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Inpossible Newsletter – July 2026

AI value has never lived in the model alone. It is built through the data the model can reach, the workflow it understands, the people shaping its decisions, and the infrastructure supporting every action it takes. When those pieces connect, AI stops being an isolated tool and becomes a business capability.

Engineers are working directly with users. AI is moving deeper into AWS environments. Models are being connected to real systems, governed with clearer controls, and measured against what actually changes inside the business.

This is what we are thinking about now: the next phase of AI will not be defined by another leap in capability. It will be defined by how deliberately that capability is integrated into the business.

Forward Deployed Engineering Is How AI Moves Faster

In Progress

AI momentum now depends on getting engineers closer to the work.

Forward deployed engineering closes the distance between the people who understand the problem and the person building the solution. That means fewer handoffs, faster learning, and AI shaped by the real workflow instead of secondhand requirements.
Neural Partners Customer Success Story

In Practice

Neural Partners needed a cloud foundation it could trust before it could safely grow.

Innovative helped harden its AWS architecture, separated the development environment from production, and created deployment pipelines designed to move quickly without putting live customers at risk. Now, features can move faster and Neural Partners has a stronger foundation for what comes next in agentic AI.
ROI, Tokenomics & the AI Bubble | AI Unplugged Ep. 15

AI Unplugged Podcast

AI ROI is getting harder to fake. More tokens do not automatically mean more value.

In Episode 15 of AI Unplugged: ROI, Tokenomics & the AI Bubble, we explore why the AI conversation is moving toward harder questions about cost, productivity, and measurable business impact.
AI Has Outgrown the Standalone Model Call

Plugged In

AI Has Outgrown the Standalone Model Call

But as experiments become part of customer experiences, internal operations, and agentic workflows, that early speed can create fragmented infrastructure, inconsistent controls, and unclear costs. Amazon Bedrock offers a way to keep access to leading models while bringing AI closer to the data, security, monitoring, and operating patterns already established in AWS.
Innovative Solutions Launches Forward Deployed Services

In Person

Introducing Forward Deployed Engineering

“AWS FDE is designed for the largest, most complex deployments in the world. But the demand for embedded AI engineers extends far beyond that tier. Growing businesses need the same model, the same agentic-first approach, the same outcome-aligned pricing, delivered through a partner who knows their environment and stays for the long term. That is exactly what Innovative Solutions provides through Forward Deployed Services.”

– Justin Copie, CEO of Innovative Solutions

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InPossible Newsletter

Inpossible Newsletter – August 2026

No single choice carries your whole system.

Businesses want one model, one decision, one person to hold the whole answer. AI rarely lets that hold for long. No single model fits every task, which is why the best systems route across several instead of betting on one. A model that performs well today can quietly fall behind within months, whether anyone is watching or not. And the reasoning behind a decision doesn’t travel on its own; it leaves the building the day the person who understood it does.

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AI Systems Have a Half-Life

AI Systems Have a Half-Life

AI systems can lose effectiveness as models are deprecated, standards evolve, and data shifts, even when the original build was excellent. This article makes the case that AI should be treated as a maintained capability rather than a finished project, and shows what that discipline looks like in practice.

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Context Debt Is the New Technical Debt

Context Debt Is the New Technical Debt

Every time an AI project changes hands, valuable business and technical understanding gets lost. This article explores how Forward Deployed Engineering preserves that context so knowledge and value can build over time.

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