hectormalot

Joined 14 years ago

Karma
1,234
Submissions
301
Member since
Dec 28
Building the best AI for phone-based customer service at Stellar (http://www.stellarcs.ai). I'm a self taught programmer (Ruby, Go, Python, TS, Rust) with a background leading teams across consulting and banking before Stellar.

[email protected]

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Recent submissions

Comment · 13 days ago
I have good experiences with both porkbun and INWX as well. INWX could indeed use a UX update.

I used to use TransIP.nl and while they are still good, they’ve gotten expensive over the last few years.

Comment · 2 months ago
Can I ask why you have this sentiment? I think the Euro has been a great achievement. It seems quite stable compared to its predecessor currencies and it’s convenient for trade across the union.
Comment · 3 months ago
I’m not sure it will go this direction. Using a generic (near) frontier model is often cheap enough that you need to talk really big volumes before it pays off to fine tune.

My example: we were doing single digit millions of automated call summaries a few years back at a major bank with GPT-4o. Smaller model gave more rejected summaries (compliance not happy), so we briefly looked at fine tuning a smaller model and basically concluded that even at that scale the effort of data collection, management, fine tuning, hosting the model, etc didn’t have a sufficient business case vs picking up other projects.

Comment · 3 months ago
Likely a lot of those tokens are cached. And because it’s an individual project it’s likely this is under a personal Claude Max 20x plan.
Comment · 5 months ago
Ah my mistake, I thought he was making a broader point that other providers always have deep subprocessor stacks.
Comment · 5 months ago
We have a vendor with almost no subprocessors because they run their own hardware in a colo.

It is refreshing actually. They can accurately answer questions on how everything works and there is no subsubsubprocessors to worry about.

Comment · 5 months ago
The thing that surprises me is they flew back to Newark for almost 90 minutes. It doesn't make sense to me.

(1) Either you believe the threat is credible and you put it down at the nearest suitable airport in the least amount of time. Say Sydney at about 200km to your west, or FSP at 150km in the direction you're going (not a great fit, but doable). In both cases you could probably land within 20 minutes, a bit more if you aim for Gander (Fun history for that airport, great as an emergency diversion).

(2) or, you believe the threat is not credible. At this point you might as well continue the flight. Flying 90 minutes back does not seem (to me) to meaningfully reduce the risk if someone is actually planning to trigger a bomb anyway.

Comment · 6 months ago
Thanks, appreciate the details. 99% is far above the amount I expected, and if it specifically hits hard to cache data then I can see how that brings a system to its knees.
Comment · 6 months ago
Thanks. I imagine there is a (a) a lot of interest in scraping source code, and (b) many requests to forges hitting expensive paths. 99% of volume though, wow, much more than expected.
Comment · 6 months ago
Maybe I’m naive about this, but I didn’t expect AI scrapers to be that big of a load? I mean, it’s not that they need to scrape the same at 1000+ QPS, and even then I wouldn’t expect them to download all media and images either?

What am I missing that explains the gap between this and “constant DDoS” of the site?

Comment · 6 months ago
Stellar | Amsterdam, the Netherlands | Onsite (2 days remote OK) | €70-100k + equity | https://stellarcs.ai

Hey, I'm one of Stellar's founders. We're building AI for large contact centers, our primary product is voice.

Contact centers are the last place where companies actually talk to their customers. We listen to calls every week and it's fascinating. AI here helps real people: shorter wait times, 24/7 support, lower cost. We’ve helped companies go from 60 to 98% pickup rate in weeks. We’ve had (human) agents asking us to accelerate our roll out plan because the days with Stellar are so much better than the days without.

We’re all builders. Everybody in our company still writes code. We have one role open:

We are looking for implementation leads that love working with clients. FDEs welcome as well.

This role is perfect if you:

* Want massive ownership at a small team

* Actually enjoy solving hard problems (real-time audio at enterprise scale)

* Think making AI sound human in niche dialects is a fun challenge

Find the full vacancies here: https://www.stellarcs.ai/careers

EU work authorization is required. No visa sponsorship available.

Apply: e-mail is in my profile, please indicate HN in your e-mail.

Comment · 7 months ago
Stellar | Amsterdam, the Netherlands | Onsite (2 days remote OK) | €70-100k + equity | https://stellarcs.ai

Hey, I'm one of Stellar's founders. We're building AI for large contact centers, our primary product is voice.

Everyone thinks contact centers are boring. They're wrong. It's the last place where companies actually talk to their customers. We listen to calls every week and it's fascinating. AI here helps real people: shorter wait times, 24/7 support, lower cost. We’ve helped companies go from 60 to 98% pickup rate in weeks.

We're bootstrapped, 10 FTE, cash-flow positive, and growing fast with household names in the Netherlands and Belgium. Doubling our volume every month for the last 4 months.

We’re all builders. Everybody in our company still writes code. We have 2 roles open:

1. We need product minded engineers who can jump between our Go and TS backends and React frontend.

2. We need implementation leads that love working with clients. FDEs welcome as well.

This role is perfect if you:

* Want massive ownership at a small team

* Actually enjoy solving hard problems (real-time audio at enterprise scale)

* Think making AI sound human in niche dialects is a fun challenge

Find the full vacancies here: https://www.stellarcs.ai/careers

EU work authorization is required. No visa sponsorship available.

Apply: e-mail is in my profile, please indicate HN in your e-mail.

Comment · 7 months ago
Comment · 7 months ago
There’s both a quality and quantity angle.

For some work, similar to the philosophy example of GP, LLMs can help with depth/quality. Is additive to your own thinking. -> quality approach

For other things. I take a quantity approach. Having 8 subagents research, implement, review, improve, review (etc) a feature in a non critical part of our code, or investigate a bug together with some traces. It’s displacing my own thinking, but that’s ok, it makes up for it with the speed and amount of work it can do. —> quantity approach.

It’s become mostly a matter of picking the right approach depending on the problem I’m trying to solve.

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