The market is hard. AI doesn’t fix that. But here’s what it actually does. I want to be clear about something, because I see a lot of AI hype around job searching that I don’t agree with. AI is not going to land you a job. The market is hard. Hiring is slow. Roles are more competitive, not less. There are fewer postings in some industries. Recruiters are buried. Hiring managers are picky. None of that changes because you opened ChatGPT. What AI does do is compress the time between effort and output. The thing that used to take 4 hours — researching a company, customizing a resume, drafting a cover letter, prepping interview answers — can take 45 minutes if you’re using AI well. That doesn’t mean you do less work. It means you do the same work faster, which means you can do more of it, at higher quality, with more energy left for the parts that actually matter: - real conversations - real follow-ups - real preparation AI is a force multiplier, not a magic wand. It compounds the effort you’re already willing to put in. If you’re not willing to put in the effort, no tool fixes that. If you are, AI can absolutely change what’s possible in 30 days. Where are you on this? Are you over-relying on AI, under-using it, or somewhere in between? 👀

Three things I'd change if I started over today. 1, I'd talk to humans before I touched the application portal. I spent the first 4 days in spreadsheet mode, building lists, researching companies, organizing my pipeline. I should have spent those days messaging 10 people in roles I was curious about. The intel I got later from real conversations was 10x what I got from job descriptions. 2, I'd batch my tasks instead of jumping between modes all day. The first two weeks I was researching, applying, networking, and prepping in the same hour. By Friday I was exhausted and couldn't tell you what I'd actually moved forward. Two hour blocks for each type of work, one type at a time, would have doubled my output and cut the burnout in half. 3, I'd have given myself a daily stop time. The search will eat your entire day if you let it. I had days where I worked until 11pm, applied to 20 to 30 roles in a single day, and was still trying to prep for the next morning's interview. A clean stop time at 6pm would have made the whole month sustainable. What would you do differently in your search if you started over tomorrow?

Most people skip context when they prompt AI. Then they wonder why the output is generic. Here’s a 4-line primer you can paste at the top of any new chat (if you’re not using a Project or Custom GPT yet). Fill in your specifics, then ask whatever you need. I’m a [your level] [your function] with [years] years of experience in [industry]. I’m currently searching for [target role] roles at [company stage/size]. My non-negotiables are [3 things] and my deal breakers are [2 things]. Be direct, push back on weak ideas, and don’t pad your responses. That’s it. Four lines. Drop that in before you ask Claude, or your preferred GPT, to review your resume, draft a cover letter, prep you for an interview, or evaluate a JD. The output will get sharper immediately because the AI now knows who’s asking and what good looks like for you. The reason this works: AI defaults to safe, generic, middle-of-the-road advice when it doesn’t know who you are. Once it knows, it can actually be useful. This isn’t a guide prompt, it’s a context primer. Use it on top of any prompt you’re already running. Try it this week and tell me what shifted in the output.

Quick reframe. If you turned down a recruiter pitch this week because the role wasn’t right, that’s a win. If you withdrew from a process because the comp was insulting, that’s a win. If you walked away from a job that felt toxic in the first interview, that’s a win too. A bad job will cost you more than no job. Six months in the wrong role can set your career back two years and leave you searching again with worse stories to tell. Saying no is not failure. It’s strategy. Last year, mid-search, I declined to move forward in a process I knew wasn’t right. The role looked great on paper. The conversations told me everything I needed to know. I said no, kept searching, and the right offer landed two weeks later. The “no” cleared space for the “yes.” Anybody say no to something this week? Drop it below. We celebrate the no’s here too.

How to actually evaluate AI output before you trust it People ask me how I know when to trust what AI tells me. Short answer: I don’t, not until I run it through three checks. 1. Does it sound like me? - If AI rewrites your resume bullet and you wouldn’t say it out loud in an interview, cut it. The bullet has to survive the “tell me about this on your resume” question. - If it feels too polished, too corporate, or full of words you don’t actually use, edit it down or scrap it. 2. Is the claim verifiable? - AI will confidently tell you a company is known for something with no real source behind i - Treat claims about companies, salaries, hiring practices, and industry trends as starting points, not final answers. Run them through Perplexity or a quick Google search before you repeat them in an interview. 3. Would I push back if a coworker said this? - If a trusted coworker gave you the same advice or rewrite, would you accept it immediately? - Or would you pause and say, “Hmm, not sure about that one”? Bring that same energy to AI output. It’s a smart assistant, not an oracle. Run every important output through these three checks before you use it, especially if you’re about to send it to a real person or say it in a real interview. What’s the worst AI output you almost trusted? Drop it below.