Category: Personal

  • My Job Search at 50+: The Data Behind Landing a Tech Job in 2025

    My Job Search at 50+: The Data Behind Landing a Tech Job in 2025

    Author: Nicholas Hart
    Date: Thursday, October 16, 2025
    Reading time: 8-9 minutes


    Tech Job Seeking in 2025

    After 8 months and 90 applications I finally landed a job! I have never experienced a job market this tough during my whole career in software engineering–either as an individual contributor or manager. Anecdotally I see a lot of posts on LinkedIn about people struggling with the job market. I’ve never been out of work more than a month or so until now. It feels like this period in 2025 is different.

    What’s different? Is it a realignment within tech spurred by AI and shortsighted tech CEOs chasing after more profit? Is it the fact that I’m over 50? Perhaps a bit of both. I don’t have all the answers, but I will share my data and offer some advice.

    My Data

    My job search visualized

    I submitted 90 job applications over eight months.

    • 5 Director of Engineering
      • 1 interview (via referral) – 20% interview rate
      • 3 ghosted – 60% ghost rate
      • 0 pending
    • 25 Senior Engineering Manager
      • 3 interviews (1 via recruiter, 1 via referral) – 12% interview rate
      • 3 ghosted – 12% ghost rate
      • 2 pending
    • 37 Engineering Manager
      • 9 interviews (1 via recruiter, 3 via referrals) – 24% interview rate
      • 7 ghosted – 19% ghost rate
      • 8 pending
    • 2 Software Architect
      • 1 interview – 50%
      • 2 ghosted – 100% ghost rate
      • 0 pending
    • 11 Staff/Principal/Founding Engineer
      • 0 interviews – 0% interview rate
      • 5 ghosted – 45% ghost rate
      • 5 pending
    • 7 Senior Engineer
      • 0 interviews – 0% interview rate
      • 0 ghosted – 0% ghost rate
      • 3 pending
    • 3 Engineer
      • 0 interviews – 0% interview rate
      • 0 ghosted – 0% ghost rate
      • 1 pending

    (A note on the numbers above–I still have 19 applications that have received no response yet, but I haven’t moved to ghosted yet, so those ghost rates may still go up!)

    In total, I landed 14 interviews from these 90 applications–a 16% conversion rate.

    It definitely helped to have a referral, although the job I ended up getting came from outreach from a recruiter. One other promising opportunity which I withdrew from (after receiving the offer I accepted) also came from a recruiter. The difference between these opportunities and all the others were that the recruiters were engaged, transparent, communicative, responsive, and reliable.

    One of the opportunities I was pretty excited about, but the recruiter took weeks to get back to me after completing a final round of interviews. They repeatedly promised dates by which they’d have news, and when those dates passed without communication I would follow up after several days and get put off another week. It was very frustrating and eventually led to a rejection when I let them know I had another offer.

    A few opportunities had a significant “homework” aspect–a presentation to create and present, or a take-home coding project. I probably spent too much time on these projects–I never got to a final round of interviews for any of them.

    One that stung was an Engineering Manager role at a Seattle startup whose mission I was really excited about. They wanted a very hands-on manager and had me do a coding test, which I bombed–not because I’m a lousy engineer, but because I’m not a seasoned React engineer–I still look things up and rely on examples. It also didn’t help that I was told the coding would be focused on Typescript–which I am much stronger at.

    I was rejected out of hand by a recruiter for one role that I was referred for by a former employee. It seems they were looking for someone with 8 years of hands-on React engineering experience. I almost wrote a blog post about this one. React 8 years ago looks nothing like React today! Any talented engineer can pick up a new technology. Setting arbitrary requirements on experience means you’re going to miss out on smart, motivated, experienced talent. Their loss!

    My New Job

    The role I ended up accepting is a Senior Engineering Manager role–which was my prior title at Sonos. The comp ended up being pretty close too. One of the huge bonuses is that the role is 100% remote. I won’t waste several hours of my time each week commuting to an office. I’ve demonstrated the ability to successfully lead distributed and remote software teams and am excited I get to continue to do so. (Here’s me thumbing my nose at all the “return to office” deadenders who argue this is the only way to go.)

    The astonishing thing about this job is that the recruiter found me and reached out. Their posting had escaped my job search. I’m still curious to know why they reached out to me among a sea of candidates. I have no illusions about being well known, but I like to think I have a reputation among those who know me as a manager who does right by his employees (I always had above-average engagement scores from my teams at Sonos). When I’m on-site for orientation I hope to ask the recruiter about why I stood out.

