏳ [00:24:38] – Final thoughts: Advice for entrepreneurs exploring alternative funding paths.Quote of the Episode:"If you want to start a company but don’t have a financial cushion, alternative funding—like SBIR grants—can help you quit your job and focus without giving up equity." – Jeremy WhittingtonResources & Links:🔗 SBIR Program – https://www.sbir.gov🔗 I-Corps Program – https://www.nsf.gov/i-corps🔗 Connect with Jeremy on LinkedIn – https://www.linkedin.com/in/jeremywhittington/Enjoyed this episode?✅ Subscribe to The Tech Trek for more insights on startup funding & technology leadership!✅ Follow Amir Bormand on LinkedIn for future episode updates.✅ Leave a review and let us know what you think!🎙️ New episodes drop weekly – stay tuned!

In this episode, we dive into blurring engineering lines, full-stack engineering, and the evolving role of software engineers in a rapidly changing landscape. Sahil shares insights on how generative AI is reshaping engineering, the shift towards problem-solving over-specialization, and how teams can optimize for speed and business value.Key Takeaways:🔹 Blurring Engineering Roles: Traditional engineering roles (frontend, backend, DevOps) are blending, leading to more end-to-end ownership. Engineers who can span the stack and understand business impact are becoming more valuable.🔹 The Power of Problem-Solving: As AI tools handle more code generation, the real skill will be problem formulation—defining problems correctly will matter as much as solving them.🔹 Generative AI’s Impact: AI-powered tools are shifting software development leftward—catching security issues, automating QA, and assisting in DevOps before code even leaves the IDE.🔹 Optimizing for Speed & Business Value: Small, autonomous teams with full ownership tend to deliver higher impact faster than large, interdependent teams.🔹 The Future of Software Engineering: Despite concerns about AI replacing coding jobs, the demand for software engineers will increase, not decrease. The job will evolve, with natural language-based programming replacing traditional syntax-based coding.Timestamped Highlights:⏳ [00:00:00] Introduction – Sahil Maheshwari joins the show to discuss blurring engineering lines and its impact on speed and value.⏳ [00:01:09] Full-Stack Engineering Revisited – Why the traditional boundaries between frontend, backend, and DevOps are disappearing.⏳ [00:03:40] Generative AI and Engineering Autonomy – How AI-powered tools are enabling engineers to work across disciplines.⏳ [00:06:57] Measuring Business Value & Speed – What are the right metrics to track speed and efficiency in engineering teams?⏳ [00:08:59] Shift Left Engineering – Why engineers need to be closer to the problem and the customer to deliver the most value.⏳ [00:12:11] AI & Developer Productivity – Real-world examples of how AI is making engineers more efficient.⏳ [00:17:00] The Evolution of Software Engineering – Will engineers still be writing code in the future, or will AI handle it all?⏳ [00:22:37] Ideal Team Structures – Why small, autonomous teams drive the most business value.⏳ [00:27:02] Decision-Making in Engineering – The importance of reversible vs. irreversible decisions in technology strategy.Quote from the Episode:"The most valuable engineers won't just be the best coders—they'll be the best at defining the right problems to solve." – Sahil MaheshwariConnect with Sahil Maheshwari:🔗 LinkedIn: Reach out to Sahil on LinkedInEnjoyed the Episode?📩 Share it with your colleagues in engineering & tech leadership!⭐ Subscribe & leave a review to help others discover the show.🗣️ Continue the conversation – Drop a comment or reach out if you have thoughts or questions!

