Performance testing is more than sending lots of requests.
I wrote a practical guide on designing realistic API performance tests - from user journeys and expected load to environments and metrics.
dev.to/gramli/api-per…#testing#api#performance
Code got cheaper. Maintenance didn’t.
As more open-source libraries move toward commercial or dual licensing, I’m asking whether AI is accelerating the shift,not by creating the problem, but by increasing the pressure on maintainers.
What do you think?
AI endpoints are not just thin proxies around a model call.
They change API flow: validation moves into post-processing, retries become semantic, and the backend decides whether the generated result is reliable enough to return.
dev.to/gramli/how-ai-…#AI#API#Architecture
I built a minimal WebMCP agent using Playwright and Gemini.
Gemini requests a tool call, and Playwright executes the matching WebMCP tool inside a real Chrome browser.
Article 👇
dev.to/gramli/build-a…#ai#WebMCP#Playwright#Gemini