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PRESHai 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.

10/13/2026

What happens when the worker completing the task never gets tired?

Persistent AI agents can continue researching, organizing, and executing work after the person managing them steps away. But that does not eliminate the need for management. It makes clear direction even more important.

Paul’s point in this clip from our Model Behavior podcast is that organizations must learn how to maintain a useful pipeline of work without confusing constant activity with meaningful progress.

If an agent could work continuously for your team, what responsibility would you give it first?

10/12/2026

One of the easiest AI mistakes is assuming the most capable model is automatically the best choice.

Some tasks justify additional reasoning, cost, and latency. Others need a faster, more focused system that can complete a repeatable job reliably.

Chris explains why organizations need to evaluate the model, tools, and agent setup together.

How is your team deciding which model belongs in each workflow?

10/08/2026

AI agents are moving beyond answering questions. They can now research, prepare work, operate software, and continue working while the people managing them are away.

That changes the responsibility of the people and organizations deploying them.

In Episode 11 of Model Behavior, Paul Radcliffe, Chris McGovern, and Archer Preshly discuss why choosing the "best" model is only part of the equation.

The more important questions are what an agent should own, which actions require human approval, how companies maintain accountability, and who steps in when the system fails.

The models may be ready. The real question is whether the organization around them is ready too.

Meet Dori Rivera, PRESHai’s Design Engineer for Web/UI Systems.Her experience across UI/UX, web design, graphic design, ...
10/07/2026

Meet Dori Rivera, PRESHai’s Design Engineer for Web/UI Systems.

Her experience across UI/UX, web design, graphic design, and front-end development adds valuable depth to the way we turn client requirements into clear, functional digital experiences.

Dori uses AI-assisted tools to prototype and refine ideas more efficiently while keeping design decisions grounded in human creativity and strategy.

Outside of work, she collects crystals and enjoys learning about their colors, formations, and meanings. We’re glad to have you on the team, Dori!

10/05/2026

AI shouldn't be another tool. It should be part of how you already work.

At MSP Summit, Paul Radcliffe of PRESHai joined Doug Green on the Technology Reseller News podcast to talk about building AI into existing MSP workflows, so it fits your tech stack, works with your team and actually provides value.

PRESHai is the partner that helps MSPs put AI to work. Listen to the full conversation here: https://bit.ly/4yxkVPb

Mohammad Al-Mousa joins PRESHai as a Forward Deployed Engineer with experience in production engineering, workflow autom...
09/22/2026

Mohammad Al-Mousa joins PRESHai as a Forward Deployed Engineer with experience in production engineering, workflow automation, and client-facing problem-solving. At Epic, he supported live systems, built automation tools, and helped modernize enterprise workflows. He is also expanding his knowledge of systems, AI, and software engineering through Georgia Tech’s OMSCS program.

At PRESHai, Mohammad works directly with clients to turn complex workflows into clear technical requirements and deploy AI solutions that address real problems. Outside of work, he enjoys traveling and visits at least one historical site on every trip.

Here's to turning complex workflows into AI that is practical, trusted, and ready for the real world.

Meet Jeff Monsalve, our new Forward Deployed Engineer.Jeff joins PRESHai with deep experience across AI, data, and infra...
09/17/2026

Meet Jeff Monsalve, our new Forward Deployed Engineer.

Jeff joins PRESHai with deep experience across AI, data, and infrastructure. His background spans Economics, Philosophy, and Mathematics before he transitioned into AI engineering, and along the way he has worked across data science, machine learning infrastructure, data engineering, and OpenShift/Kubernetes engineering. That combination gives him both a broad problem-solving perspective and the technical depth to build reliable, scalable AI systems.

At PRESHai, Jeff applies that experience across AI, data, and infrastructure to help develop and improve our projects. His work includes turning ideas into practical solutions, supporting the systems and architecture behind them, and collaborating with the team to build scalable, reliable products.

Outside of work, Jeff is fascinated by AI's potential to help explore what philosopher David Chalmers calls the "hard problem of consciousness": how physical processes in the brain create our subjective experiences. He is also a soccer fan and player who tries to attend a local match whenever he travels, as a way to connect with the culture of a new destination.

We’re glad to have you as part of the team, Jeff. Welcome aboard.

Will Rogers joins PRESHai as an AI Solutions Architect, bringing experience across federal cybersecurity, data engineeri...
09/14/2026

Will Rogers joins PRESHai as an AI Solutions Architect, bringing experience across federal cybersecurity, data engineering, full-stack development, AI and LLM product development, machine learning, data analytics, and product management.

His background in the natural sciences, particularly physics and chemistry, adds another dimension to his technical work. His experience in Forward Deployed Engineering has also put him directly alongside customers, where he works to understand the problem, design the architecture, and stay involved through development and implementation.

At PRESHai, Will turns complex business requirements into technical plans, architectures, prototypes, and production solutions. He works across AI workflow design, software development, data analysis, validation, and customer-facing technical strategy.

What interests Will most about AI is building systems that can work across workflows, tools, and data rather than stopping at a demonstration. He also continues to pursue personal research in AI and machine learning, combining his interests in physics and chemistry with his cybersecurity background.

We’re glad to have Will on the PRESHai team.

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?

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