For more on building AI products and careers, along with early course announcement and special pricing, subscribe to the AI Career Boost mailing list at https://aicareerboost.com/interested

THE GUEST

Sudha Kumar is a powerhouse product leader who thrives at the intersection of data, compliance, and user impact. With more than a decade of experience scaling B2B SaaS platforms and modernizing federal IT systems, she has delivered measurable outcomes across sectors, from accelerating healthcare audits by 30% to driving product revenue across more than 50 companies. Known for her ability to simplify complex workflows without sacrificing rigor, Sudha brings deep technical fluency and a sharp sense of user empathy to every challenge. Now focused on shaping the next generation of AI-powered enterprise tools, she is dedicated to advancing system compliance, reliability, and trust in the AI age.

THE SUMMARY

Data is the real truth-teller in product work — The conversation emphasises that users rarely behave the way product teams expect. Data becomes the only reliable signal to understand real usage patterns and close the gap between intention and reality.

Technical fluency massively elevates a PM’s impact: Being able to query raw logs, validate theories, and guide engineering with precision turns a PM into a high-leverage operator—especially in platform roles, where hidden complexity and technical debt drive long-term success or failure.

Compliance is an AI goldmine: Compliance work is repetitive, high-stakes, and deeply dependent on human interpretation. Automating the mapping of findings to regulatory standards shows immediate value, especially when errors can trigger hospital shutdown risks.

AI performance reflects the clarity of the human behind it: Iterating on prompts, supplying examples, and defining rules tightly is what improves accuracy. AI only becomes “smart” when the PM is intentional, structured and thorough with the inputs.

Data harmonisation is the hidden prerequisite for real AI adoption: At Renovo, six companies with six definitions for basic concepts made clear that most AI problems are data problems. Without consistent definitions and clean context, AI becomes a guessing machine—not a reliable system.

Mindset is the real barrier to entering AI, not skill: Sudha describes the early fear of being “left behind” and how the shift happened when she realised AI is a partner that frees PMs from tactical noise so they can do the strategic work they’re actually paid for.

Feeling behind means you’re already ahead: The episode closes on a strong, counterintuitive insight: the moment you worry you’re behind is the moment you’ve already started moving. Diving in early, experimenting, and iterating is the real differentiator.

THE SHOW

Weekly conversations with the AI’s top product leaders. Join Polly Allen as she discovers the paths to success in the world of AI.

THE LINKS

Have a question you want us to answer? Send it through to support@aicareerboost.com

Sudha Kumar

LinkedIn: https://www.linkedin.com/in/sudhadkumar

My links

LinkedIn: ⁠https://www.linkedin.com/in/pollymallen/⁠

AI Career Boost: ⁠https://www.aicareerboost.com/⁠

For more on building AI products and careers, along with early course announcement and special pricing, subscribe to the AI Career Boost mailing list at https://aicareerboost.com/interested

THE GUEST

Taylor Algren is a product leader, founder, and strategist with over a decade of experience tackling real-world challenges at the intersection of tech, health, and global operations. He’s launched scalable platforms, advised early-stage startups, and brings a unique mix of systems thinking and human-centered design to every project. Now building a stealth-mode AI health-tech startup focused on chronic disease care, Taylor is known for his execution, mentorship, and commitment to meaningful, equitable innovation.

THE SUMMARY

Impact starts with lived experience — and this founder proves it. The episode dives into how years navigating the healthcare system as a cardiomyopathy patient revealed just how broken, bureaucratic, and non-human-centric chronic disease care really is. The constant cycle of refills, prior authorisations, pharmacy stock outages, and insurer rules creates a system that pushes patients to give up — at the cost of their long-term health.

AI isn’t a buzzword here — it’s a survival tool: The conversation highlights how agentic AI can step into the administrative chaos patients face: tracking expiring prescriptions, pre-auth deadlines, pharmacy stock issues, and even escalating tasks clinicians don’t have time for. The strong opinion: AI isn’t replacing clinicians — it’s replacing the waste that’s burning them out and harming patients.

