Tommy Ryan

CEO of ThreeWill. Passionate about employees thrive on Microsoft technologies. Other interests are organic gardening and photography.

[Tommy Ryan @tommyryan]

Check out the latest article in my newsletter: When Too Much of a Good Thing Becomes a Problem https://t.co/7HW6PnX00n via @LinkedIn

[Tommy Ryan @tommyryan]

Check out the latest article in my newsletter: The Joy of Giving Forward https://t.co/ry0s8E5qIb via @LinkedIn

[Tommy Ryan @tommyryan]

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[Tommy Ryan @tommyryan]

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[Aaron Levie @levie]

Headless software is the future

[Tommy Ryan @tommyryan]

Who Tends the Farm When You’re Gone? https://t.co/UruHalMWc0

[Tommy Ryan @tommyryan]

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[Aaron Levie @levie]

Whether it’s existing consulting firms, new ones that emerge, FDEs from agent vendors, or new internal agent engineering roles, the amount of work that is going to be created to implement agents in enterprises will exceed anything we imagine today.

The complexity of implementing agents in any existing organizations is very real. When I talk to large enterprises, as you move from a chat paradigm to agents that participate in meaningful workflows, there are a number of things they need to do.

First, you have to get agents to be able to talk to your data securely across your systems. In many cases, enterprises have decades of legacy infrastructure that contain the valuable context for AI agents. That’s going to take a ton of work to go modernize and move to systems that work well with agents.

Then, you need to ensure that you’ve implemented agents with the right access controls and entitlements, the right scopes to be safely used, and have ways of monitoring, logging, and securing the work that they do.

Next, you need to actually document the processes in the organization in a way that agents can utilize for doing the work. You also need to figure out what the new workflow looks like when agents and people are working together on a process, and who steps in where. Just replicating the old workflow will mute the gains. Oh and you likely need to create evals for your top new end-state processes.

Finally, you have to keep up with a rapidly changing set of best practices and architectural shifts happening in the agent space. While it’s fun for people to change their personal productivity tools on a dime, it’s 100X harder to do this in a business process. The speed of change is a blessing and a curse right now for anyone trying to keep a stable system design.

All of this means that individuals and companies that develop expertise on the above set of components (and more) are going to be needed to help organizations actually implement agents at scale. This is also the rationale for vertical AI agents right now that can go in deep on a business domain and help bring automation to it.

This is a huge opportunity right now whether you’re doing this internally or as an external business provider.

[Tommy Ryan @tommyryan]

Check out the latest article in my newsletter: The Pressure of Spring https://t.co/TNWEhRXWea via @LinkedIn

[Tommy Ryan @tommyryan]

Check out the latest article in my newsletter: The Return of Abundance https://t.co/Dk5L95cywU via @LinkedIn

[Tommy Ryan @tommyryan]

“AGI is not here yet, change management is the real challenge.” https://t.co/ey0zRMtv1T via @YouTube

[Tommy Ryan @tommyryan]

Check out the latest article in my newsletter: 🌱 When Stress Strengthens Growth https://t.co/mtPP5gWCWd via @LinkedIn

[Tommy Ryan @tommyryan]

Really appreciate with @levie does to share his insights for Enterprise AI adoption. I am seeing a similar posture in our clients. Agents are becoming real, but also take real work to get there!

[Aaron Levie @levie]

Another week on the road meeting with a couple dozen IT and AI leaders from large enterprises across banking, media, retail, healthcare, consulting, tech, and sports, to discuss agents in the enterprise.

Some quick takeaways:

* Clear that we’re moving from chat era of AI to agents that use tools, process data, and start to execute real work in the enterprise. Complementing this, enterprises are often evolving from “let a thousand flowers bloom” approach to adoption to targeted automation efforts applied to specific areas of work and workflow.

* Change management still will remain one of the biggest topics for enterprises. Most workflows aren’t setup to just drop agents directly in, and enterprises will need a ton of help to drive these efforts (both internally and from partners). One company has a head of AI in every business unit that roles up to a central team, just to keep all the functions coordinated.

* Tokenmaxxing! Most companies operate with very strict OpEx budgets get locked in for the year ahead, so they’re going through very real trade-off discussions right now on how to budget for tokens. One company recently had an idea for a “shark tank” style way of pitching for compute budget. Others are trying to figure out how to ration compute to the best use-cases internally through some hierarchy of needs (my words not theirs).

* Fixing fragmented and legacy systems remain a huge priority right now. Most enterprises are dealing with decades of either on-prem systems or systems they moved to the cloud but that still haven’t been modernized in any meaningful way. This means agents can’t easily tap into these data sources in a unified way yet, so companies are focused on how they modernize these.

* Most companies are *not* talking about replacing jobs due to agents. The major use-cases for agents are things that the company wasn’t able to do before or couldn’t prioritize. Software upgrades, automating back office processes that were constraining other workflows, processing large amounts of documents to get new business or client insights, and so on. More emphasis on ways to make money vs. cut costs.

* Headless software dominated my conversations. Enterprises need to be able to ensure all of their software works across any set of agents they choose. They will kick out vendors that don’t make this technically or economically easy.

* Clear sense that it can be hard to standardize on anything right now given how fast things are moving. Blessing and a curse of the innovation curve right now - no one wants to get stuck in a paradigm that locks them into the wrong architecture. One other result of this is that companies realize they’re in a multi-agent world, which means that interoperability becomes paramount across systems.

* Unanimous sense that everyone is working more than ever before. AI is not causing anyone to do less work right now, and similar to Silicon Valley people feel their teams are the busiest they’ve ever been.

One final meta observation not called out explicitly. It seems that despite Silicon Valley’s sense that AI has made hard things easy, the most powerful ways to use agents is more “technical” than prior eras of software. Skills, MCP, CLIs, etc. may be simple concepts for tech, but in the real world these are all esoteric concepts that will require technical people to help bring to life in the enterprise.

This both means diffusion will take real work and time, but also everyone’s estimation of engineering jobs is totally off. Engineers may not be “writing” software, but they will certainly be the ones to setup and operate the systems that actually automate most work in the enterprise.

[Tommy Ryan @tommyryan]

Check out the latest article in my newsletter: Who Tends the Farm When You’re Gone https://t.co/U559PHUFie via @LinkedIn

[Tommy Ryan @tommyryan]

Check out the latest article in my newsletter: The Work Before the Harvest https://t.co/6LADPFGH6W via @LinkedIn

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Check out the latest article in my newsletter: Growth Needs Light, But Not All at Once https://t.co/ZM2S0qn8sf via @LinkedIn

[Cybertruck @cybertruck]

As standards got tougher in 2026, Cybertruck is the only pickup with both an IIHS Top Safety Pick+ Award AND NHTSA 5-star safety rating

[Tommy Ryan @tommyryan]

Check out the latest article in my newsletter: What the Farm Teaches Us About Giving Forward https://t.co/qTXHkDpNcY via @LinkedIn

[Tommy Ryan @tommyryan]

Check out the latest article in my newsletter: The Strength We Borrow https://t.co/uBB0b3TAnv via @LinkedIn