The Least Sexiest Thing

I find it human nature to chase the shiny new thing. Or make something overly complex and over-engineer it. I was reminded last week that sometimes the least sexiest thing is most useful. In my case, it was a flat priority list of projects for Q2. From highest to lowest priority, I was meeting with the Engineering Manager and Product Manager on my team to discuss the prior and upcoming sprint. It wasn’t a fancy strategy image or something complicated in Jira. 

Our discussion was effective because we were able to see and discuss accomplishments & learning, where we’re going next, and what is delayed, which is exactly what you need to find ways to discuss throughout a quarter. 

It was a simple flat priority list of ~15 projects in buckets from P1, P2, and P3. Sometimes the least sexiest thing is most useful.

Weekly Listen #2

This was one of my favorite podcasts I listened to this week. I actually rolled it back a second time to understand more about the power supply points they made connected to AI supply and pricing. I also found it helpful how they think in first principles by talking about the demand for human-like intelligence.

It got me thinking outside of work, do I have demand for human-like intelligence or any AI use cases I’d use daily for personal reasons? Outside of reading on the web and maybe looking at personal finances, I really try to put technology down on the weekends so I found it hard to think of true recurring examples of using AI daily for personal reasons, unless chatting with personal AI assistants takes off. I suppose then it comes down to AI in existing products for me personally that help me do those things better (reading on the web, understanding monthly spend, etc.).

I want to be fairly selective on new technology especially for personal use to avoid adding technology I don’t need or might be harmful to my values and creating positive habits.

The pod also does a great job bringing it back to traditional business principles of differentiation. These guys have been around the web a while so it was cool to hear them talk about the internet in the 90’s. For example, there were 20 search companies trying to break through before Google won the market. That reminds me of one of my favorite HBS cases about search in the early days here and here.

AI Use Cases at Work

It is good to know I am not alone. Recently, I have read or listened to strong thinkers in their respective domains question if AI can be used in their day to day. I too have had these observations in my own day to day. To be really clear, I see the power of it and how it can be used to solve certain problems, mainly jumping steps from start to finish. 

That said, in my day to day as an SEO leader, I am struggling to adopt it as a power user. Despite this, I remain open and excited to the new technology so that I can adapt my skills and experience to stay relevant in the field of SEO. Here’s a few tactical ways I’ve been reading about using AI:

Here’s a few AI ideas I am most excited about: 

Generative AI and Retrieval Augmentation Generation (RAG) have a chance to completely change the point and click experience that the graphical user interface (GUI) brought us. The GUI was an unlock in technology that opened up computers to more industries. Prior to that, workers in certain industries couldn’t see value in computers.

My Take: I totally see how this concept applies to desktop software applications specifically. I’d love to chat with software versus trying to figure out how to use it with a series of clicks and sometimes waiting each click. The best use case I can think of is chatting with something that is hooked into data I need to get at. So instead of knowing SQL or point and click steps in Tableau or Looker, I can tell the computer what I want. This is great and something I’d use. My thought is this use case is very specific to desktop experiences and not mobile. The tap, type, scroll, read experience on mobile is totally different. I am not entirely convinced that AI chat is integral to the mobile experience as so much of mobile use is browsing articles, social media, and search. Maybe it does catch on via mobile or simply is complementary to existing search, social, and other products? 

The best way to familiarize yourself with Generative AI is to identify a problem you have and try solving it with AI. That is where the magic will be felt.

My Take: About 6 months ago, I came across this experience. There was something I was dying to do for about a year but was trying to solve it with someone who had expertise in a certain area. The problem was I could not get the internal or external help. Enter AI. I began trying to solve the problem myself with AI and it proved to be useful. I compared against other LLMs and learned about each and then shopped it around to others on my team who supported the use case. We then worked to productionalize it. This felt to me like magic and the use case fit AI perfectly.  

I remain excited and interested to see where this new technology takes consumer behavior. 

LLM Value Chain

I found this image provided by the UK’s Competition and Markets Authority (CMA) very helpful for understanding the current LLM value chain. In the image they use FM which stands for Foundation Models. Specifically you can see where the big tech incumbents are currently playing. Some interesting pieces to me are:

  • The FM release will be how other enterprise and start up companies are able to leverage these FMs at scale for proprietary data. Perhaps startup FMs will run in tandem with these as well. I am excited about innovation here because it opens up the door for a lot of improvements to SEO and CRO executional improvements and changes. 
  • It will be interesting to follow how the bottom row continues to play out since that is where the end users. I am excited to see how AI makes its way into productivity software like Gsuite, Android, Microsoft Office, or  iOS. 
  • Notice where Apple is playing? They’re developing models and with its mobile ecosystem of users has a chance at shaking things up. 
  • When people talk about GenAI favoring incumbents, this image makes that clear. 
LLM Value Chain

AI, Blockchain, and Search

I recently finished Read Write Own by Chris Dixon. I found the brief section titled, Artificial Intelligence: The New Economic Covenant for Creators the most interesting because it most closely ties to search. He quickly summarizes historical context around content creators bringing supply and distributors like Google putting that content in front of relevant users. The creator base was fragmented back in the 90s and early 2000s and still today. Dixon argued the fragmentation of content creators prevented them from gaining any sort of power in the relationship between supply and distributor. Had creators been able to band together, the Google we know today might have been different. Instead the result was Google gathering more users to amass a 80%+market share in search today through moving to compliment products it gave away for free such as an internet browser (Chrome) and mobile OS (Android) then moved most of the commerce to search with ads and built a great product that kept users coming back. 

The connection both AI and blockchain have to this history of the internet is that it is a chance to reset the power dynamics. His big argument is that blockchain is the only way to do it because of the network design. The root of the design is to give more power to people who contribute value to the network, not the management teams of those networks. If a traditional corporate network tries to do this, over time it will just turn into what you see today as the network attracts users and then extracts as much value as it can for the benefit of the people who own the corporate network (founders, shareholders,etc.).  

It is a short part of the last chapter on pages 216 to 222 with some thought provoking questions at the end.

My thoughts are that I want the creative work I am a part of on the internet to have a chance to perform in search and get credit when value is generated. I also want to be able to find and point to the creative work of others as a user. I am really excited about that end-state. The design or technology that powers that discovery is less of my expertise but I find it interesting to stay on top of new technologies and ideas that might gain traction like blockchain.