    Apply Early and Often

    I was more likely to get traction on an application if I applied within a few days of the role being posted. Recruiters are overwhelmed by bot applications and genuine candidates are getting lost in the system. When searching LinkedIn make sure you look for posts within the past week (at most). Create job searches for roles posted in the past 24 hours and set alerts–when a new role of interest drops prioritize it, don’t wait!

    (Sorry I wish I had kept more data on the age of job postings that I applied to!)

    Focus on quality over quantity. You might want to have a few slightly different resumes–especially for a manager or senior engineer who is capable of leading in more than one specialization. Re-read and tweak your resumes–you may figure out some ways to improve them over time. Over the months I evolved several versions of my resume: mobile engineering leader, full-stack engineering leader, and staff engineer/architect in mobile.

    I made sure to craft a personal cover letter for each application. Over time I evolved this process as well, so that I had a standard template for a manager or staff engineer role–a couple of concise paragraphs that tell a story about my technical and leadership expertise. Then I’d write a custom intro paragraph that had some sort of hook that connects me to the company and the specific role. I might tweak the other standard paragraphs if there was a particular aspect of my experience worth emphasizing.

    I aimed for 2-4 quality applications per week. If I couldn’t see myself connecting to the role in some way and write an intro paragraph for a cover letter, then I simply passed on it. There are certain toxic companies (including several of the FAANG) that I simply avoided–personal preference as well as disrespectful past interview experiences. Perhaps this also reflects upon my over 50 attitude–I’ve done jobs for a paycheck before and at this point in my life finding a meaningful opportunity is of critical importance to me.

    Keep the applications going, even when you’re interviewing. You want to keep your pipeline full, even if you made it through the final round for your dream job. They might pick someone else, and when you need a paycheck you can’t afford a lull in the job search process.

    Referrals Are Key

    Work your network. Reach out to former colleagues, friends, and family and get those referrals in. It helps! I had the best luck getting an interview via connections that I knew well. Those 2nd degree connections, not so much. Be sure to connect with people you’ve worked with, and don’t just slide into their DMs with “hey remember me from 10 years ago when we occasionally were in the same meeting? Could you refer me please?” Put in some effort, re-establish the connection, find out how they’re doing–ask about the company and if they have any insight. Build genuine connections and referrals often follow naturally.

    Sometimes the job posting on LinkedIn has a recruiter or hiring manager you can reach out to. I tried this a few times and never got a response, nor an interview. They’re probably inundated with requests. It probably doesn’t hurt your chances, but don’t toss some clearly AI-generated message their way, or a form letter with misspellings. I think the thing here is to come across as a real human, with some sort of connection to the role that will make them want to bother fishing your application out of the thousands in their system and give it a look.

    Job Searching Over 50

    I’m afraid I don’t have any data here, just anecdotes from LinkedIn (I sure see a lot of people talking about ageism), and my own experience. My best advice is:

    • Remove work experience older than 20 years from your resume. Chances are it’s not relevant to what you’re doing today and it’s taking up valuable real estate.
    • It’s ok to leave the graduation date off your education.
    • Actively learn new technologies and practice your coding skills. It’ll help with your interview conversations and look good on your GitHub profile.

    Keep Your Skills Fresh and Relevant

    One of the things that kept me going was working on personal projects–many of which I made public. I have no idea whether this factored into getting hired or not, but if a recruiter or hiring manager bothered to look at my GitHub profile they would see that I am writing code and learning. Plus if anyone wanted to drill in to my projects they’d see well-organized code with tests and automation. This regular practice will also help in interview conversations and technical screenings.

    Expect to be Ghosted

    Kudos to the recruiters who took the time to reach out with a personal message. I know you’re swamped! When I get a personal response, that is a company I will want to re-apply to someday. It’s nice even to get the automated rejections so I can cross one off my list. Applications that linger in limbo with no response are frustrating, but the reality is that many of one’s applications will never get an acknowledgement beyond the initial automated “thanks for your application” email. If it has been more than 4 weeks with no contact I move an application to the “ghosted” pile and move on.

    Keep Your Chin Up

    This process is demoralizing, frustrating, and filled with disappointment.

    • That role you thought you were perfect for and got an automated rejection…
    • The interview loop you thought you nailed but they’re moving forward with other candidates…
    • The recruiter you had a promising conversation with and never heard from again…

    I see a lot of people posting a lot of negativity on LinkedIn about how broken the hiring process is, how frustrated they are, how unfair it all is. I see the recruiters who are frustrated and overwhelmed too. The thing is, I don’t think posting negativity is going to help you in the long run. I do enjoy reading some of the more creative and humorous posts about how rough the job search is, and I hope it works out for them!

