AI strategy
Microsoft's new AI test generator rewrites the economics of QA for mid-market teams. Unit test writing costs drop 70%, coverage gaps close in weeks instead of quarters, and your QA spend shifts from labor-intensive test writing to strategic test quality.
AI Operations
Most mid-market companies struggle to measure AI ROI because they confuse cost savings with value creation. Here's the framework ops leaders use to move from speculation to numbers.
AI strategy
Switching to a cheaper AI model often costs more. Learn the framework for routing tasks to different models based on economics, not just price-per-token.
AI strategy
Most mid-market companies buy off-the-shelf AI models first. But there are situations where building pays off. Here's how to decide.
AI strategy
Most companies pick their first AI project backwards. They chase the sexiest idea or the one that got pitch deck attention, then spend months discovering it was unsolvable or unprofitable. Here is how operators actually pick winners.
fine-tuning
Your team wants to fine-tune a model for better performance. The estimated cost: $30-50K in data prep, training, and infrastructure. But you could get 80% of the benefit from better prompts and evals for $5K. Here's how to know which path actually matters.
AI hiring
A $50M revenue company faces a choice: hire a 3-person ML engineering team ($400K+ annually) or use a managed AI service ($100-200K annually). The wrong choice costs you either excess overhead or months of lost velocity. Here's how to decide.
AI evals
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.
AI security
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.
AI ROI
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.
AI strategy
AI collapsed the cost of a working prototype to almost nothing. The build versus buy decision most teams learned is now wrong in a specific and expensive way.
AI strategy
Most AI roadmaps stall because they treat the tool as the finish line. Here is a six-phase roadmap that gets you from strategy to production, and to durable adoption.