Hook
An AWS account with 240 Lambda functions runs infrawise analyze. The tool prints a clean summary: services detected, findings generated, no errors. A developer asks their AI assistant, wired up through MCP, "does this function have a dead-letter queue?" for a function that happens to be function #217 in the account. The assistant calls get_lambda_overview, gets back a list, doesn't find the function, and confidently tells the developer it doesn't exist — or worse, silently skips it and reasons about a different function with a similar name. No error. No warning. Just a wrong answer delivered with total confidence, because 40 functions never made it into the graph in the first place.
That was Infrawise issue #40, and it's a useful case study in how a tool whose entire pitch is "stop AI assistants from guessing" can quietly start guessing itself.
The 200-function wall
Infrawise builds an in-memory graph of a project's infrastructure — tables, functions, queues, indexes — and exposes it to AI coding assistants through 21 MCP tools. extractLambdaMetadata in src/adapters/aws/services.ts is the function responsible for pulling every Lambda function into that graph. It calls AWS's ListFunctionsCommand in pages of 50 and loops until AWS says there's nothing left:
