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Agentic AI in Production: Three Architecture Patterns for Mid-Market Engineering Teams
Multi-step AI agents are powerful and failure-prone. This post covers the three architecture patterns that appear in most production agentic systems and the operational considerations that most tutorials skip.
Prompt Engineering at Scale: Version Control, Testing, and Deployment for Production LLM Systems
Prompts are code. Most teams do not treat them that way until a silent regression costs them. This post covers the engineering discipline that production prompt management requires.
Reducing LLM API Costs in Production: A Framework for Engineering Teams at Scale
LLM API costs at development scale are noise. At production scale with 50,000 daily users, they become a significant budget line. Here is the four-lever framework for keeping them under control.
An AI enablement roadmap for mid-market: a framework for the messy middle
Mid-market AI enablement (50-500 person companies) is the work of moving from "individual employees use AI tools" to "the organization has a coherent AI capability." The standard enterprise AI playbooks were written for organizations with internal data science teams, dedicated CIOs, and multi-year transformation budgets.
AI Center of Excellence structure for 50-500 person companies
An AI Center of Excellence (CoE) at mid-market scale is a small coordinating function -- typically 1-4 people -- that maintains shared AI capabilities, supports product teams building AI applications, and represents AI in technical decisions.
An LLM governance framework for mid-market companies
LLM governance at mid-market scale (50-500 employees) is the small set of policies, processes, and reviews that prevent AI use from causing harm without blocking AI use from creating value.
GenAI deployment patterns for B2B SaaS
B2B SaaS companies deploying GenAI features face a recurring set of design decisions: where in the product the AI lives, how customers control its behavior, how multi-tenancy interacts with model context, and how pricing surfaces the cost.
Build vs buy vs hybrid for enterprise AI initiatives at mid-market scale
None of build, buy, or hybrid is universally right for mid-market AI initiatives. Buy fits well-defined commodity use cases (transcription, basic chat support, document Q&A).
An AI enablement maturity model: assessing where your organization stands
An AI enablement maturity model gives an organization a structured way to assess where it currently stands across the dimensions that determine AI capability.
What 7 mid-market AI enablement engagements taught us
Between Q3 2024 and Q1 2026 we ran seven AI enablement engagements for mid-market companies (50-500 employees, varied industries: B2B SaaS, e-commerce, healthcare-tech, financial services, manufacturing).