For the past few years, the internet has been inundated with news, tools, and foreboding around generative artificial intelligence, GenAI for short. I’ve attended four online day-conferences about the technology, how to use it, and ways it can strengthen & support professional project & product managers.

This time ‘round, I was asked to give a talk about it. From what the attendees are looking for and where my own curiosities have led, I decided to talk about how GenAI, with used in orchestration with no-code and/or low-code tools, can be a powerful combination.

This is me, planning in public.

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Context

• I’ll be the eighth talk of the day; they’d have gone through five hours of presentations so far

• Preceding topics:

  • Presentations with GenAI

  • AI Concepts, Tools, and Use Cases

  • Governance, Compliance, and Decision-Making

  • Enterprise AI Adoption

  • Future of Project Management

  • Test Driven Development

  • Technical Program Management

• The presentation is 30 minutes in total, around 3,000 spoken words total

• Should be around 3,000 words spoken, according to Words to Time.

• There’ll be a break just after my talk

• Current Blurb: This beginner-friendly talk explores the evolving landscape of product management through low-code, no-code, and AI technologies. The presentation covers key concepts, popular tools, and how these approaches intersect with Generative AI. It examines the impact on the Software Development Life Cycle (SDLC), discussing how these technologies are making development more accessible and efficient.

Audience

• Beginners in using GenAI

• Likely unfamiliar with low-code, no-code, and practical uses of GenAI

• ~300 project and product management professionals around the world

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Outline

• Introduction

  • Hello, I’m Jonathan

  • Here’s a bit about me

  • Here’s what I’ll be covering

• Framing

  • The work is never just “the work”1

    • The future of project management, as Chris Knotts shared in previous talk today, is up in the air. While 80% of project management tasks are predicted to be replaced and {use an example from earlier talk}, it’s important to focus on your need and use case

    • A framework for this can be defining what work you want to use it for, coming from Dave Stewart’s post:

      • the work around the work (meetings, reviews, etc)

      • the work to get the work (research, experimentation, scoping, quoting, pitching)

      • the work before the work (configuration, setup, services, infra)

      • the work (the actual build, product, design, tests, docs, etc)

      • the work between the work (iteration, debugging, refactoring, maintenance, tooling)

      • the work beyond the work (changes, omissions, nice-to-haves, scope creep)

      • the work outside the work (surprises, contingency, disasters, mission creep)

      • the work after the work (hosting, deployment, security, support, updates, fixes, etc)

• Defining the terms

  • Low-code is:

    • a visual approach to software development that enables faster delivery of applications through minimal hand-coding.2

    • a rapid application development (RAD) approach that enables automated code generation through visual building blocks like drag-and-drop and pull-down menu interfaces.

  • No-code is:

    • a software development approach that enables users to create applications and automate business processes without writing code. 

    • a RAD approach and is often treated as a subset of the modular plug-and-play, low-code development approach. While in low-code there is some handholding done by developers in the form of scripting or manual coding, no-code has a completely hands-off approach, with 100% dependence on visual tools.

• Sharing and evaluating tools

  • Low-code

    • add to list

  • No-code

    • Notion

• How do we integrate GenAI into these tools?

  • A lot of them are already using aspects of Generative AI in their own tool

  • Practical use cases, needed.

• Why is this important?

  • Job expectations

    • find job advertisements that expect project, product, and program managers to create tools themselves

  • Can become more independent in getting things done

  • Can create tools specific to your need and what you don’t like to do in the “work around the work.”

    • What do you enjoy doing?

    • What do you hate doing?

    • How can you create something to reduce the stuff you don’t like and make more time for the stuff you do?

• Recap

  • provide a URL for resources and slides

• Thank you

  • contact information