Zach Lawryk

🍖🚵🏼💻🐶👨‍👩‍👦‍👦

[Aaron Levie @levie]

Having talked to hundreds of IT leaders over the last year alone, it’s clear we have a capability overhang where the current AI models are already very good at solving many problems that haven’t been adopted yet.

The biggest hurdles generally are the imagination for what’s now possible, the sheer speed at which the tech is changing, and the change management to make it happen.

In tech, it’s natural to experiment with lots of solutions and do a lot of work to make something work. But outside of tech, other than for a small percentage of the largest companies, these capabilities need to be packaged as working solutions to clear problems.

The big opportunity right now is building domain specific AI Agents that tap into today’s AI capabilities but bring a high degree of domain understanding, a UX pattern that fits the use-case, and support for actually doing the change management in the enterprise.

Without this set of factors, the adoption is going to be slow. But with them you have a potent advantage.

[Zach Lawryk @zlawryk]

@Jason @grok summarize best long term plays for
me

[Aaron Levie @levie]

Lots of conversation on what the future of software looks like in the enterprise. Here’s how I think it plays out.

For deterministic workflows where the cost of getting something wrong is high, enterprises will have a tendency to pick core platforms for their most common, important, and repeatable functions in the organization. Think payroll, ERP, CRM, ITSM, customer support, ECM/document management, and so on. These are areas where you want something done the same way, every time.

Each of these platforms will have to be AI-first by design, which means that they will have user interfaces that become tuned for interacting with the workflows and data via AI, and be fully designed for AI agents to operate in the platforms. Over time, we can expect usage on these systems to bias far more to AI agents than even people. The seat model remains for the users, but consumption becomes the model for agents. Some incumbents will make it to the end state, but others will not adapt quickly enough and die off.

There will then be a new crop of effectively Agent-only companies that are purpose-built for automating specific types of work (and especially for non-deterministic work). Their business models will tilt even more consumption. Think Claude Code or Devins (likely with some UI layer for managing the agents) but for various job functions. We will likely see hundreds or thousands of these emerge over time. Pen testing, coding, bug finding, compliance reviews, financial analysts, and so on. This is a huge space where startups will do quite well because there will tend to not be any software incumbents in these categories.

We will interact with these various agents from a mix of the software platforms that they are tied to (like Box AI, or Agentforce), via APIs in other systems, and horizontal workflows systems that stitch together agents across platforms (like ServiceNow, IBM Watsonx, Google Agentspace, and so on).

And of course, users will often consume these agents via horizontal chat experiences (like ChatGPT, Claude, Perplexity, Grok, Copilot, etc.) via MCP or other types of direct connections. Users will commonly work in these horizontal chat systems, pulling in the agents, data, and workflows from the various Agentic platforms as needed. When relevant, l they will hop into the core platforms to complete workflows, review information, etc.

There will also be a longtail of experiences where users can generate micro apps on the fly when they need quick applications or use cases automated, when there’s no obvious piece of software to do that with. This may happen directly in the horizontal chat systems, a tool like Replit, Lovable, or in workflow automation tools, etc. I’d expect this is more for the power users where they need glue between multiple systems or where no software yet exists.

The net of it is that software becomes only more important over time, even if the modalities where we’re interacting from change and expand. Similar to how we hop between our phones and desktop computers with ease, even though they could easily converge, the future will offer a mix of ways of interacting with software.

[Zach Lawryk @zlawryk]

@HarryStebbings 1.56b, 68% margin, <1k employees, immigrant founder @HarryStebbings

[Zach Lawryk @zlawryk]

@HarryStebbings Verisign

[Zach Lawryk @zlawryk]

@unusual_whales What is Silicon Valley? All of San Francisco, the Peninsula, and the South Bay?

[The Twenty Minute VC @twentyminutevc]

CAREER ADVICE FOR YOUNG FOLKS:

“It doesn’t matter how fast the company is growing, how great the technology, or how big the TAM.

If you don’t feel like you’re learning from the people you’re surrounded with, you’re in the wrong spot.”

@zlawryk @Rippling explains👇

[Bill Gurley @bgurley]

That said, these adjustments are meeting with shock & surprise when it comes to the employee base, particularly those employees in the Bay Area. During this rate induced boom, competition for employees created a Disney-esque set of experiences/expectations in high tech companies.

[Zach Lawryk @zlawryk]

@zebulgar You should specify. Only applicable for very early stage companies and obviously correlated to company size. Series C is about even.

[Zach Lawryk @zlawryk]

@lpolovets @hunterblock knows

[Zach Lawryk @zlawryk]

@Kellblog Is a responsive website on the list? I love your blog but like to read on the go. User error?

[Zach Lawryk @zlawryk]

@HarryStebbings Congrats @HarryStebbings !

[Zach Lawryk @zlawryk]

@NWischoff @NWischoff I think you will love https://t.co/YIwB3VVkyT - great team, massive market, challenging industry often overlooked by traditional vcs

[Zach Lawryk @zlawryk]

@RTGPodcastDFS @MountKos Enjoy @MountKos !

[Zach Lawryk @zlawryk]

@singhns @Linksys @googlenest You can have five google mesh points?

[Zach Lawryk @zlawryk]

@LiebermanAustin What about twitter?

[Zach Lawryk @zlawryk]

@adcock_brett Thats a lot of dudes.

[Zach Lawryk @zlawryk]

@Austen A lot of managers/leaders are not prepared. Simple expectation and objective setting = productivity. I hear more people talking about how many people ‘arent working’ and leadership is to blame. It is pretty easy to figure out who’s working and who isn’t, remote or otherwise.

[Zach Lawryk @zlawryk]

@jasonlk 🤞🤞🤞🤞🤞

[Zach Lawryk @zlawryk]

@HarryStebbings If you dont retain, you cant complain.