In this episode, we dive into the evolving role of engineering leadership with Andy Elmhorst, VP of Engineering at Bolt. We explore the delicate balance between delegation and hands-on leadership, dissect the founder mode philosophy, and analyze how servant leadership has been interpreted—and sometimes misapplied—in tech organizations. Andy shares insights on why traditional management books may be outdated for modern engineering leadership, and how staying hands-on with teams can drive better problem-solving and business outcomes.Key Takeaways🚀 Founder Mode Explained – A leadership approach where managers work alongside teams, not just delegate.📚 Are Management Books Outdated? – Why classic leadership principles may not fully apply to fast-moving engineering teams.⚖️ The Balance Between Delegation & Hands-On Leadership – Knowing when to be involved and when to step back.🛠 Servant Leadership: Misunderstood? – Andy challenges common interpretations and explains how coaching, not just empowering, is key.🔄 Tech Leaders Must Stay Close to the Work – How maintaining technical depth can make engineering leaders more effective.💡 The Impact of AI on Leadership – Will AI shift engineering leaders into more business-focused problem solvers?Timestamped Highlights🕒 [00:01:00] – Andy introduces Bolt and how their accelerated checkout technology works.🕒 [00:02:30] – Why traditional management books don’t fully capture the realities of modern software engineering.🕒 [00:03:47] – Founder mode vs. bureaucratic mode: What’s the difference?🕒 [00:06:00] – The rise (and potential pitfalls) of servant leadership in tech.🕒 [00:10:40] – Football coaches vs. engineering leaders: The art of guiding teams without being absent.🕒 [00:15:00] – Push vs. pull leadership: How leaders can choose when to get involved.🕒 [00:20:40] – Do AI and automation change the role of an engineering leader?🕒 [00:26:30] – Andy’s non-traditional career journey—from VP back to IC and back again.🕒 [00:34:35] – Final thoughts: Why leaders must always be learning and evolving.Quote of the Episode"Leadership is presence, not absence. The best managers don’t just delegate problems—they solve them together with their teams." – Andy ElmhorstConnect with Andy🔗 LinkedIn:Andy Elmhorst✍️ Blog:compiling.enstaria.comJoin the Conversation!📢 If you enjoyed this episode, share it with your network! What are your thoughts on founder mode vs. servant leadership? Let’s discuss—leave a comment or message Amir on LinkedIn!🎧 Subscribe & Stay Updated:Like, follow, and rate the podcast to never miss an episode!

In this episode,Sasha Bartashnik shares her insights on howlarge language models (LLMs) are transforming the development ofdata products, making advanced AI-driven solutions moreaccessible and scalable. We dive into thechallenges of traditional data tools, theadvantages and risks of LLM integration, and how businesses shouldadapt to the changing landscape of AI-driven decision-making.Key Takeaways🔹What Are Data Products? – Any software that processes or surfaces data to users, including dashboards and AI-powered insights.🔹Challenges in Building Data Products – Team complexity, data quality, and model training require specialized knowledge and resources.🔹How LLMs Help – They speed up development, make AI-driven insights more accessible, and improve data cleaning and structuring.🔹Risks and Limitations – Accuracy concerns, hallucinations, and over-reliance on AI-generated outputs require human oversight.🔹Changing Stakeholder Expectations – Faster and more scalable data solutions raise business expectations for AI-driven insights.🔹Where to Start with LLMs? – Safer applications likeinternal chatbots before tackling complex structured data analysis.Timestamped Highlights📌[00:00] – Introduction to Sasha Bartashnik & Vendelux’s role in event intelligence📌[01:25] – Defining what a "data product" really means in the AI-driven era📌[03:00] – Key challenges in building scalable data products📌[06:45] – The impact of traditional data tools and their limitations📌[07:54] – How LLMs accelerate development and improve AI-driven insights📌[10:00] – Risks of LLMs: Accuracy concerns, hallucinations, and human oversight📌[14:18] – The evolving role of data engineering teams with LLMs📌[17:31] – Where should businesses start when implementing LLMs?📌[22:00] – The responsibility of AI builders in ensuring data accuracy and transparency📌[23:43] – How to connect with Sasha for more insightsQuote of the Episode"LLMs are not a silver bullet. They don’t replace humans; they just shift where expertise is needed." –Sasha BartashnikConnect with Sasha🔗 LinkedIn: Sasha Bartashnik🎧Enjoyed this episode?Subscribe, leave a review, and share it with someone exploring LLMs in data products! 🚀

