How do you keep related when AI is reshaping every little thing you’ve discovered as a PM?
In case you’re a product supervisor who’s constructed dashboards, shipped cell apps, or optimized person flows — congrats. You’ve completed significant work. However currently, each different job itemizing desires expertise with LLMs, embeddings, or multimodal AI.
So what do you do when your resume screams “transport velocity” and the market desires “token effectivity”?
You reposition, not restart.
This information walks you thru how one can market your self as an AI Product Supervisor, even if you happen to’ve by no means educated a mannequin.
You don’t must be a machine studying engineer. However you do must reframe your previous product work by an AI lens.
Let’s say you led a venture that added customized tags to a person database.
That’s not only a UI characteristic. It’s structured information enrichment important for AI fashions.
You helped create cleaner inputs. Labeling. Group. Relevance.
You’ve already been a part of workflows AI groups care about. You simply weren’t calling it that but.
Fast tip: Re-read your resume. Exchange “added filters to go looking” with “enabled structured information for downstream personalization.”
Nobody expects you to implement backpropagation. However if you happen to’re in conferences the place folks say “RAG,” “fine-tuning,” or “zero-shot studying,” you shouldn’t blink.
Concentrate on ideas like:
- Supervised vs unsupervised studying
- Embeddings
- Inference vs coaching
- Immediate engineering
- Information labeling and analysis metrics (accuracy, F1, and many others.)
Assets:
You don’t want a unicorn aspect venture. You want a sign that claims, “I get it.”
Examples:
- Use Zapier to construct a easy AI-powered chatbot in your private web site
- Create a figma prototype of an AI co-pilot inside a device you’ve labored on
- Annotate a small product dataset in Label Studio and clarify what a mannequin might be taught
Deal with it like a product. Present the downside, resolution, and influence — even when hypothetical.
In case your profile says “Digital PM with agile expertise” you’re mixing in.
You wish to sign curiosity, readiness, and relevance.
Headline:
Earlier than: “Senior Product Supervisor | B2B SaaS | Roadmaps & Supply”
After: “Product Supervisor | Constructing AI-Enabled Experiences | Person-Centered + ML-Conscious”
About Part:
Point out your AI-related learnings, instruments you’ve explored, and the way you body AI trade-offs with person worth in thoughts.
Expertise:
Spotlight cross-functional work with information groups, experimentation, tagging programs, personalization — something that aligns with ML workflows.
You don’t want a weblog. However sharing 1–2 posts on:
- The way you’d enhance an AI characteristic (e.g., Notion AI, Duolingo Max)
- What shocked you when constructing with GPT-4
- What AI means for belief, UX, or edge instances
It’s not about virality. It’s about sign.
One teardown put up can get you an interview. One first rate remark can earn you a referral.
Use “AI-literate” key phrases:
- Collaborated with ML groups
- Labored on options powered by NLP or advice programs
- Outlined information necessities for personalization
Don’t chase “deep tech” roles except you’ve obtained the chops.
As a substitute, discover transitional roles:
- Productiveness instruments utilizing AI (e.g., Notion, Coda, Grammarly)
- Healthtech with diagnostic assist instruments
- Inner AI instruments at massive orgs (e.g., Salesforce, HubSpot)
Search for jobs the place AI is the layer, not the product.
AI PMs aren’t unicorns.
One of the best ones know how one can ask sharp questions, body person issues clearly, and translate ambiguity into motion.
Sound acquainted?
Good. That’s your story. You simply want to start out telling it like an AI PM would.
