Andy Holley

Create, transform, develop leaders, push boundaries in a hyperconnected world. Opinions are my own.

[Aaron Levie @levie]

The two biggest launches in AI in the past month are now constrained by capacity. This is what we meant by Jevons paradox.

[Aaron Levie @levie]

AI is going to cause us to move to higher levels of abstraction of how we work. Each level of abstraction provides more leverage than the prior level, so each bit of input leads to vastly higher output.

This has happened all throughout history when there’s major technological progress, from the Industrial Revolution with mechanical automation and in the Information Age with digital automation. The work that we do today looks far different from 100 or 50 years ago respectively.

The same will be true again with AI. What we perceive is “work” today will continue to be redefined. When you can merely think of an idea to prototype and AI can generate the code, the timelines on building software suddenly alter. When you can instantly research a topic and understand it deeply without the hundred hours going down the wrong threads, you’ll move to the next task much quicker.

This will naturally change what we spend our time doing each day in almost every field. Building software will be as much about reviewing code and considering the right prompts as it is writing the code. Delivering a healthcare outcome will mean having access to every bit of research at your fingertips instantly, augmenting anything you already know. Every domain will experience a similar impact.

Skills will matter just as much as ever, but they will look different, just as skills have changed during every other technological revolution. And more people can get started in a field they’re interested in, while the experts in the field can get even more done than they could’ve before.

In just a few years, we will look back on how we used to work and be utterly surprised how long everything took to do. It will seem implausible that you had to literally do everything yourself on a *computer*, the thing that was invented to help automate work.

[Aaron Levie @levie]

Google just unveiled a new project that shows how AI Agents are coming for full browser and computer use. This opens up AI to any of the laborious knowledge tasks that we do today. Most importantly, it lets us automate work that we never had even contemplated before.

[Aaron Levie @levie]

The best way to build products is to never get into the trap of imagining a user will do any work to figure out anything. The moment you start describing how a user will learn how something works you’ve designed the product wrong.

[Gokul Rajaram @gokulr]

CEOs, founders and leaders, as you go through 2025 annual planning, remember the following maxim:

It's not prioritization until it hurts.

In other words, you'll need to cut many GOOD initiatives / projects in order to have the bandwidth and resources focus on a few GREAT ones.

[Aaron Levie @levie]

AI Agents have the potential to democratize knowledge work in the same way that SaaS democratized software. And as we've seen in the past couple of decades with software, every time you make a service cheaper and more available, you dramatically increase the size of the total addressable market. 

Let's take, for instance, what happened in the early days of SaaS. The biggest mistake that most people and investors made was looking at the market sizes of traditional on-prem software to see how big the market could be for this new crop of companies. In fact, some even felt the markets would actually be *smaller* because the software may be cheaper to run for an enterprise. All these theories were wrong, by an order of magnitude.

What we actually saw happen was not that SaaS initially replaced or went after traditional incumbent software products for existing customers, but instead, the biggest early customers were actually smaller businesses or teams in large enterprises that previously didn't have access to traditional on-prem enterprise software. On-prem software, from CRM systems to ERP platforms, were notoriously expensive, hard to manage, and required significant IT teams and partners to operate. This meant only the largest enterprises in the world could actually implement best-in-class technology for their enterprise.  

Enter SaaS. Starting with Salesforce and NetSuite, for the first time small businesses had access to effectively the same tech stack that a large enterprise had. This led to a gold rush of software. AWS ushered in an era where a one person startup could build an app and scale it without ever visiting a datacenter. Box let businesses of all sizes manage documents and content securely. Shopify let anyone have access to a powerful ecommerce system, leading to a huge boom in direct-to-consumer product companies and other retailers being able to sell successfully online. Stripe gave any developer a full payment stack. All of these new services --and thousands more-- led to a 10Xing (or more) the size of traditional markets by serving customers that previously didn't have access to these types of tools.

