A technical recap of Fábio Velloso’s talk at Avalia Tech Forum 2026, exploring how Java supports enterprise AI and what monitoring reveals about model behaviour in production.

How hard will it be to change the software once you own it? Delivery history helps investors assess the waiting time, rework and dependence on key people that can affect a company’s ability to execute after an acquisition.

AI agents are changing how software is built, but faster development brings new questions around trust, technical debt and understanding what is being created. Olivier Liechti explores what engineering teams need to rethink as AI becomes part of the software development lifecycle.

What does it take to move AI from pilot to real operations? A look at governance, ROI, culture and scaling from the DOT Digital Group roundtable at Avalia Tech Forum 2026.

In December 2022, Southwest hit every operational target right up to the moment its technology couldn't absorb the shock. The weakness never showed up in the numbers the company tracked, until it did, at a cost of more than a billion dollars. This is the case for finding hidden technology risk on purpose, before the business depends on it.

Delivery problems usually become visible to management after they have already been developing for some time. Delivery data can show the deterioration earlier, while teams are still shipping and there is still time to react.

The way most organisations track technology spending tells you where the money went but not what it was for. And that second question is the one that actually matters for decisions.

Teams can measure every stage of software delivery and still not know if the business is getting value. Why activity isn't outcome, and how to connect them.

Why technology reporting fails at board level, how operational metrics obscure business impact, and what boards need to make better investment and risk decisions.

You do the work — but can you prove its business value to the board? How Avalia's DX Hub helps CTOs translate engineering into the language of money.

Engineering intelligence platforms make developer productivity more visible. The next challenge is connecting those insights to business priorities and decisions.

Revenue growth and an active roadmap can make a software company look healthy from the outside — but they don't show how work actually moves through the engineering org. This piece looks at what DORA, SPACE, and recent AI-adoption research reveal about the operational risk investors can't see in the financial model, and why it matters most in the months after a deal closes.

DX Hub makes technology work visible by connecting business priorities, delivery data, risks, initiatives, and AI-generated insights in one shared view.

CIOs are under pressure to prove that technology work creates real business value. But ROI does not start with the tool. It starts with the business problem. When CIOs connect technical progress to outcomes such as faster delivery, lower cost, better decisions, or reduced risk, technology becomes easier to justify and smarter to invest in.

For C-level leaders, production rate alone can create a false sense of progress. Real productivity begins when delivery creates business value the organization can trust, without increasing hidden cost through rework, instability or operational friction.

Where technology investment goes isn't always clear. Learn how linking spend to strategic objectives transforms accountability and improves the success rate of digital initiatives.

Technology productivity is broken when organizations mistake pure activity for progress. True productivity requires connecting executive strategy directly to engineering reality, shifting the conversation away from code volume and toward traceable business value. By balancing delivery speed with technical health and risk management, leaders can transform technology from a defensive cost center into a transparent driver of strategic growth.