Three earnings beats in seventy-two hours, three completely different verdicts from the market. Seven weeks to CASA26 — and nobody’s bingo card survived the summer.

At CASA25, Creo’s new CTO Jason Goecke revealed how agentic AI is transforming the way teams code, collaborate, and deliver software—at scale.

“We’ve gone from months to days.”

That one line from Jason Goecke, the newly appointed CTO of Creo Solutions, captures the heart of a quiet revolution happening inside modern development teams. During his talk at CASA25, Jason walked the audience through a pragmatic, deeply experienced view on how agentic AI isn’t just an add-on to your dev process—it can become the process.

And if anyone has the credibility to make that claim, it’s Jason. A lifelong developer with roots in call center technology since the late ‘80s, he’s seen wave after wave of transformation sweep through the software world. But according to him, this one—AI-powered development—is different.

🧠 What’s Wrong with “Vibe Coding”?

Jason didn’t mince words:

“I don’t actually like vibe coding.”

Vibe coding—where developers use GenAI prompts to generate chunks of working code—has been gaining attention for its speed and simplicity. But as Jason explained, it mirrors human shortcuts a little too well. AI that simply reflects human behavior tends to reproduce the same flaws: rushed code, weak observability, minimal testing, and fragile scalability.

“You get a working product, but it’s not ready for primetime.”

This is where Creo draws a hard line. In Jason’s view, it’s time to move past vibe coding into something deeper, smarter, and more structured.

🤖 Enter Agentic AI: Codifying Quality from the Start

At Creo, Jason and the team are embracing agentic AI—where development doesn’t hinge on one AI assistant but instead a team of domain-specific agents, orchestrated like a real dev squad.

Think of it like this:

One agent understands React. Another monitors security or runs a code scan. Another ensures observability and logging are consistent. And you, the human, are still in the loop—steering the strategy.

This isn’t a single-shot prompt. It starts with something more familiar: a product requirements doc. From there, Creo uses RootCode, an open-source agentic AI framework, to assign responsibilities to various AI agents (and humans) and orchestrate the build.

This hybrid “human + AI” team handles everything from writing secure, production-ready code to ensuring logging, monitoring, and compliance are in place—by design, not afterthought.

🌍 From Nairobi to India: Building Global Teams That Work Like One

Perhaps the most compelling part of Jason’s talk was the operational impact.

By codifying their quality management strategy and development standards into the tools themselves, Creo has massively reduced onboarding time. What used to take months of training and documentation can now be handled in a few days.

“We’re onboarding developers from India, Nairobi, and elsewhere—and they’re productive within a week.”

For any tech leader managing distributed teams, this is a game-changer.

🛠️ Open Source, Open Future

Jason ended with a powerful commitment:

Creo is open sourcing their agentic AI development setup—starting with RootCode and extending into other components in collaboration with partners like Thomas Howe and his team at Vconic.

“We want the whole ecosystem to take advantage of this.”

This fits perfectly within Creo’s broader vision of enabling smarter, faster go-to-market for CPaaS players, telcos, and enterprise platforms alike. Rather than building closed, siloed solutions, Creo is betting on community-driven innovation.

🚀 Why It Matters

Jason Goecke’s talk wasn’t a flashy demo or an AI hype session. It was a sober, experienced perspective on what it really takes to deliver quality software in the AI age—without losing control, standards, or scalability.

In an industry still figuring out how to move from experimentation to execution, Creo Solutions is showing a clear path forward. One where AI doesn’t just generate code—it enforces quality, enables scale, and empowers global teams to move fast without breaking things.

Welcome to the future of development. It’s not just fast—it’s structured, smart, and open.

📢 Stay tuned as Creo and partners release more open-source components in the months ahead—and keep an eye on how agentic AI reshapes product delivery across the CPaaS ecosystem and beyond.

At CASA25, amid the intense discussions on network APIs, GTM models, and CPaaS monetization, one panel stood out for its mix of raw honesty, technical depth, and forward-looking pragmatism: Agentic AI — Consent, Identity & Trust.

Moderated with humor and curiosity by Kyle Nel of Sandbox Industries, this panel cut through the AI hype and tackled the hard questions: What really makes AI “agentic”? How do enterprises get started without getting lost? And how do we prepare humans — not just machines — for the agentic era?