In this episode, we dive into the evolution of theChief Product and Technology Officer (CPTO) model, the blending of traditional engineering and product roles, and howAI, hackathons, and shifting org structures are reshaping product development. Arjun shares insights on what this means for engineers, product managers, and leadership teams, as well as the challenges of making this shift successful.⏳ Timestamped Highlights[00:00] IntroductionAmir introduces Arjun Shah and sets the stage for discussing the CPTO model.[00:01] The Traditional Product Development ModelBreakdown of theclassic trifecta: product management, design, and engineering.How Agile shaped product teams over the last two decades.[00:02] The Shift to a More Integrated ModelWhy companies are moving away from rigid role definitions.Engineers taking on user research, designers coding, and product managers prototyping.[00:04] What is the CPTO Model?Defining theChief Product and Technology Officer role.Examples of companies making this shift.How CPTO improvesstrategy execution and alignment.[00:06] The Impact on Engineers & ICsEngineers expected to care aboutbusiness outcomes, UX, and customer needs.Squadron model vs. Scrum model – how AI-driven teams are changing the landscape.New hiring criteria:product sense, entrepreneurial mindset, and data analytics.[00:08] Measuring Success in the CPTO ModelHow do you know if the CPTO model is working?R&D metrics:velocity, alignment, and strategic impact.[00:10] Hackathons: The Canary in the Coal Mine?The role of hackathons inbreaking down barriers between product and engineering.How great features and products have emerged from hackathons.[00:14] AI’s Role in Accelerating the CPTO ModelAI blurring functional lines and enablingfaster product iteration.Why "everyone is a developer" in the age ofLLMs and code generation tools.[00:16] Risks & Failure Points of the CPTO ModelThe biggest challenge:finding the right leader for the CPTO role.Potential pitfalls:misalignment of product vs. engineering goals, poor org design.How tostructure squads and teams for success under a CPTO.[00:19] The Right Person for the CPTO RoleDo you need to be afounder to succeed as a CPTO?Why curiosity,cross-functional expertise, and product acumen are essential.[00:22] Final Thoughts & How to Connect with ArjunFollow Arjun Shah on LinkedIn for more insights on product and engineering leadership.🏆 Key Takeaways💡The product and engineering roles are merging. Engineers today are expected to think like product managers, and PMs must understand technology.🚀The CPTO model is gaining traction. Companies are moving away from separate CPO and CTO roles in favor of a unified leader todrive better alignment and execution.⚡AI is changing product development. Large language models and AI-driven tools are enabling anyone to prototype, reducing barriers between roles.🔎Finding the right CPTO is challenging. The role requiresbusiness acumen, technical expertise, and product strategy skills—a rare combination.🎯Hackathons are an early signal. Engineers experimenting with new ideas and taking on product roles during hackathons may hint at the future of team structures.🗣️ Quote of the Episode“The new programming language is English. With AI, everyone can be a developer.” – Arjun Shah🎧Enjoyed the episode?✅ Subscribe for more insights on the evolving world of tech and product development.💬 Share your thoughts in the comments or on social media!🔗Connect with Arjun Shah on LinkedIn: https://www.linkedin.com/in/arjunshah/.

In this episode, JD Williams joins Amir Bormand to dive into the critical role ofchange management in driving successful digital adoption. From leading with digital fluency to navigating organizational change for AI integration, JD shares actionable insights from his work at Zoetis.Key TakeawaysDigital Fluency Starts with People:Training needs to be role-specific and practical.Peer-to-peer learning fosters deeper adoption across teams.Change Management is a Team Effort:Success requires both top-down support and grassroots enthusiasm.AI champions in different regions help scale efforts effectively.Rethinking ROI in AI Adoption:Focus onhours gained rather than hours saved.Establish CFO-certified metrics to measure value and demonstrate ROI.Integrating Change Management Early:Include change management planning from the proof-of-concept stage.Prioritize initiatives that are both technically and operationally feasible.Storytelling is Key for Leadership:Data leaders must communicate AI's value across diverse business functions.Timestamped Highlights[00:01:03] JD introduces Zoetis and its global role in animal health.[00:02:04] Defining digital fluency and how Zoetis integrates AI into workflows.[00:04:34] The three pillars of digital transformation: people, process, and technology.[00:06:14] Leveraging AI champions for grassroots adoption.[00:10:00] The importance of process mapping to identify change impacts.[00:14:53] Measuring AI’s ROI: hours gained, accelerated R&D timelines, and improved sales tools.[00:19:10] Injecting change management into strategy from the start.[00:21:38] How storytelling helps leadership align on AI's value.Memorable Quote"Change management isn't just a top-down directive; it's about enabling and empowering individuals across the organization to embrace and drive innovation." – JD WilliamsConnect with JD WilliamsLinkedIn: JD WilliamsFollow JD for insights on digital adoption, AI, and data-driven leadership.

