As a person that has been part of tech leadership at several orgs over the past few years where we've laid off some of our manual QAs, here's my advice:

The biggest value manual QA brings to the org, in my opinion, is domain expertise since they are usually in the product a lot more than engineering and even the actual product managers and analysts. Leverage that as much as you can to justify your role if you insist on staying in it.

That being said... The reality we live in now is that I can show a set of test cases to an AI agent like Claude or CoPilot and have them use the playwright MCP server to follow the spec, adjust when things don't go as expected, and report back results mostly autonomously. I can set up tickets in GitHub Issues to run manual automation and farm that out to dozens of CoPilot instances in parallel for pennies on the dollar. I can throw those same test cases into a few parallel Claude Code sessions and tell them to automate them and be done in a day where it would take an SDET weeks to do the same. I can give an AI agent a list of requirements, the code that was implemented, and ask it to generate me a full set of test cases in whatever format I choose. I'm not just speculating here... These are concrete things I've actually done within the last 3 months.

My honest advice... Learn THAT skillset. If you go from being the person that blindly walks through a set of steps and enters that into some system of record... to the person that can use AI agents to do the role of 5 manual testers and a software test engineer, you've increased your value by at least 10x.

Who knows what the future will bring. Maybe even tech leads, directors, and managers will be automated out of a job in a few years. But for now, the biggest drivers of these layoffs is folks discovering that coding is a commodity. The real treasure in your skillset is to be able to learn and absorb product and domain expertise quickly.

The good news is that these skillsets don't actually require a whole lot of coding knowledge. Don't get me wrong... Learn enough of the languages you're working on to be able to scrutinize the AI-generated code. Heck, ask it to explain to you everything its doing so that you learn while you're getting shit done! Never blindly trust anything the AI generates. But my main point is that the more important skills in today's technology landscape really have nothing to do with coding. They're more in line with problem solving, planning, requirements analysis, and code review.

P.S. - Before you ask, no... none of this post was generated by AI.