Here are the highlights and takeaways from the session featuring:

• Kyle Nel (Sandbox) – Moderator, venture investor, AI outsider-turned-ally
• Adnan Saleem (Radisys) – CTO of Software & Cloud Solutions
• Mark Castleman (Intel) – Ecosystem lead for AI and deep tech
• Olaf Wallaart (CM.com) – Lead Data Scientist, Agentic AI platform
• Remco Magielse (GLBNXT) – Startup founder tackling the “proof of concept to scale” gap

🔁 From AI Hype to Agentic Reality

Kyle opened the discussion with a simple question: “Who here is actually using agentic AI?” A few hands went up — but more had used AI in their personal lives. As he noted, the consumer world is once again leading the enterprise, signaling what’s to come.

But as Olaf Wallaart pointed out, most organizations are still trying to figure out the basics — how to write a proper prompt. The magic agent that handles everything on its own? “It doesn’t exist,” said Castleman. “You need a hundred agents, each tuned to a specific outcome, with checkpoints along the way. It’s a recipe — not a single ingredient.”

Agentic AI isn’t just a smarter chatbot. It’s the orchestration of intelligent agents capable of executing tasks, calling APIs, and interacting with other systems. But the infrastructure of most businesses — especially telcos — is still too fragmented, siloed, and legacy-heavy to support this at scale.

🎯 Where to Start: Low Complexity, High Impact

Remco’s team uses a simple framework to assess use cases: map complexity vs. impact. The goal? Find the “wow” moments — high-impact wins that are easy to implement and explain on a single slide.

“You don’t want safe,” he said. “You want something that gets people to go: Whoa, this changes how we work.”

Adnan echoed the point: “Don’t aim for sci-fi agents yet. Start with low-hanging fruit that improves productivity, then build from there.” Internal tools — like secure ChatGPT-style assistants — are often the best starting point.

🧠 AI Literacy Is the New Digital Literacy

The panel agreed that a huge part of the challenge is human, not technical. We’ve spent decades teaching people to write short keyword queries. Now, we must teach them to write long, rich prompts — to treat machines like collaborators, not search engines.

Olaf shared how CM.com formed an internal AI team tasked with helping every department identify their top problems — then co-create solutions. “They become like a beacon of AI, promoting ideas, showing what’s possible, and building internal momentum.”

Training helps. Practice is better. And curiosity is the ultimate success signal.

“Curious people engage deeply,” said Castleman. “Transactional ones don’t. Look across your org — who’s asking better questions? Those are your early adopters.”

⚙️ Infrastructure, ROI, and the Spaghetti Stack

Agentic AI reveals the cracks in enterprise systems. Legacy platforms, dirty data, and siloed infrastructure become instantly visible when you try to automate tasks end-to-end.

Castleman explained it through the lens of ROI: the cost per token per watt changes radically based on the task. Complex reasoning needs exponentially more compute — and therefore more budget. That’s why enterprises freeze: they can’t yet model the risk of going below-zero on ROI.

“The agent is the chef,” he said. “But you have to account for the entire supply chain behind each ingredient. And if the recipe isn’t worth the cost, you kill the project.”

🤝 Telcos: From Dumb Pipes to Agentic Enablers

The final part of the panel tackled the telco opportunity. As Castleman put it bluntly: “In the old app era, telcos lost because they tried to figure out the apps instead of enabling them. This time, they need to expose all the little levers and let the agents go wild.”

Agentic AI breaks apps down into atomic functions. Telcos and CPaaS players sit on a goldmine of these functions — but they must make them available as APIs that agents can trigger.

Identity, trust, and consent become key. As Olaf noted, telco networks have something unique: reliable identity. That’s a massive asset in an era where bots can imitate humans — and vice versa.

🧪 Final Words: It’s About Agency — Not Just AI

The last round of the panel shifted from tech to philosophy.

“If done right, AI gives us back our agency,” said Olaf. “We get to build quickly without begging for budget. We get to focus on what’s fun and impactful.”

AI might reduce cost. But the panel’s message was clear: it’s about productivity, creativity, and revenue growth — not just optimization.

And it’s about people. Give them tools. Train them. Let the curious ones lead.

Because in the end, agentic AI isn’t just software. It’s a shift in how we work, build, and think.

This week, OpenAI’s CFO made a bold statement:

“SaaS will be disrupted by AI.”

It’s not just a throwaway comment. It’s a flashing red signal — and one that hits especially close to home for those of us in the cloud communications space.

