John Kreisa

AI agents shouldn’t just access your data. They should understand it. With AI-powered semantic understanding, teams can ask questions in plain English and get answers grounded in real business context. This is how enterprise AI moves from queries to real understanding. Learn more: sema4.ai/products/dynam…

Security for AI agents comes down to one question: where are they running? If the answer is outside your environment, you don't have full control. @paulcodding, Co-Founder and SVP of Product and Customer Experience, shares what it actually takes to secure agents in production – why keeping agents inside your own infrastructure matters, how layered security + role-based access work in practice, and what full visibility actually looks like.

@WalkerATX @UTAustin @fox7austin That’s how I did it in ‘85!

It's 1982 in Austin and you're registering for classes 🤘@UTAustin @fox7austin

The era of manual data wrangling is over. AI agents are transforming the Office of the CFO with 90%+ automation across invoice reconciliation, payments, and AP workflows, cutting processing time from days to minutes. With mathematical precision and hands-off reconciliation, teams gain accuracy, control, and faster outcomes.

The biggest misconception in enterprise AI: the model is the differentiator. It’s not. What actually matters is whether your agents can truly understand and operate on your data. 🎥 @paulcodding , Co-Founder and SVP of Product and Customer Experience, breaks down what separates experiments from real systems.

Here is a great article about Ripple Effect in Lookout Magazine thanks to @wallacebaine lookout.co/the-big-ripple…

I’m super excited about a new arts festival we’ve been working on here in Santa Cruz. The Ripple Effect Arts Festival is a celebration of the amazing artistic talent in Santa Cruz county. This is the inaugural year but hopefully it will grow and grow! rippleartsfestsantacruz.org

When AI moves into finance, the stakes shift entirely. It stops assisting and starts deciding, and that changes everything about how you need to govern it. Finance requires: •zero error tolerance •real audit trails •the ability to step in instantly Co-Founder and SVP of Product and Customer Experience @paulcodding on governing in finance. ⬇️

Ready to move from AI experiments to production? Join us March 25 at the Snowflake Silicon Valley AI Hub for a hands-on workshop on building production-ready AI agents in Snowflake. Learn to build with Python, SQL, and runbooks, connect to enterprise data with zero-copy access, and deploy securely at scale. Register: luma.com/n72a0mv3?tk=5e…

We’ve loved connecting with everyone this week at the @Gartner_inc Data & Analytics Summit. If you’re in Orlando, stop by Booth #207 and join our session today at 2:00 PM ET: “From Data Silos to Intelligent Action: Building Enterprise AI Agents That Work with Your Data.” See live demos and learn how organizations are moving beyond stalled automation to AI agents that execute real work across enterprise data.

Most AI agent deployments stall after pilots. The missing piece? A semantic layer that lets agents understand enterprise data across databases and documents. In our latest blog, Paul Codding, Co-founder and SVP of Product and Customer Experience at Sema4.ai, shares a bold take: “The semantic layer is the most underestimated capability in enterprise AI.” Read more: sema4.ai/blog/semantic-…

Getting value from enterprise data shouldn’t require SQL or complex pipelines. Today at the @Gartner_inc Data & Analytics Summit, Sema4.ai announced the GA of our Semantic Layer, helping AI agents understand enterprise data and enabling business users to analyze structured and unstructured data faster. Learn more: sema4.ai/newsroom/sema4…

@EvanKirstel @sema4ai Bold claim yes, but with the right tools and platform this can happen.

Bold claim: 2026 belongs to AI agents. We map the ecosystem, the platform play, and a crawl-walk-run path to measurable ROI. Back office to boardroom, this is the autonomy shift. Will your team be ready or left behind? @sema4ai x.com/i/broadcasts/1…

74% of enterprises are investing in agentic AI workflows, and that shift is happening now. This isn’t about exploration anymore, it’s about execution. Trust is growing, integration is underway, and AI agents are moving into the heart of business strategy. Learn how to get started: sema4.ai/learning-cente…

Excited for the rebirth of the Santa Cruz Film Festival!

Enterprise AI made simple. With @sema4ai and Docker’s MCP Gateway, business users can build agents in natural language and connect instantly to tools like Stripe, Box, and Slack. Secure, scalable, and powerful. youtu.be/HaGeP6nPTeQ

Great to be partnering with @docker on this!

@levie I agree with this take. It takes longer to agentify a multi-step or complex human in the loop process but the gains once implemented can be on orders of magnitude scale. That is consistent with what we are seeing.

There really are 2 different worlds of AI adoption right now. Most individuals, teams, and organizations have *finally* gotten around to implementing AI chat systems for the first time. But this is happening at the exact same moment when it’s getting clearer what the future of AI agents are going to look like. The type ahead or chat interaction paradigm of AI maxes out at double digit productivity gains because you’re inherently rate limited by how fast you can type or interact with the system. You’re still doing most of the work, and AI is just providing quick answers and suggestions to move you along faster. The AI agent model, where you can run many agents in the background in parallel, actually can deliver multiples in productivity gains. Coding is where we’re seeing this first, but it will come for most categories of knowledge work. The only trick is that it’s likely not as easy to adopt as the first paradigm was, because it requires a change in workflow. But those that get there are going to see the future faster, and get more compounding returns, than those that don’t.

This is tomorrow, worth checking out!