Product Bakar

What can Product Managers learn from the world’s best AI-driven products?

In this episode of Product Bakar, Rishikesh Kankal — seasoned Product Manager — breaks down how Spotify, Netflix, and Duolingo use AI to drive personalization, engagement, and growth.

You’ll learn:

• How Spotify uses AI to build a strong personalization moat

• Why Netflix combines AI with constant experimentation

• How Duolingo delivers personalized learning at scale

• Key product lessons for building AI-powered experiences

If you’re building digital products, this episode offers practical insights on turning AI into real business value.

📩 Looking for a Product Manager to build your digital product?

Get in touch: [email protected]

SaaS is moving beyond simple automation to intelligent, AI-powered workflows.

In this episode of Product Bakar, Rishikesh Kankal — seasoned Product Manager — explains how AI is transforming SaaS products into smart copilots that guide decisions and improve productivity.

You’ll learn:

• How automation shaped early SaaS

• Why rule-based systems are no longer enough

• How tools like Salesforce, Grammarly, and Jira use AI

• What this shift means for Product Managers

If you’re building or scaling SaaS products, this episode will help you rethink how AI fits into your product strategy.

📩 Looking for a Product Manager to build your digital product?

Contact: [email protected]

AI doesn’t just learn from data — it learns from our data.

And that means it can inherit the same biases, blind spots, and inequalities that exist in the real world.

In this episode of Product Bakar, Rishikesh Kankal dives into one of the most critical — and often uncomfortable — topics in AI product building: bias, fairness, and inclusivity.

This isn’t just a technical problem for data scientists. It’s a product problem, and Product Managers play a central role in either amplifying bias or preventing it.

In this episode, we cover:

• How bias quietly creeps into AI systems through data and usage patterns

• Real-world examples of biased AI in hiring, facial recognition, and credit scoring

• Why fairness directly impacts user trust, business growth, and regulatory risk

• Practical actions PMs can take to design more inclusive AI products

• How to move fairness from an afterthought to a core product principle

If you’re building AI-powered products, this episode will help you ask better questions, define better metrics, and build products that work for more people — not just the majority.

AI innovation is moving fast — but regulation is catching up.

From the EU AI Act to US executive orders, and evolving rules across India and China, governments worldwide are setting boundaries for how AI products can be built and deployed.

And for Product Managers, this creates a tough reality:

If your AI product isn’t compliant, it doesn’t matter how innovative it is — it’s a liability.

In this episode of Product Bakar, we unpack the regulation puzzle and break down what PMs actually need to know to ship AI products that are both fast and safe.

We cover:

• Why AI regulation is uniquely complex and constantly changing

• The core areas regulators care about: transparency, privacy, accountability, and risk

• How frameworks like the EU AI Act think about low vs high-risk AI use cases

• A practical PM playbook for staying compliant without slowing delivery

• Why compliance isn’t a blocker — but a long-term survival strategy

This episode is essential listening for PMs building, scaling, or planning AI-powered products in a global market.

AI doesn’t just make products smarter — it makes them more powerful.

And with that power comes a responsibility that Product Managers can’t ignore: ethics.

In this episode of Product Bakar, Rishikesh Kankal tackles one of the most uncomfortable — yet unavoidable — topics in modern product management: AI ethics and the PM’s role in drawing boundaries.

We explore:

• Why AI ethics is not a legal or engineering problem — but a PM problem

• The real ethical questions AI products force on teams, whether they’re ready or not

• The three biggest ethical fault lines in AI: bias, transparency, and harm

• How PMs can bake ethics into requirements, not slide decks

• Why trust, not just accuracy or engagement, determines long-term product success

This episode isn’t about slowing innovation. It’s about making sure what you build is defensible, trustworthy, and sustainable.

If you’re a PM working on AI-powered products — this conversation will change how you think about responsibility and leadership.

AI product teams don’t look like traditional product teams anymore.

