Coburn Ventures Podcast

Today we sit down with a true "analysts' analyst", our friend Gareth, to learn more about how he has built his AI integrated process. He wrote us, "The advanced analyst uses AI to accelerate the workflow they already had. The Revolutionized analyst redesigns the workflow around what AI makes possible, keeping the human for the part only a human should do: judgement." There's so much here... let's jump in.

Volatility can be a disruptive force in many ways, from affecting our time horizons to our day-to-day systems and behaviors. Today we want to look at some of the possibilities for making volatility, this key element of new market structures, something to get enthusiastic about. Let's jump in.

What happens when AI meets investment process? If we define the investment process as getting in a position of discernment, taking in uncommon inputs and the ability to convert knowledge into investable insights, there is plenty to work with. As one friend put it “the analyst I am today integrating AI could wipe the floor with the analyst I was 12 months ago”. I think we want to learn more. Let’s jump in.

What are some of the primary characteristics of an AI integrated Investment process? Today we highlight three, but if you’re going to remember one thing from this conversation, let it be this: every healthy research team will alter its ratio o f research to analysis dramatically toward analysis. Let’s jump in.

This week a conversation started with a familiar worry: if everyone can drop the same data into AI and get the same answers, won't the market just level out? It's a fair question on the surface, but underneath it assumes the market's questions are the right questions, that there’s absolutely no inefficiency. So today we're using JP's four-stage model — observation, diagnosis, prediction, prescription — to talk about why the common question of the day is almost never the right investment question, and why AI, used well, can actually widen the gap between the common and the uncommon rather than closing it. Let’s jump in.

The line of reasoning that may have attracted clients to money managers 10-20 years ago or more may be changing and causing tension as we work to adjust to new market structures, AI, passives and more. This does not mean we are at an impasse, or have to stay 100% tied to our process and stance from decades ago. Instead, we can build the connection with clients, bringing them along, communicating how we discern what's worth evolving and what’s not. In this conversation, I hope you’ll listen specifically for samples of how we might begin these conversations to better connect with clients and others on the prosperous, incredible path into the future... Let’s jump in.

When you hear the phrase best practices, are you excited for whatever explanation comes after it? It's a phrase that's representative of wanting to succeed and do our best, but the path doesn't always hold up especially in a fast-moving industry that has been injected with a new partner in AI. The mode of best practices presumes someone's already figured out the way, when really, we're still in the middle of figuring it out ourselves. 

In this discussion we’ll talk about some of the unfocused activity we're seeing right now, the temptation to just look around at what everyone else is doing, and why that instinct usually leads nowhere useful and definitely not to uncommon. 

If there's one thing to take away from this conversation, it's this: start with your core. Know what you're trying to accomplish, know your arbitrage, know your process — and then, and only then, ask how AI advances that goal. Let’s jump in.

Today we continue our conversation on uncommon insight, this time asking why it's so hard to actually get there, even when we can agree it's the goal. We talk about the discomfort of stepping outside professional norms, the habit energy that keeps us doing our job the same way, and why AI amplifying our ability to find uncommon understanding won't make it common because most people aren't looking to go there in the first place. Let's jump in.

When you say "Now we are all going to implement AI into our investment process", does the energy in the room go UP? I'd guess probably not. Today we introduce a module that is simply getting us used to the idea that we can add AI into our processes in playful ways that make it less intimidating and more energizing. Let's jump in.

Today's AI module has at least two really important elements that I hope you will take away with you . The first is that this is a module that works from a slightly different vantage point. It works very, very rigorously on the pivotal question. This module is not so much about impressive massive output or information synthesis from AI. It's about staying in and working and re-working what we hope will be one concise question that sets us off on a path to uncommon insight. Second, this module gives you a partner for the work of being inquisitive and rigorous, which, depending on a lot of circumstances, might take some vulnerability to accomplish in a team or group setting. With this module, we hope you can get very far down the path and more practiced at having these difficult elements become more easily incorporated into your process.  Let's jump in.