    If you’re an engineer my advice is to keep busy, show off what you’re building, put a positive spin on your public posts, and find some friends and family with whom you can commiserate with privately.

    This is all my own data, personal experiences, observations, and advice. I hope others find it helpful. Your mileage may vary.


    About the Author

    Nicholas Hart is a software engineer and technical writer passionate about sharing knowledge and helping others learn. You can find more of my work at:

  • 5 Ways AI Helped Me Handle My Mother’s Passing

    5 Ways AI Helped Me Handle My Mother’s Passing

    AI and End of Life

    This article is not about Skynet and AI ending all life on Earth. 😂

    I recently lost my mother. And my job. It’s been a stressful and difficult time, and something I had never really prepared for. I had lots of questions and tasks: managing her estate, dealing with her taxes, dealing with my taxes, organizing her contacts, planning a celebration of life, preparing to livestream the celebration, and even figuring out what I wanted to say for a eulogy.

    As an AI enthusiast I instinctively turned to AI to help me navigate these many activities and challenges. I found AI to be an invaluable tool. I’m going to detail how I have been using it over the past few months to assist with end of life tasks.

    Data Mining for Contacts 🗃️

    As I began planning a celebration of life I wanted to make sure I invited all of my mother’s friends and connections. She wasn’t very organized about her contacts and addressbook—some were in her phone, some were in an email account she shared with my late father, and others were in her gmail account. Still more were scribbled on various notes throughout her office 🤦‍♂️.

    She corresponded with many people who weren’t recorded in her contacts/addressbook, so I knew I needed to scan her emails to find email addresses of personal contacts. I exported and downloaded all of her emails from both accounts, and exported her iPhone contacts. Her MBOX files were gigabytes of data so I knew I couldn’t just upload them to ChatGPT and expect AI to data mine it for me.

    I’ve been a Python developer since before the turn of the century, and it’s one of my favorite tools for processing and transforming data. MBOX files and email headers aren’t that complicated to parse, but I wanted to experiment with AI and see if it could speed up my development process.

    I asked ChatGPT for its help to write a Python script to process the MBOX files, look for email addresses and store them in a SQLite DB. I also wanted to record some contextual metadata with each occurrence of an email address. Was it from a sender or to a recipient? Were there telltale signs of a listserv in the email headers? How many interactions were there with each email address? I chose SQLite because it’s simple and fast for querying the data (and I wasn’t yet sure what I wanted to query).

    I then made a second script to process the SQLite DB and filter for email addresses that matched certain criteria. The script was able to parse a separate list of contacts from an addressbook CSV file, cross reference any email address with it and fill in the person’s name if it wasn’t parsed from the email. And then it output a new CSV with each contact, their first and last name, how many occurrences were found, and whether the address was categorized as personal or listserv. The script also had some filtering parameters to limit the output to only personal addresses, or require a minimum number of occurrences.

    Along the way I found discrepancies and anomalies in the output. I worked with ChatGPT to refine the scripts, for instance when I discovered a pattern of email addresses that were re-sent through yahoogroups.com (eg: someone%40comcast.net@yahoogroups.com).

    Eventually I arrived at a tool that worked pretty well for my needs. It was able to sort through gigabytes of data and arrive at a list of about 160 contacts which appeared to be real people with whom my mom had interacted with online over the past 25 years. This list became the basis for the invitations I would later send out for her celebration of life.

    I’ve published my ContactsScraper on GitHub in case anyone else may find it useful.

    Financial Planning 💸

    DISCLAIMER: Talk to your attorney and accountant/tax preparer. Do not rely on AI to make any legal or financial decisions.

    I inherited a small IRA from my mother, so had lots of questions about what to do here. What is a required minimum distribution? How much is it? What would this do to my taxes? How much debt could I afford to pay off without bumping myself into another tax bracket? Can I afford a new roof for my house? ChatGPT helped me answer a bunch of these questions and model several different scenarios. Then I called my accountant and discussed my plans with her and she confirmed what I had modeled.

    I provided as much specific information as I could about my finances and my mother’s IRA to ChatGPT. I’m not going to post any of that information here or any of the results, for obvious reasons. However, I found this to be a valuable process.

    As I iterated on the financial models new questions and considerations came to mind. How much interest am I paying on this chunk of credit card debt? How much in additional taxes will I pay by taking a larger IRA distribution, and how does that compare to the interest saved? What if I underpay my taxes? Below are some examples of prompts that I used to figure out how best to use this modest windfall.

