Quick note: I’m writing about productivity here, in end-user scenarios. What we’re seeing in business apps and services is way beyond the scope here!

AI. You might have heard of it. Little buzz thing going on just now, apparently it might change the world.

I think it already has, and will continue to change things in both positively impactful and potentially negative ways. It depends on context and perspective. Will it take all our jobs away and make humans irrelevant? I don’t think so. Will it take some jobs away and require retraining and shiftings of ways we get things done? I believe yes. Will it create NET NEW jobs? Also yes. So .. a wash? :)

In the world of product marketing (and peripheral disciplines like evangelism, technical marketing, communications, AR, PR etc) I have found myself cautious. I am very much against auto generated content being spewed out without review. The AI tooling we have today is far too nascent to warrant full and complete trust. I’ve seen a bunch of generated content that to the uninitiated looks awesome, but when viewing by knowledable and practioner level audiences is quite literally incoherent garbage. Context matters. Perspective matters. Intuition matters. And AI is not good at any of those to the degree required for anyone to just trust and publish out. Yet. I have a strong belief what we are seeing is just the beginning, and in the months and years to come, the iterative learning the models are undergoing, the training we are all providing to these tools when we correct them, ask them to clarify and iterate, will lead us to far more impactful scenarios.

So back to the question of humans and jobs. We’re seeing some leading indicators where companies are betting, perhaps a little aggresively in this writers opinion, that AI can provide an opportunity to invest differently from humans to tools. In some cases this is likely warranted and appropriate. In others, less so. In order to be a part of the change and ride the AI wave in positive ways, I advocate that everyone should look at the tools being made available to you and test scenarios and workflows where the tools make you better. That might be efficiency, creativity, effectiveness or any other vector where “more value” can be derived.

I’ve been playing with ChatGPT and Google Gemini over the last few months and have started to see where the “Humans + AI” value is showing positive results. There will be a never ending list, and I’m sure y’all have a ton more, I encourage you to share!

Here’s a few within the use cases I’ve personally found intriguing and helpful in Getting Shit Done. There’s nothing stunningly crazy here, and TBH that’s one of my learnings. AI doesn’t need to be mindblowing at every turn, some things will be, but a lot of the real value is in productivity gains and speeding up execution … I don’t shy from that, I embrace it. Will we get to detailed, complex workflows of epic proportions? In some cases yes, in some cases, that’s unnecessary and wasteful. I replay my “automation” heritage here, back when we were adopting the runbook philosophy from mainframes to private clouds and then public clouds, there was a tendency to want to AUTOMATE EVERYTHING. But not everything needs to be automated. Automate when you need scale and speed.

My quickstart, repeatable and helpful-in-getting-my-job-done and helpful-across-the-team list:

  • Idea Generation: Creating a list of interesting things and running up first drafts are obvious kickstarters
  • Idea Iteration: Once you have a few things, run up some iterations, generate 10 different versions, quickly test words and meanings
  • Test tone, change perspective: One of the more impactful things I’ve found, asking the tools to take something written in one voice and shift to a different one, from different role perspectives to first/third person shifts
  • Notebooks As Briefs: Using Notebooks as a way to aggregate a set of assets common to a topic, generating summaries, briefs, mind maps, FAQ’s and audio podcasts
  • Aggregating Content: Import a set of existing assets and create aggregated compilations and summaries to gain multiple uses of the same content
  • Summarizing Long Form Content: An impactful way to consume a large amount of content such as reports, and capturing both common and contrasting viewpoints
  • Transforming Content: Shape shifting content is time consuming, but moving from slides to docs, transcripts of speeches to slides, audio generation of documents for accessibility such as listening over reading, are all quickly and efficiently done
  • Recurring Projects: Building repositories of things like agenda, meetings notes, audio recordings, transcripts so that stakeholders can search and query to gain value
  • Web Research: Grab links to a set of pages and sites and let the AI reason over it, summarize, compare, contrast and provide insights

As you can see, I bet there’s nothing that jumps off the page and makes you go “holy shit would you look at that”. To which I say … EXACTLY. But you know what, I’m saving hours per day, we’re executing orders of magnitude faster, we’re getting from “zero to something” rapidly so that the human aspects can jump straight to the 75-80% mark and finish it up over the last 20%. That old 80/20 rule applies here so much, if we can spend our time on that last 20% and not the boring hard yards of the first 80% on use cases like this, we’re in a better spot.

I’m excited by what these tools can do, and if we adopt carefully, safely, and with an appropriate set of checks and balances as they evolve, we’re heading into an exciting world. And this post is only about some productivity aspects in the world of PMM, what we’re doing with Agentic AI in Security, Health, Environmental, Finance … just insane how cool and impactful this is and will be.