In this episode ofThe Tech Trek, Amir Bormand sits down with Stephen Harris, former Corporate Vice President of Global Data Science and Growth Analytics at Microsoft. Steffen, a seasoned data executive with over 30 years of experience, shares insights into tackling foundational data issues, addressing data debt, and integrating advanced AI strategies. Together, they explore how businesses can move the needle on long-standing challenges and position themselves for sustainable growth in a data-driven world.Key TakeawaysFoundational Data Challenges: Many enterprises struggle with defining and managing core data assets such as customer and product data, often resulting in inefficiencies and missed opportunities.Data Debt: Short-term wins in data management can lead to long-term complications. Addressing data debt requires balancing immediate needs with sustainable strategies.AI as a Catalyst: Generative AI and machine learning can help identify gaps, streamline processes, and improve data quality, but they must align with business goals to maximize ROI.Parallel Solutions: Digital transformation and AI strategies should run on parallel tracks, emphasizing quick wins while developing a cohesive long-term roadmap.Stakeholder Engagement: Effective communication and tailored problem-solving are essential when advocating for foundational data investments to stakeholders.Highlighted Timestamped Moments[00:00:21]: Introduction to foundational data issues and their role in enabling advanced technologies like generative AI.[00:02:05]: Steffen shares insights from his time at Wells Fargo and VMware, discussing challenges in mastering customer and product data.[00:09:29]: Exploring the concept of data debt and its implications for short-term wins versus long-term sustainability.[00:14:58]: Leveraging AI to assess and address foundational data gaps and enhance decision-making.[00:23:54]: The evolution of digital transformation and the rise of interconnected challenges like cybersecurity and cloud integration.[00:29:08]: Strategies for presenting long-term data solutions to stakeholders and prioritizing fixes for maximum business impact.Quote of the Episode"Stop, pause, reflect, and reimagine the opportunity. Quick wins today can fuel long-term strategies tomorrow." – Stephen HarrisConnect with Stephen HarrisLinkedIn: Stephen Harris

In this episode, Amir Bormand is joined by Marty Kausas, Co-founder and CEO of Pylon, a groundbreaking customer support platform for B2B companies. Marty shares his journey of navigating "pivot hell," the challenges of ideation, finding the right co-founders, and understanding what it takes to build a billion-dollar company. Whether you're an aspiring entrepreneur or a seasoned professional, this episode is packed with insights on creating, evolving, and scaling a tech startup. Key Takeaways: The Ideation Journey: Startups often require multiple pivots before discovering a viable product-market fit. Co-founder Chemistry: Aligning goals, skillsets, and hustle is crucial for long-term success. Big Market Thinking: Even niche solutions can thrive when embedded in expansive markets. Unicorn Realities: Building a billion-dollar company demands focus, persistence, and adaptability. Founder Fitness: Maintaining personal resilience is as critical as business execution. Timestamped Highlights: [00:00:00] Introduction to Marty Kausas and Pylon’s mission. [00:01:00] From Airbnb software engineer to entrepreneur: Marty’s background and startup motivation. [00:02:55] Lessons learned from early ideas and the struggles of healthcare and nonprofit markets. [00:05:12] Decoding product-market fit and total addressable market (TAM) for startup success. [00:06:31] The importance of choosing the right co-founders for adaptability and growth. [00:13:49] "Find a niche in a big market" – Balancing focus and scalability. [00:16:18] Insights into unicorn companies and the pressures of achieving high valuations. [00:23:26] How Marty decompresses and stays motivated amidst the demands of entrepreneurship. [00:26:00] How to connect with Marty and his final thoughts on startup growth. Quote of the Episode: "The worst-case scenario isn't failure—it's becoming a 'zombie company' that can't grow or sell. Momentum is everything." – Marty Kausas Links and Resources: Connect with Marty on LinkedIn Email Marty at: marty@usepylon.com Learn more about Pylon: usepylon.com Share the Knowledge: If you found this episode insightful, share it with your network and tag us! Don’t forget to like, subscribe, and leave a review on your favorite podcast platform. Let us know your thoughts and what topics you'd like to hear next.

