Work & Insights

Case studies and notes from the front line of applied AI.

Case studies from 400+ client engagements across 10 geographies, plus essays and operating playbooks on making AI actually move the P&L.

Articles

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Why Your AI Pilot Will Fail (And When to Go Phased Instead of Big-Bang)

AI deployment

Why Your AI Pilot Will Fail (And When to Go Phased Instead of Big-Bang)

Your AI initiative has a 60% chance of stalling in pilot. The reason isn't the model or the data. It's usually the deployment decision you made before you wrote a single line of code.

July 20, 2026 · 5 min read

Is Your AI-Written Code Secure? The Vibe-Coding Security Gap

AI code security

Is Your AI-Written Code Secure? The Vibe-Coding Security Gap

AI does not write insecure code randomly. It fails hardest on exactly the things that matter most: authentication, access control, and your cloud config. The average score hides the danger. Here is what the data actually shows and what to do about it.

July 17, 2026 · 9 min read

Why Your Production AI Prompts Fail (And How to Fix It)

prompt engineering

Why Your Production AI Prompts Fail (And How to Fix It)

Your prompt works perfectly in testing. Then it ships to production and suddenly fails on 15% of real requests. The problem isn't the model. It's that you tuned your prompt to development data, not to the chaos of actual user inputs.

July 17, 2026 · 8 min read

The Real Cost of AI: What Mid-Market Operators Should Budget For

AI cost

The Real Cost of AI: What Mid-Market Operators Should Budget For

You budgeted for the model. Then came inference costs, fine-tuning, infrastructure, ops overhead, and the team time to keep it running. Most mid-market operators are shocked by month two. Here's the breakdown.

July 16, 2026 · 7 min read

Your AI Model Isn't Broken. Your Data Is.

data quality

Your AI Model Isn't Broken. Your Data Is.

Mid-market operators invest in AI models but get inconsistent results. The problem is almost never the LLM. It's what you're feeding it: incomplete, duplicated, or misstructured data that makes any model look bad. Here's how to fix it before you buy another tool.

July 15, 2026 · 8 min read

What McKinsey's State of AI Report Really Means for Mid-Market Operators

AI adoption

What McKinsey's State of AI Report Really Means for Mid-Market Operators

Universal adoption but near-zero ROI capture. Here's what actually separates mid-market winners from dabblers, and why your governance gap might be larger than your tool gap.

July 14, 2026 · 6 min read

Your AI Product Does Not Have a Model Problem. It Has an Evals Problem.

AI evals

Your AI Product Does Not Have a Model Problem. It Has an Evals Problem.

The reason most mid-market AI projects stall after the demo is not the model. It is the absence of a system to measure whether the output is any good. Here is how to build one without a data science team.

July 13, 2026 · 5 min read

You Are Giving AI Agents the Keys. Here Is How to Secure Them.

AI security

You Are Giving AI Agents the Keys. Here Is How to Secure Them.

Mid-market teams are deploying AI agents faster than they are securing them. A practitioner's guide to the new attack surface and the handful of controls that actually matter.

July 12, 2026 · 5 min read

How to Measure AI ROI: A Framework for Mid-Market Operators

AI ROI

How to Measure AI ROI: A Framework for Mid-Market Operators

How to measure whether your AI investments actually move the needle. A three-layer framework for mid-market operators: preconditions, process impact, and business outcomes.

July 10, 2026 · 6 min read