Software Factories: A Field Conversation when code moves at machine velocity

Software Factories: What AI Changes About The SDLC

0:00

/1308.623628

Software development is becoming one of the clearest early examples of what happens when AI moves from assistance to delegated execution.

In this Summit Evidence AI Field Conversation, I sit down with TensorLake founder Diptanu Gon Choudhury to examine how the engineering bottleneck is changing: developers are beginning to manage parallel agent work, architecture and testing are becoming more important, and the traditional SDLC is starting to look less like a linear handoff and more like an objective-led operating loop.

The broader enterprise implication is not simply faster coding. Organizations need a better operating model for machine-generated work: clearer objectives, stronger evidence, risk gates, runtime infrastructure, and feedback loops that can keep pace.

Watch the full conversation or use the audio player below.

Disclosure: I advise TensorLake. This is a Summit Evidence AI field conversation about software development, AI infrastructure, and enterprise adoption. It is not an independent product review.

Software Factories: What AI Changes About the SDLC | Jason Haupt with Diptanu Gon Choudhury

The Trust Layer: Where Enterprise Healthcare AI Gets Decided

Model quality is commoditizing. The decisive factor is now whether a system can be trusted at healthcare scale. To understand where the market is heading, look closely at the vendors quietly winning enterprise traction right now. 4 trust layers in healthcare0:00/762.3238321× A useful way to understand where

Beyond Human-in-the-Loop: Decision Telemetry for Non-Human Entities

For years, data scientists built trust by decomposing probabilistic systems into measurable tasks. That discipline still matters. But once agents act across tools, workflows, and decisions at machine velocity, task telemetry and analysis alone is no longer a sufficient baseline. Baseline Decision Telemetry0:00/845.5330151× For decades, trustworthy AI

Why AI Adoption Stalls in the Middle, and What Actually Moves it

Most large healthcare organizations have solved the C-suite buy-in problem. The harder problem — the one that actually determines whether an AI program scales or plateaus — are the layers directly below.

The Real Innovation Behind First-Dollar Coverage Wasn't the Pricing — It Was the Behavior

How Surest rewired member decision-making without rewriting provider contracts — and what the next wave of plan innovators is actually competing for.

Read more

The Trust Layer: Where Enterprise Healthcare AI Gets Decided

Beyond Human-in-the-Loop: Decision Telemetry for Non-Human Entities

Why AI Adoption Stalls in the Middle, and What Actually Moves it

The Real Innovation Behind First-Dollar Coverage Wasn't the Pricing — It Was the Behavior