Should we build Generative AI into our existing software?

Is adding AI to your product a competitive necessity or just a costly distraction? This talk provides a framework to make the right call.

#1about 2 minutes

Framing the AI integration decision as no, yes, or maybe

The decision to integrate generative AI can be framed as a simple no, a clear yes, or a more nuanced "chicken and egg" problem for developers to solve.

#2about 4 minutes

Evaluating product fit with desirability, viability, and feasibility

Avoid adding AI for hype by using the desirability, viability, and feasibility framework to ensure it solves a real user problem and has a business case.

#3about 4 minutes

Identifying clear use cases for generative AI integration

Generative AI is a clear yes for industries like customer service, data entry, and translation where it can fundamentally disrupt and improve existing processes.

#4about 3 minutes

The developer's role in navigating business and investor pressure

Developers must provide technical perspective to business stakeholders and investors who are often driven by market hype rather than product need.

#5about 5 minutes

Choosing between RAG and fine-tuning for your application

Use Retrieval-Augmented Generation (RAG) for querying documents and reserve fine-tuning for teaching a model a specific style or vocabulary.

#6about 1 minute

Leveraging evolving hyperscaler AI solutions

Hyperscaler platforms like Azure are rapidly simplifying AI integration, moving from complex custom builds to more accessible, business-focused solutions.

#7about 2 minutes

Looking beyond language to future AI applications

The underlying transformer architecture of LLMs is now being applied to new domains like visual data and time series forecasting for finance and IoT.

#8about 3 minutes

The evolution of AI from tool to assistant to agent

Generative AI is evolving from a simple tool to a programming assistant and is now moving towards autonomous multi-agent systems that can model entire companies.

#9about 3 minutes

Partnering with business to build better products

Developers must act as partners to business teams, providing the deep technical knowledge needed to make informed decisions about when and how to use AI.