    Prompt 1: Basic IRA Withdrawal vs. Credit Card Debt Tradeoff 💬

    “I have an inherited IRA worth $100,000 and $50,000 in credit card debt at 19% interest. I’m considering taking a distribution from the IRA to pay off the debt. What are the tax consequences of taking out $50,000 in a single year? Should I spread the withdrawals over multiple years to reduce the tax impact?”

    Prompt 2: Modeling Partial Withdrawal Strategy 💬

    “Assume I’m in the 22% federal tax bracket. If I take $25,000 from my inherited IRA this year and another $25,000 next year, how does that compare (in terms of taxes and interest saved) to taking the full $50,000 this year to eliminate my high-interest debt immediately?”

    Prompt 3: Safe Harbor and Withholding Adjustments 💬

    “If I take a $40,000 distribution from my inherited IRA and don’t adjust my withholding, could I owe an underpayment penalty? What’s the safe harbor threshold for avoiding a penalty, and how might I adjust my estimated tax payments to stay in the clear?”

    This sort of financial modeling is something I usually try to do myself with spreadsheets. Depending on the complexity and my familiarity with the topic it might require an hour of research before I even start writing the spreadsheet. Then as I enter data and model the answer I’ll spend hours more tweaking the spreadsheet columns, cell formatting, formulas, and trying to build a model that would help me visualize and understand different financial scenarios.

    In less than half the time it would have taken me to build a bunch of custom spreadsheets by hand ChatGPT helped me by generating charts and graphs, as well as asking clarifying questions that helped me provide better input. ChatGPT was like a financial planner that helped me get hands on with exploring various options.

    Creative Support ✍️

    “A eugoogalizor, one who speaks at funerals. Or did you think I’d be too stupid to know what a eugoogoly was?” – Derek Zoolander

    I’ve never written a eulogy before. I spoke at my dad’s funeral but aside from an anecdote I had thought of the day before it was largely spontaneous and I didn’t write it down. I wanted to plan a more comprehensive and heartfelt eulogy for my mother’s celebration of life.

    Let me be clear: I did not use generative AI to write my mom’s eulogy. I did use it to give some broad examples of how to approach it, and what elements to incorporate. It helped me establish an outline and plan to fill 5-10 minutes of time. At a high level:

    • Welcome & Thanks
      • acknowledge out of town family and those who couldn’t be here
      • special thanks to volunteers and key providers of support
    • A Difficult Year
      • talk about some of the struggles she’d been fighting through
      • acknowledge her grace and cheerful disposition through it all
    • Her Favorite Things
      • talk about some of the decor and memorabilia and how it relates to her
      • walk through the themes and give an anecdote or two–aim for some levity
    • Who She Was to Others
      • mention her career and impact
      • mention her volunteer work
    • Personal Reflection
      • talk about what she did for our family
      • the values I learned from her
      • how I will remember her
    • Closing
      • toast to her memory
      • invite others to speak

    It’s very personal so I won’t share exactly what I wrote, but the above outline really helped me focus my thoughts. It gave my speech a good cadence/flow, and helped me cover many of the essential memories and stories about her that I wanted to share.

    One thing I will share is my mom’s love of the Mona Lisa. She collected all sorts of artwork and knicknacks featuring that famous smile. I was planning a livestream of the celebration of life and knew I wanted to feature the Mona Lisa. I used Dall-E to generate a version of the Mona Lisa aiming a DSLR camera at the viewer, upscaled it to a large size and then added a speech bubble and disclaimer text, as you can see below.

    I then had this blown up into a 24” x 36” mounted poster and propped it up next to the livestream station, which I will elaborate on in the next section.

    Livestream Planning 📹

    I knew many of my mother’s family wouldn’t be able to travel and join us in person at the celebration of life, so I decided to do a livestream and recording of the event. I had never done a livestream before and figured I’d need some near-professional equipment in order to do it right. My kids are interested in becoming YouTubers, so I figured I could invest in some quality equipment for this event and work with them later on their own video streaming content.

    Naturally I turned to ChatGPT to help me plan the livestream.

    I could probably write an entire article about the hardware, software, various accessories, setup, and event planning. I probably will someday, perhaps the next time I use this equipment to livestream an event. This event was a success and the final edited video of the event was greatly appreciated by many people.

    I started by setting a clear goal for ChatGPT: create a professional, reliable livestream setup for your mother’s celebration of life that would both honor her memory and make the event accessible to remote guests. I wanted to not only broadcast and record the eulogies, but also set up a “greeting station” where guests could see a preview of themselves on an iPad and leave a message, story, or greeting for remote guests.

