Nathaniel Whittemore

Both the normal and max versions produce a pretty significant bump to relevant benchmarks, with the max version now state-of-the-art compared to GPT 5.4 and Opus 4.6.

Interestingly, the agents are still just Gemini 3.1 Pro under the hood, the same as the previous version of Deep Research.

This means the entire improvement was driven by harness upgrades and additional inference rather than a more advanced model.

The agents are only available through the API, so they are designed to be used in professional workflows.

Google said that DeepResearch Max is designed to consult significantly more sources and identify critical nuances that are overlooked by other agents.

They wrote, The result is a nuanced report that draws from authoritative sources like SEC filings and open access peer-reviewed journals, lays out information well, and transforms dense technical data into actionable stakeholder-ready formats.

A small upgrade on the surface, but one which could be extremely valuable to people who have a deep research use case.

For now, though, of course, that is not the new model that everyone wants to talk about today.

So that is going to do it for the headlines.

Next up, the main episode.

All right, folks, quick pause.

Here's the uncomfortable truth.

If your enterprise AI strategy is we bought some tools, you don't actually have a strategy.

KPMG took the harder route and became their own client zero.

They embedded AI and agents across the enterprise, how work gets done, how teams collaborate, how decisions move, not as a tech initiative, but as a total operating model shift.

And here's the real unlock.

That shift raised the ceiling on what people could do.

Humans stayed firmly at the center while AI reduced friction, surfaced insight, and accelerated momentum.

The outcome was a more capable, more empowered workforce.

If you're looking to adopt an agentic SDLC, Blitzy is the key to unlocking unmatched engineering velocity.