Now, if you extrapolate out what we're seeing in the earliest days of AI, the same dynamic could hold true for AI Agents. While large enterprises have traditionally had access to nearly every specialized form talent or an abundance of labor, the vast majority of businesses don't have this same luxury. For most small startups just getting going, they often don't have the resources to do outbound sales, full customer support, specialized legal work, and so on. And as a startup scales, you're constantly making resource trade-offs that are less driven by what's best for the business, but instead driven by how much capital you have.

In the future, by making the barrier to entry to getting knowledge work done as simple as a website signup or API call, we will likely see a massive increase in usage of “services” that previously were near-impossible to access easily. And what's amazing is the vast majority of the usage of these AI Agents will likely come from previous areas of "non-consumption". That is to say, these will be customers that would not have spent anything on similar labor categories in a pre-AI world. Now, of course, in many cases, AI will start out worse on some dimensions than traditional forms of solving these problems, but as tooling gets better, models get cheaper and higher quality, we know the capabilities will improve over time dramatically.

We're in only the very beginning of this new era of AI-driven work, but the scale of the opportunity and the market will be massive.

[Andy Holley @AndyHolley]

@gpetriglieri As usual, beautifully said. And so true. Thank you for this, GP.

[Andy Holley @AndyHolley]

https://t.co/YA0a2dqVUl

[Andy Holley @AndyHolley]

Lifting the design potential of Japanese companies - part 2 of the series. Thanks Matt Durack, Derrick Kiker and team. https://t.co/TPPqBnxjAp

[Andy Holley @AndyHolley]

The State or Organizations 2023 … in a nutshell. https://t.co/XMss5PoqDP

[Andy Holley @AndyHolley]

What every CEO should know about GenAI… at least for now :) https://t.co/8fd3MAJKT8

[Andy Holley @AndyHolley]

5 Hallmarks of an agile organization - good reminder from the Explainer series... https://t.co/qRKpmNYk8t

[Andy Holley @AndyHolley]

Here’s what leadership looks like in organizations that thrive - good weekend reading for leaders. https://t.co/lUfilvlwRX

[Andy Holley @AndyHolley]

Leadership is an argument with tradition. It's not just a matter of skills and style. - Love this piece by @gpetriglieri.
#leadership #transformation #culture https://t.co/vWrWapyKej

[Andy Holley @AndyHolley]

Cracking the code on digital Talent: Even with recent industry layoffs, the tech talent shortage shows few signs of abating. To attract this critical segment, it’s important to understand what they want (hint: it’s not just compen…https://t.co/ESxKxGIRaU https://t.co/H0JMMfInWR

[Andy Holley @AndyHolley]

Business’s ‘It’s not my problem’ IT problem - For IT to function better, the business side of the company has to get more involved. Great food for thought on how to get tech modernization right by friends @OliverBossert and @bmuens…https://t.co/rDdr0GQIoP https://t.co/KK7wj5XzrD

[Andy Holley @AndyHolley]

https://t.co/xKhe8ephCr

[Andy Holley @AndyHolley]

The little-known history of Champagne - how three women led innovation and market breakthroughs and created some of Champagne's most lauded empires. Thanks Robert Paterson for digging this up, great way to start the weekend. #champ…https://t.co/DGfukthFPN https://t.co/IzaGHhLZaL

[Andy Holley @AndyHolley]

Great thoughtful piece on the mid-/long-term implications and critical fundamental questions arising societies, leaders and all of us with the rise of generative AI and the dawn of the “Age of AI” - by Henry Kissinger, Eric Schmidt and Daniel Huttenlocher

[Eric Schmidt @ericschmidt]

What happens if this technology cannot be completely controlled? What if there will always be ways to generate falsehoods, false pictures and fake videos, and people will never learn to disbelieve what they see and hear?
https://t.co/iVkVwlorXU

[Andy Holley @AndyHolley]

How leaders can leverage the power of dissent and the art of healthy debates to get better outcomes, even in culturally diverse contexts. Wonderful timeless piece by colleagues Ben Fletcher, Chris Hartley, Rupe Hoskin AM and Dana M…https://t.co/zNxwCB3b9J https://t.co/SrnUpCJLRq