We’ve spent the better part of two decades moving communications to the cloud — shifting from legacy systems to UCaaS, CCaaS, and CPaaS platforms. We’ve built reliable, multi-tenant SaaS tools that serve millions of users. But here’s the reality:

The traditional SaaS model isn’t built for the AI-native era.

A Structural Shift Is Underway

Generative and Agentic AI are changing how software gets built, consumed, and valued.

More and more enterprises are realizing that they don’t have to wait for vendors to “add AI features.” They can now build their own intelligent tools — customized agents embedded directly into workflows, trained on internal data, and deployed wherever they want: cloud, on-prem, or edge.

It’s faster, cheaper, more secure, and more aligned with how teams actually work. And it’s not hypothetical. This trend is real, and accelerating.

So where does that leave cloud comms?

UCaaS & CCaaS: Adapt or Be Abstracted

For UCaaS and CCaaS players, this is both a threat and a wake-up call.

Most of these platforms are still architected around fixed workflows, static integrations, and multi-tenant control planes that were never designed for AI-native use cases. They’ve been good at incremental improvements — smarter IVRs, sentiment analysis, voice bots — but these are bolt-ons.

In the world of Agentic AI, bolt-ons aren’t enough.

We’re moving toward autonomous agents that can:

• Interpret complex conversations
• Take actions across systems
• Improve themselves over time
• Operate privately, securely, and in real time

To enable that, you need control. You need data proximity. And you need an AI-ready architecture, not just an “AI-powered feature.”

If UCaaS and CCaaS platforms don’t evolve fast, they risk getting abstracted away — reduced to dumb pipes or passive UI layers as the real intelligence moves elsewhere.

Why I Believe CPaaS Might Come to the Rescue

Here’s where I think the opportunity lies — and it’s a hopeful one.

I believe CPaaS might just come to the rescue.

Why? Because AI agents — whether internal, customer-facing, or embedded — still need to communicate. They need to:

• Place a call
• Send a message
• Start a video session
• Trigger a workflow across channels

And that’s where CPaaS shines. It provides the foundational capabilities: programmable access to voice, messaging, video, authentication, and more.

But here’s the key: the value is shifting up the stack.

To stay relevant — and capture a bigger piece of the pie — CPaaS players must:

• Embrace agentic use cases, not just programmable APIs
• Enable AI integration at the edge, in-device, or in hybrid setups
• Support sovereign AI deployments for regulated industries and privacy-conscious regions
• Offer composable building blocks, not monolithic services

If they get this right, CPaaS won’t just survive — it could thrive. It could become the backbone of the AI-native communications layer, powering everything from agent-led CX to real-time, autonomous enterprise workflows.

We Also Need Startups That Get It

While established players adapt, we also need to nurture and invest in the startups that are already building for this AI-native future.

The ones that:

• Combine deep cloud comms and telco expertise
• Understand the shifts in infrastructure and enterprise buying behavior
• Build modular, agentic, privacy-conscious tools that plug into comms networks intelligently
• Treat telcos and CPaaS platforms not as old-world dinosaurs, but as enablers of the next wave

These startups often struggle to get attention — or funding — because they sit at the intersection of two complex worlds: telco and AI. But that’s exactly where the disruption is happening.

We need to give them the capital, connections, and credibility to thrive.

This is not just about product innovation — it’s about rebuilding the entire comms stack for the next decade.

We’ll Explore All of This at CASA25

At CASA25 this September in Amsterdam, we’re devoting entire sessions to this shift.

We’ll explore:

• The rise of Agentic AI and what it means for telcos and comms platforms
• How CPaaS can evolve into an AI orchestration layer
• Why telcos are uniquely positioned to enable AI at the edge
• How startups and scaleups are already disrupting the model
• What enterprises actually need from their comms stack in an AI-native world

We’ll also showcase real use cases, startup pitches, and practical strategies to move from theory to execution.

Final Thought

The question isn’t if AI will reshape cloud communications. It’s already happening.

The real question is: who will own the new layer of value?

UCaaS and CCaaS platforms need a rethink.

CPaaS providers have a chance to lead — if they evolve.

Telcos can step back into relevance — if they seize the AI and edge opportunity.

And the startups that bridge these worlds? They may end up defining it all.

Let’s make sure we’re not just reacting — but shaping what comes next.

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📖 Read the OpenAI CFO article that inspired this post: