I'm one of the most pro-AI support/solutions/FDE engineers you'll find, and I really don't see AI taking away support and hand holding.
Even though I use AI to answer questions large customers would still rather wait for a weekly meeting to ask a question or have someone fly onsite then write the same question in an email or to a chatbot and get a near instant answer
This is more of a VAD/turn detection issue. It's gotten a lot better over the last few years, but it's a hard problem. The extra ~100ms of latency makes a huge difference otherwise, especially when you have use cases that require tool calling that can easily add 500ms+ of latency.
I expected the same out come you're saying here, but in my experience this hasn't been the case. I've been researching new acoustic guitars to purchase, and I've been getting an equal amount of suggestions from the major brands and the small brands.
Part of it though is I'm giving lots of context (e.g. guitar player for 10+ years, huge Opeth fan, looking for something with as close to an Ibanez style neck as possible under $1000)
Had the pleasure of working with Alex while at System1. Great guy. If I remember correctly I got one tiny change merged into Waterfox that's probably since been undone in the years since :-).
@cootsnuck, if I didn't really love working with the people/company I'm at now, I'd also start my own consulting company.
Once I realized you really only need 3-5 consistent customers (well, you only REALLY NEED one customer), and you can generally keep customers and employees happy by responding quickly and doing what you say you'll do (aka not taking on work you can't handle) I'm confident I could branch out on my own if I ever wanted to.
It might be role-specific. I'm a solutions engineer. A large portion of my time is spent making demos for customers. LLMs have been a game-changer for me, because not only can I spit out _more_ demos, but I can handle more edge cases in demos that people run into. E.g. for example, someone wrote in asking how to use our REST API with Python.
I KNOW a common issue people run into is they forget to handle rate limits, but I also know more JavaScript than Python and have limited time, so before I'd
write:
```
# NOTE: Make sure to handle the rate limit! This is just an example. See example.com/docs/javascript/rate-limit-example for a js example doing this.
```
Unsurprisingly, more than half of customers would just ignore the comment, forget to handle the rate limit, and then write in a few months later. With Claude, I just write "Create a customer demo in Python that handles rate limits. Use example.com/docs/javascript/rate-limit-example as a reference," and it gets me 95% of the way there.
There are probably 100 other small examples like this where I had the "vibe" to know where the customer might trip over, but not the time to plug up all the little documentation example holes myself. Ideally, yes, hiring a full-time person to handle plugging up these holes would be great, but if you're resource constrained paying Anthropic for tokens is a much faster/cheaper solution in the short term.
1000%. When the sale doesn't go through, it's the salesperson's fault. When the product doesn't work, it's the "real" engineer's fault. When everything works, the client gives you a high five.
If you don't know the answer, you can ask one of the "real" engineers.
As long as you show up with a smile on your face and the demo kinda works during the call, you're 10/10.
At FAANG companies, you generally get paid at a level above your technical role; for example, if you have a mid-level engineer's coding ability but can also talk to customers, you'll generally be paid a senior engineer's salary.
Some days, I don't understand why everyone doesn't want this job. But then I'll talk to the product engineers on my team, and they'll thank me for talking to the customers so they can focus on coding. I think it's really a personality/preference thing.
This is one of the few hills I will die on. After working on a team that used Phabricator for a few years and going back to GitHub when I joined a new company, it really does make life so much nicer to just rebase -> squash -> commit a single PR to `main`
I agree with you for many use cases, but for the use case I'm focused on (Voice AI) speed is absolutely everything. Every millisecond counts for voice, and most voice use cases don't require anything close to "deep thinking. E.g., for inbound customer support use cases, we really just want the voice agent to be fast and follow the SOP.
Referrals are the key to non-FAANG jobs. I also have over 10 years of experience, with six of those years spent working under the same supervisor across two different jobs. Four of those years were two different jobs, thanks to strong referrals from my previous boss and the one I worked with for 6 years before that.
I fumbled a bit early in my career and burned some bridges, but luckily, I smartened up after the first 2ish years.
I figured if I have 10+ years of experience and do not have at least 5-10 people I can call up to ask for a job who've worked with me in the past, I've screwed up. Investing in relationships has been the key job security hack for me (also a completely average React dev who happens to know an above-average amount about video and webrtc).
Your logic works out fine if you don't mind a dash of risk (e.g. from a job loss). But when I ran the numbers from my perspective it didn't seem worth it. (I might be doing my math wrong).
Let's say I get a car that costs $30k, I put $10k down, and I take a loan out using the numbers above rounded up just for napkin math (1% APR, 4% savings account).
After one year:
```
$30,000 x 0.04 = $1,200 from savings account interest
$1,200 x 0.33 = $396 in TAXES from the interest (assuming you earn over $145k/year in California)
$30,000 x 0.01 = $300 in loan interest
Total earned = $1,200 - $396 - $300 = $696
```
Don't get me wrong, $696 isn't _nothing_ but I personally would rather have the feeling of not owing people money then an extra $696 at the end of the year. Add in depreciation from getting a new car and it's almost a wash.
I worked at the company that acquired MapQuest a few years ago. It's been bought and sold a few times, but their most popular feature is still the "print maps" button...
As you can guess it's mostly people over the age of 50 still using MapQuest lol
Unless I'm reading the wrong pricing page, Duolingo Max seems to cost $29.99/month. In my experience learning Chinese, it costs $15-20 an hour to find a decent teacher online with whom to practice via video call. A few teachers charge less than $10 an hour, but they are very weak. Seems pretty darn reasonable for me, especially since I'm guessing they have at least $10/month in costs just paying for the LLM.
Or just say hi by sending an email to hello at jameshush.com.
I spend 80% of my time in Taipei and 20% of my time in Spain. I'll always make time for coffee for HN people, so feel free to reach out.
https://hnbadges.netlify.app/?user=jameshush
https://jameshush.at.hn