Productize Yourself: AI Proof Yourself
Your company will train you on tools, processes and compliance. It has zero reason to train you to be findable outside its walls. That skill is the reason I got a stage at TestMu Conf ’26.
Your company is doing its job here. It pays for value delivered inside the building. Your appraisal, your promotion and your L&D budget all measure that one thing. The market measures something else. It measures what people can see.
Nobody at TestMu asked for my designation or my last appraisal rating. They found me through work I’d put out in public over the years: this blog, community talks, posts. None of it was on a goal sheet. All of it travelled with me.
That’s what productizing yourself means. You take the problems you already solve at work and turn them into proof that strangers can find, trust and repeat to someone else. Same skills. Same job. Far more doors.
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TestMu Conf 2026 · 19–21 August 2026 · 31 minutes
What I covered
The questions testers avoid. I opened with a chain of questions:
- Do you want to stay in corporate tech?
- Is your job satisfying, and is it good for your future?
- Does your company keep people in bad times?
- Could you stay there for ten years? Do people there actually stay ten years?
- Is your employer’s business model future-proof?
A “no” anywhere means it’s time to productize. If every answer was yes, the talk wasn’t for you.
The reality check. The tech market isn’t evolving. It has already evolved.
- Resumes are dead as a signal, because most are now generated to look the same.
- Layoffs have become normal rather than news.
- Junior hiring has slowed for the first time in 25 years.
- AI is quietly positioned as a cheaper version of you.
Add weekly model updates, with loop engineering one week and context engineering the next, and standing out gets hard.
What productize means. It means turning your expertise into something sellable and scalable. I took the idea from The Almanack of Naval Ravikant. That book changed my life, and it’s free to download.
Four things to productize:
- Your offering. Test cases, reports, data mocks and API checks are execution-level work, and that is exactly the work AI came for. Move up: from execution to thinking (risk analysis, test design, strategy, exploration, requirements), then to systems (tools, skill and MCP libraries, agents, checklists), then to insights (RCA, case studies, research). Reading vendor case studies shows you what the market actually buys.
- Your learnings. Scrolling, bookmarking and forwarding don’t stick. Applying is what turns learning into value, so apply something today, even if it’s small. My whole profile is learnings converted into courses, talks, articles and free resources.
- Your portfolio. Everyone is talking about AI, but almost nobody is building with it. Developer portfolios have spiked since AI arrived, and tester portfolios are far behind. If you don’t make your skills public, nobody can find them. Places to start: open source and crowdsourced testing, GitHub repos of prompts, skills and agents, meetup talks, and publishing your study notes, which is how I started.
- Your branding. Who knows you matters more than who you know. Try this: ask an AI who you are. AI is becoming the interface people use to find people. Branding takes consistency and has to be authentic, so pick a platform and a community that fits you. I never applied for this talk. TestMu knew my work and invited me.
From the Q&A
- Hardest first step? Put yourself out. Share what you learned, tag the speaker, start the discussion.
- Automation tools or AI agents? Learn at least one tool so you understand how automation works. Then learn the orchestration layer above it, because that’s where the work has moved.
- Proving AI skill beyond certifications? I’ve never done a certification. My portfolio is my certificate.
This talk has a history
This is not the first time I’ve given this talk. It started as Productizing Yourself: Building Portfolio as a Tester at TestBash, and grew into Productize Yourself as a Tester. The core idea hasn’t changed. What changed is the pressure behind it: this version is about AI-proofing yourself, because execution-level work is now the first thing AI takes.
If your employer disappeared tomorrow, what would the market know about you?
Every TestMu Conf 2026 session is in the full conference playlist. More talks like this one live on my talks and podcasts page.