In this episode, Tanaz Mody shares insights on the hiring struggles founders face as they scale their companies. We explore how founders navigate the decision-making process, overcome hiring hesitations, and transition from being hands-on operators to strategic leaders. Key Topics:✅ The weight of hiring decisions on founders✅ How founders can avoid “decision paralysis” in hiring✅ The evolution from founder to CEO✅ The role of VC talent partners in scaling startups✅ When (and why) founders should consider executive coaching 🎯 Key Takeaways 💡 Hiring Delays = Growth DelaysIf a founder keeps postponing hiring, it could be a sign that they aren’t ready—or that they haven’t clearly defined what they need. Setting milestones helps avoid an endless search. 💡 Letting Go is Hard, But NecessarySuccessful founders evolve their roles. Holding onto every function prevents company growth. Hiring isn’t just about filling a role—it’s about scaling leadership. 💡 Decisions Made Late Are Still DecisionsA decision avoided today can become a crisis tomorrow. Founders must recognize that delaying hiring (or any critical choice) will eventually force a decision under less favorable conditions. 💡 There’s No “One-Size-Fits-All” PlaybookBest practices are useful, but every startup is unique. Founders must build teams that align with their specific needs, not just industry templates. 💡 Coachability MattersSome founders struggle with external advice. The key is finding the right voice that resonates and helps them pivot their perspective. 🕒 Timestamped Highlights ⏳ [00:01:00] – Introduction to Tanaz and her role at Lerer Hippeau⏳ [00:02:30] – Why hiring is one of the hardest decisions for founders⏳ [00:05:00] – The danger of founders being too involved in hiring⏳ [00:08:30] – How delaying hiring can indicate deeper problems⏳ [00:12:00] – The importance of outside coaching for founders⏳ [00:16:00] – Trusting teams and evolving leadership skills⏳ [00:20:00] – Why the “operator” mindset in people teams is changing 💬 Quote Worth Sharing "Your company won’t grow if you don’t. If you’re still doing the same job as a founder that you did six months ago, you’re holding the business back." – Tanaz Mody 📢 Connect with Tanaz Mody 🔗 LinkedIn: Tanaz Mody 🎧 Enjoyed this episode?Like, subscribe, and share with someone who needs to hear this! 🚀

In this insightful episode, James Evans dives into the unique challenges and growth opportunities for first-time founders. From building leadership styles to navigating tough decisions, James shares his journey and valuable lessons from leading CommandBar to its acquisition by Amplitude. If you're a tech enthusiast, startup founder, or aspiring entrepreneur, this episode is packed with actionable takeaways! Key Takeaways Leadership Style Evolves Over Time: As a first-time founder, leadership is a learning process; it’s okay to admit you’re still refining your style. Authenticity is crucial—your actions must align with your leadership claims. Decisions Matter, but Not All Are Equal: Overthinking can paralyze growth. Some decisions, like choosing a CRM, don't need innovation—pick a functional solution and move forward. Prioritize building a team culture that aligns with long-term company goals. The Importance of Early Employees: The first ten hires shape the company’s culture more than the founders. Be intentional about hiring individuals who embody the values you want to amplify. Seek Advice From Experienced Founders: Establish a network of mentors who are 1–2 steps ahead in their entrepreneurial journeys. Tactical advice from seasoned founders can save you months (or years) of missteps. Redefining Product-Market Fit: True product-market fit feels effortless—customers want your product, not just your team or service. Timestamped Highlights [00:00:00] Introduction to James Evans and the topic of first-time founders. [00:01:08] Defining and discovering leadership style as a founder. [00:04:23] What candidates really look for in a founder's leadership style. [00:06:38] Aligning leadership style with company culture. [00:11:00] The impact of early employees on company culture and growth. [00:16:00] Avoiding decision paralysis as a first-time founder. [00:17:18] Finding and leveraging founder mentors. [00:22:00] Product-market fit: Lessons and red flags for first-time founders. Quote of the Episode "As a startup, you should seek to innovate as little as possible—focus your creativity on what truly matters, like your product or distribution strategy." — James Evans Connect with James Evans Podcast LinkedIn: James Evans X: @JamesEvans Support The Tech Trek If you enjoyed this episode: Share it with friends or colleagues interested in startups and leadership. Subscribe to The Tech Trek for more insightful conversations with tech leaders. Leave a review and let us know your favorite takeaways!