Easy Medicine" tackles the most painful, immediate problem: cost: Instead of starting with the flashy stuff, the MVP focuses on something every chronic patient feels — medication prices. By pulling manufacturer coupons, GoodRx prices, and Cost Plus Drugs data, the tool delivers real savings instantly. It’s practical, high-impact, and built entirely using modern AI coding tools, no traditional coding required.

Rapid AI-powered building is the new superpower: The episode pushes a strong stance: don’t start with a course — start by building. A one-hour prototype is now more valuable than weeks of prep. The biggest skill in AI product building isn’t knowing how to code; it’s knowing what’s worth building, validating fast, and iterating with real users. Tools like Lovable, Bubble, Replit, and Figma have lowered the barrier to near-zero.

Purpose drives better products: Taylor’s journey from Botswana to Google to chronic illness to founder underscores a theme: when you’ve lived the problem, you build differently. His story is a reminder that the most meaningful AI solutions don’t start with technology — they start with empathy and frustration with the status quo.

THE SHOW

Weekly conversations with the AI’s top product leaders. Join Polly Allen as she discovers the paths to success in the world of AI.

THE LINKS

Have a question you want us to answer? Send it through to support@aicareerboost.com

Taylor Ahlgren

LinkedIn: https://www.linkedin.com/in/taylorahlgren

My links

LinkedIn: ⁠https://www.linkedin.com/in/pollymallen/⁠

AI Career Boost: ⁠https://www.aicareerboost.com/⁠

For more on building AI products and careers, along with early course announcement and special pricing, subscribe to the AI Career Boost mailing list at https://aicareerboost.com/interested

THE GUEST

Daryl Teo is a technology strategist and seasoned CTO known for turning bold business vision into practical, scalable technical execution. Over the years, he has led engineering organizations of up to 150 developers, guided product and platform strategy across multiple industries, and built high-performance teams grounded in clarity, culture, and strong delivery. Today, Daryl advises companies as a fractional CTO—doubling down on AI-driven automation and transformation. With a rare blend of deep technical expertise and sharp business intuition, he brings the kind of leadership that helps startups, scale-ups, and SMBs move from idea to impact with confidence.

THE SUMMARY

Small, agile teams outperform large ones: when rapid change is required. Working with compact, high-calibre teams lets leaders drive meaningful shifts in weeks instead of months — a pace larger organisations struggle to match thanks to bureaucracy and slow decision-making.

Remote teams make junior hiring far harder: Without shoulder-to-shoulder mentoring, junior developers often become a net cost. In services-based environments, the margin pressure makes it almost impossible to justify the overhead of training juniors without a dedicated program.

AI adoption starts with a mindset shift, not a technical one: The moment you stop treating AI as a novelty and start treating it like a collaborator — one whose output you audit with healthy skepticism — everything changes. This “AI-first” approach is now non-negotiable.

The fastest wins come from augmenting existing capabilities: Some of the easiest, highest-ROI applications of AI aren’t glamorous. A 24/7 voice agent for a laundromat chain is a perfect example: humans sleep, machines don’t. Businesses gain capability they simply couldn’t afford before.

AI is a weapon for speed in operational bottlenecks: Even shaving a few minutes off time-sensitive workflows — like sourcing inventory prices from multiple vendors — can materially shift conversion rates. AI becomes a force multiplier in places humans didn’t even realise they were inefficient.

There’s no single “best” coding agent — the value is in speed, not purity: For rapid prototypes and short-lived projects, the differences between tools like Cursor, Claude Code, and Codex barely matter. What matters is delivering value, not endlessly comparing models.

The most important advice for anyone entering AI? “Lean in and commit: Half-adopting AI is as useless as not adopting it at all. Treating models as capable collaborators — while still verifying their output — is the mindset that unlocks real leverage.

THE SHOW

Weekly conversations with the AI’s top product leaders. Join Polly Allen as she discovers the paths to success in the world of AI.

THE LINKS

Have a question you want us to answer? Send it through to support@aicareerboost.com

Daryl Teo

LinkedIn: https://sg.linkedin.com/in/thedarylteo

My links

LinkedIn: ⁠https://www.linkedin.com/in/pollymallen/⁠

AI Career Boost: ⁠https://www.aicareerboost.com/⁠