Building GenAI Products - Product Management Perspective

By Abhijeet Joshi , Product Director, Rakuten India

This article talks about the considerations and the change in mindset for a Product Manager when thinking about, building and rolling out GenAI based Products & Features

In our previous blog post “Product Strategy for Generative AI and rise of Open LLMs”, we read about the possibilities that GenAI has opened up and the practical considerations there in. Though the possibilities seem limitless, the fundamental principle of building something valuable that users are willing to pay for very much remains relevant. For all the things that GenAI can do, it cannot sell itself (maybe one day it will!) and the Product Managers need to think deeply about the relevance and practicality of introducing GenAI in their products.

Building sustained value that customers are ready to pay for

From software eating the world to AI eating software, we are now talking about GenAI eating AI. But at its core, its still the classic phenomenon of a newer technology subsuming a relatively older technology and in the process creating new product avenues. The fundamental question of whether GenAI is a nail in search of a hammer still very much applies but based on the initial signs, GenAI definitely seems to have found the Technology-Product Fit for use cases such as near-human chatbots, content generation, document summarization and so on. When we are considering use cases beyond these in our respective domains, the first principles of Product Management need to be critically looked at. Am i building something that is generating value at a manageable cost? And is someone willing to pay for this value? Its common knowledge that GenAI applications have significant development costs spanning costly hardware and top quality engineers amongst other things. The tough question that all PMs need to be clear about is “How much will it cost me to build a GenAI driven feature vis-a-vis how much sustained incremental revenue will i be able to earn?”

Native GenAI workflows or GenAI on top of existing workflows

While the first thought for a PM would be to think about how can GenAI enhance existing Product Workflows, there is a golden opportunity to think about Native GenAI workflows. This is analogous to the transition from the web era to the mobile era. The initial product efforts during this period tried to fit web workflows into the mobile form factor. It took a while before PMs and Designers ditched web altogether and started imagining mobile-first workflows. GenAI is capable of introducing hitherto improbable product experiences but it will take some time for Product folks to discount existing flows and go GenAI-first.

Imagine a GenAI rendered avatar as your sales assistant joining you in all your customer calls. You introduce the assistant to your customers as like any other team member. In the meeting, this assistant is able to quote past conversations for context, share details about the product / service that you are struggling to remember or maybe even highlight any contractual nuances during a tough negotiation. Imagine the efficiency this would bring in sales meetings and with it hopefully conversions!

I expect startups to be the catalyst here for such experiences. GenAI-first startups with the ability to experiment and fail fast will quickly iterate and pave the way for this sort of native GenAI thinking to become commonplace.

Regulations, privacy and the growing scrutiny for GenAI

The Future of Life institute released an open letter in March 2023 calling for a pause on GenAI related development work and ensure that the necessary safety protocols are put in place for GenAI activities. Amongst the 33,712 signatories are technology stalwarts Elon Musk and Steve Wozniak. Now these people definitely know a thing or two about mainstreaming cutting edge technologies and here they are acknowledging the risk elements in GenAI. The counterpoint to this letter is that the GenAI is being mistaken for Artificial General Intelligence which could one day surpass the cognitive ability of humans and end up taking over the world. Product Managers don’t have the time to wait for this debate to play out and are under pressure to get started with GenAI quickly. Now, its the PM’s responsibility to put in the necessary guardrails while leveraging GenAI. Coverage of data privacy norms, local government regulations, compliance requirements will form a critical section of a PRD (Product Requirements Document) which will have to vetted by the company’s Risk and Legal teams. Given the nascency of this technology, chances are that Legal teams may want to play safe and turn down some of the coolest GenAI use cases a PM is thinking of. Regulations around GenAI is an additional area that a PM will have to spend a significant time getting familiar with.

Impact on the product of a potential of a GenAI mistake

Majority, if not all, AI systems are probabilistic in nature and prone to error or inaccuracies. In such error scenarios, B2C applications can be comparatively more forgiving as compared to B2B ones. But irrespective, accountability needs to be fixed in case of any errors. Predictability of performance needs to be introduced so that PMs know that Production systems will work as expected day in day out. But how do we introduce a deterministic aspect into something that is probabilistic in nature?