Designers and software engineers are now joined by data scientists, ML engineers, and research-heavy roles — and for many Product Managers, this shift can feel intimidating.

In this episode of Product Bakar, Rishikesh Kankal breaks down how PMs can work effectively with data-heavy AI teams — without being data scientists themselves.

You’ll learn:

• The real difference between data scientists, ML engineers, and software engineers

• Where PMs add the most value in AI product teams

• How to frame problems instead of prescribing technical solutions

• Why data availability and feasibility matter more than flashy AI ideas

• How to define success beyond model accuracy — focusing on adoption, trust, and business impact

• Practical ways to build strong collaboration and protect your team from “AI magic” expectations

If you’re a PM working with AI teams — or about to — this episode will help you lead with clarity, credibility, and confidence.

Episode Tags / Keywords

Product Management, AI for PMs, Data Scientists, Machine Learning Engineers, AI Product Teams, Generative AI, Product Leadership, AI Strategy, PM Skills, AI Collaboration

Building AI products isn’t just about models, prompts, or metrics — it’s about people.

In this episode of Product Bakar, Rishikesh Kankal dives into one of the hardest challenges Product Managers face today: stakeholder management in the age of AI.

On one side, you have AI evangelists pushing for AI everywhere, fast.

On the other, AI skeptics worried about risk, bias, hallucinations, and compliance.

As a PM, your job isn’t to pick a side — it’s to bridge the gap.

In this episode, we break down:

• How to manage over-enthusiastic AI evangelists without derailing your roadmap

• How to win over skeptics using evidence, guardrails, and small experiments

• Practical frameworks PMs can use to balance speed and safety

• Why stakeholder trust is becoming a core PM skill in AI-driven products

If you’re building, shipping, or even talking about AI inside your organization, this episode will help you stay credible, calm, and in control.

Getting real users for interviews is hard. AI is changing that.

In this episode, we break down how synthetic users and AI-driven UX research are reshaping product discovery. Learn how PMs and designers can instantly test flows, simulate edge cases, and accelerate insights — without waiting weeks for recruitment.

But we also unpack the limits: bias, false confidence, and why humans can’t be replaced.

If you’re building in AI or pushing for faster discovery, this episode is a must-listen.

Keywords (SEO): synthetic users, AI UX research, AI in product management, UX automation, user research at scale, product discovery, AI personas, PM AI workflow, synthetic testing, AI product tools

Search as we know it is collapsing. AI is transforming how people discover information—from typing keywords into Google to simply asking and getting one clear, personalized answer.

In this episode of Product Bakar, Rishikesh breaks down the shift from “10 blue links” to AI-driven answer engines. You’ll learn why traditional search is failing, what a post-search world looks like, and how product managers can design for natural language discovery, personalization, and AI-native decision support.

Whether you’re building consumer apps, SaaS tools, marketplaces, or internal platforms—this episode will reshape how you think about discovery and product strategy in the age of AI.

Keywords / SEO Tags:

AI search, answer engines, post-search world, product discovery, conversational interfaces, AI design, personalized recommendations, AI product management, LLMs in products, future of search, ChatGPT, Perplexity AI

AI is no longer about one model answering your question — it’s about many AIs working together. In this episode, we dive into the world of multi-agent systems and why they’re becoming the next big leap in AI.

You’ll learn:

• What multi-agent systems actually are (think: a digital team of specialized AIs)

• How multi-agent collaboration can automate entire workflows end-to-end

• Why specialization beats one giant “super AI”

• How emergent behaviors like negotiation and cooperation reshape product decisions

• What PMs must rethink: user journeys, interoperability, business models, and agent-to-agent decision making

We’re moving from “AI as a tool” to “AI as a team.”
And that shift will challenge every assumption in product strategy.

This is Product Bakar, Episode 34 — The Rise of Multi-Agent Systems.
Stick around for the next episode: AI and the Death of Search — Designing for a Post-Search World.