    I gave ChatGPT a list of hardware I already had (like my MacBook Pro and iPad Pro), but asked for assistance choosing a good camera, indoor lighting options, microphone(s), tripod, video encoder, and other equipment. For each item ChatGPT usually offered a few different options and recommendations depending on budget and needs.

    I definitely spent a few hours researching many of the options (particularly the big ticket items like the camera), but eventually settled on a list of semi-pro equipment that I felt would give me the best bang for my buck:

    On the software side of things ChatGPT recommended OBS, an open-source streaming/recording tool which was a breeze to set up and connect to YouTube. For post-production and editing the recorded footage into a polished video I used iMovie. It’s pretty basic, but is free with macOS. I think next time I do something like this I may invest in Final Cut Pro, but as I’m not a pro who does this for a living I think Adobe Premiere Pro is probably overkill.

    ChatGPT even offered to make a “day of” checklist for me to help me configure the whole end-to-end livestream setup. I didn’t bother with this but did ask a few troubleshooting questions (eg: about XLR to TRS microphone conversion) while setting up at the event.

    Overall the event was a wonderful gathering of people and sharing of memories and stories about my mother. I don’t know that many remote relatives tuned in to the livestream, but they definitely appreciated the edited recording I eventually created and shared.

    Post-Production Challenges 🎛️

    A few days later I sat down in front of my MacBook intending to do a little editing and create a version of the celebration of life which I would post to YouTube and share with family and friends. This is when I discovered the audio was terrible.

    I thought I had correctly connected to the in-house AV system using a jury-rigged XLR to TRS converter for the microphone. However it sounded like the only audio that was picked up was from the camera’s built in mic. It captured the sound from the house speakers–as well as any nearby chit-chat, laughter, or applause from guests.

    With a few suggestions from ChatGPT I was able to manually clean up the audio enough that the eulogizers were mostly intelligible:

    • Apply the “Enhance Audio” feature
    • Use the “Voice Enhance” filter
    • Reduce Background Noise (40% worked pretty well in my case)
    • Lower Gain or Volume on Peaks (manually select moments of applause or laughter and reduce the gain)

    I also came up with a shopping list of additional microphones and equipment (like a good XLR to TRS converter) so that next time I livestream an event I would be prepared.

    Final Thoughts

    What I found during this whole process was that AI can not only be a valuable resource for dealing with the variety of unexpected questions and issues that may come up when you have lost someone, but surprisingly I think it helped me cope with the grief.

    I spent a lot of time on my computer working on the tasks detailed in this article–and through it all AI appeared to lend a supportive and sympathetic ear. AI helped me stay focused on the tasks I needed to get done and create a wonderful memorial for my mother.

    What surprised me the most about AI’s capabilities was how natural it felt. It almost felt like a friend on the other side of a chat app who was there to help me figure out how to manage anything that came up–whether it was finances, tech, or how to write a eulogy. Other times AI was simply there to cheer me on and celebrate a small success.

    AI is being incorporated into everything, but I don’t think I’ve seen it used for end of life planning and services. It makes me wonder if there is an opportunity here for a startup.


    I’d love to hear how you have used AI to navigate end of life issues. Do you know of a startup that works in this space? I think this is an interesting and possibly untapped area for AI.

  • Long time no see…

    Long time no see…

    It’s been a while! Got laid off. Mom passed away. And the backdrop? World going to hell.

    My mom had been battling a variety of health issues this past year and at least I had the time to spend with her. Fortunately I had the support of my wife and her family.

    I will give Sonos credit for giving me the time to take her to appointments and be with her when she was in the hospital—but I’d have preferred FMLA to a layoff. (I still think they make great products, FWIW.)

    My wonderful wife and her sisters helped me clean out her co-op. It’s still not done but we made a ton of progress—and we had fun discovering some amazing memorabilia. I can’t wait to share some of it at her celebration of life—at the Paramount Theatre in Seattle! (The featured image is a pair of her boots I found).

    My mom volunteered at the Paramount for many years and I never knew what a community of friends she had built there, as well as at the Opera and Ballet. It’s really special that we’ll be able to remember her at such a gorgeous and historic site!

    For me the Paramount was where I saw my third live concert; my dad took me to see Weird Al Yankovic (don’t ask which tour because it will date me—as will the artists of my first two concerts).

    Anyhow, I’ve never felt like I had time to work on this cobwebsite, but now that I’m job hunting (and reluctant to give my content to LinkedIn gratis) I will try to post here semi-regularly.

  • Hello world!

    Hello world!

    A recent technical issue forced me to redo this website again. I don’t enjoy spending a lot of time working on this site. For now there’s not much to see—just some info about me and Zolite.