Insights
Answers to the questions SaaS leaders ask before adding AI
Short, direct answers on adding agents to established vertical B2B SaaS, what production AI actually costs, choosing between AWS Bedrock, Azure AI and Vertex AI, and keeping gross margin intact.
Brownfield AI
How to add AI agents to an existing SaaS product without rebuilding it
Engineering reality
Why vibe coding is not enough for mature SaaS
Cost
How much does production AI cost in SaaS?
7 answers to the questions asked before an AI build is approved.
Brownfield AI
How to add AI agents to an existing SaaS product without rebuilding it
A practical route to shipping AI agents inside an established B2B SaaS product: use the existing permission model, integration layer and business logic instead of rebuilding around the model.
Read the answerEngineering reality
Why vibe coding is not enough for mature SaaS
AI coding tools are excellent at generating code and blind to your constraints. Here is what mature vertical SaaS needs on top of them before anything reaches paying customers.
Read the answerCost
How much does production AI cost in SaaS?
The real cost of running AI in a SaaS product: inference, retrieval, storage, egress and engineering. Indicative bands and the variables that move them.
Read the answerPlatform choice
AWS Bedrock vs Azure AI vs Vertex AI for existing SaaS
A practical comparison of Amazon Bedrock, Azure AI Foundry and Google Vertex AI for teams adding AI to an already-deployed SaaS product.
Read the answerMigration
When should an AI workload move between clouds?
The defensible reasons to move an AI workload to another cloud, the reasons that are not worth it, and how to migrate without disrupting a live SaaS product.
Read the answerUnit economics
Why AI features can damage SaaS gross margins
AI turns a fixed-cost software business into a variable-cost one. Here is how margin erosion happens and how to price and architect against it.
Read the answerCost
How to reduce AI infrastructure cost in production
Concrete levers for cutting production AI cost in a live SaaS product: context discipline, model routing, caching, placement and GPU utilization.
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