Presh Marketing Solutions

Presh Marketing Solutions AI, implemented. For the IT channel. We architect and ship the agentic systems that separate the companies who lead this era from the ones who watch it.

AI model comparisons focus on intelligence, speed, and cost. They often overlook the system that determines how the mode...
09/08/2026

AI model comparisons focus on intelligence, speed, and cost. They often overlook the system that determines how the model operates.

That system is the agent harness. It controls the tools the agent can use, the context it receives, the systems and data it can access, how its work is verified, and what evidence is recorded.

Two platforms can use the same model and produce very different results. The agent harness determines whether that model can perform reliably in real workflows.

When AI supports a customer-facing or revenue-impacting workflow, a failure can quickly become an operational problem.Do...
09/04/2026

When AI supports a customer-facing or revenue-impacting workflow, a failure can quickly become an operational problem.

Document the fallback before you need it. Make sure the team knows it. Test it under real conditions.
What workflow would you put to the test first?

08/28/2026

Local agents can be useful, but long-running work becomes difficult to scale when closing a computer can end the session. Moving the workflow into a controlled cloud environment gives the agent persistent context, a file system, an ex*****on sandbox, and access to approved tools.

08/27/2026

The biggest risk in the AI data-center buildout may not be circular capital. It may be where the credit risk lands.

At the PORTS-Pike campus, SB Energy will build, own, and operate the data center. OpenAI is the tenant. NVIDIA is providing conditional residual-value guarantees tied to the initial buildout and taking on a form of infrastructure exposure that goes well beyond selling chips.

We look past the headline number and ask the more useful question: If the assumptions fail, who is responsible for the downside?

08/26/2026

AI hasn’t cured cancer. But personalized cancer-vaccine research is making measurable progress.

The more useful question is where computational tools and AI (when it is actually part of the workflow) can help researchers handle the patient-specific complexity behind an individualized treatment.

08/25/2026

Three AI stories that sound unrelated reveal the same practical challenge.

Personalized cancer-vaccine research raises questions about what AI contributed and how to expand access without overstating the science. Cursor Origin raises questions about the context, tools, permissions, and rollback paths cloud agents need. NVIDIA’s infrastructure strategy raises questions about who carries the financial and community risk behind the data-center buildout.

Episode 10 of Model Behavior connects all three without flattening their differences. The useful takeaway is to look beyond the model and examine the full system around it.

08/17/2026

The release decision for a high-capability model is not just a product decision. It is a readiness decision.

We consider the value of testing, staged access, and giving security teams time to prepare before broader release.

How should organizations balance speed with preparedness?

08/15/2026

If a system is capable of pursuing an outcome, it may find paths that are not obvious to the people supervising it.

Here, our hosts discuss a reported agent messaging scenario and the operational takeaway for security teams: observability needs to extend beyond the interfaces you expect to matter.

08/13/2026

Giving an AI agent more autonomy does not remove the need for controls. It makes those controls more important.

We break down the practical safeguards teams should have in place before treating auto mode as part of their operating model.

What is non-negotiable in your environment?

08/13/2026

Breaches are not just a prevention problem. They are a preparedness problem.

Teams building resilient systems know what they can isolate, how to stop damage, and how to recover. We share four questions worth rehearsing before an incident puts them to the test.

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