AI Startups & SaaS

The build trap

AI startups move fast by design. The problem is that moving fast without a clear architecture locks in decisions that are expensive to undo — model choices, data pipelines, evaluation frameworks, prompt structures, and inference costs all compound early and compound wrong.

Most teams discover the architectural problem after the first demo fails in production, not before.

What usually goes wrong

• Model selection is driven by what is newest rather than what fits the latency, cost, and capability requirements
• Prompt architectures are built ad hoc and become unmaintainable as product complexity grows
• Evaluation pipelines are skipped early and become urgent later, when quality regressions are already affecting users
• Context window management is not designed for edge cases until those cases start causing failures
• AI cost structures are not modeled until burn rate becomes an existential question

How I help

Stress-test the architecture before committing the engineering team to it.

• Assess your current AI system design, model choices, evaluation approach, and infrastructure dependencies
• Identify where the architecture will break under real usage — scale, edge cases, cost, latency
• Map a technical roadmap that gets to a defensible v1 without burning runway on avoidable rework

Where architectural guidance actually helps

• Model selection and orchestration design tuned to your use case, budget, and scale requirements
• Prompt architecture review and restructuring for maintainability and performance at production volume
• Evaluation framework design: how to measure what matters before users measure it for you
• RAG and retrieval system design for knowledge-intensive products where retrieval quality determines output quality
• AI cost modeling: inference, context, storage, and API dependencies — before they become surprises

What you get

An architectural assessment with prioritized risk findings, a technical roadmap for the next 90 days, and design recommendations that the engineering team can act on without a full rewrite. Built for founders and technical leads who need an outside perspective before the first big architectural commitment.