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.
Guardrails are a key consideration for AI adoption, as enterprises focus on safety, transparency, auditability, and strong access controls to ensure models operate within trusted boundaries.
Watch @alighodsi dive deep into the future of enterprise AI: https://t.co/YXlcdoyi5P
When it becomes apparent that equity in a startup is going to represent life-changing outcomes, there is an inevitable culture shift. Many early employees will do anything to keep their job and keep vesting and later-stage employees will do anything to get more equity.
You know a startup has irrevocably become a corporation when a majority of its employees stop viewing their main job as winning in the market and start viewing it as meeting the expectations of their manager — and a majority of these managers are doing the exact same thing.
I am planning to start publishing more data content in order to share my experience with the data industry. While X has a healthy data community, I have actually seen more interesting content on LinkedIn recently than I see here. Interested to hear if others see the same thing.
This is not surprising to me at all. Trust in data is not where it needs to be given the need for data-driven analysis. Yet another reason to consider @revefiinc to manage your data platform.
Over ⅓ of CFOs believe that data quality inhibits the use of AI in finance.
Explore three fundamentals to deliver AI-ready data and trusted finance insights that deliver impact across the enterprise: https://t.co/hUfWLhk9Ty
#FinanceAnalytics#DataGovernance
@CriddleBenjamin In 1992 I was a freshman and we managed to get 4 tickets so we drove up from Provo. We got snow balls thrown at us and got cussed out, but we did see Jamal Willis torch the Utes.
🚧 Construction in progress 🚧
It’s all coming together: it’s fun to see the Alation booth come to life at @SnowflakeDB AI Data Cloud Summit!
Head to booth 1330 tomorrow to see what we have in store.
Allie plushies, anyone? 👀 #datacloudsummit
https://t.co/v2QHEaBSAU
It is always kind of surreal to attend Snowflake Summit. As an early employee, it amazes me how big the company has become. It goes to show that a truly innovative idea and a ton of hard work by a lot of smart people can change the world.
If you're attending #SnowflakeSummit, join this hands-on lab!
Join us & @SnowflakeDB to learn how Snowflake and Alation can:
⚔️ Mitigate compliance risk
🔋 Boost user productivity
✅ Enhance data usage
We're offering this twice, so no excuses! ☝️
https://t.co/epwIlmo0na