My latest life hack which I can recommend to anyone, at least in Germany: as part of my local library membership I get access to the PressReader app, which gives me access to the print edition of the economist! At 10 EUR a year it’s so affordable it nearly feels like it’s unethically so for what I get. I guess I’ll close with: May we forever be blessed with libraries, and may they never be „optimised away“ as an unnecessary social good.

And I totally agree with your thoughts on the criticality and inadequacy of AI replies in such a context! Lack of answers was holding a months worth of income hostage with no real recourse for us other than trying to be loud online. Kind of sad.

Looking at alternative merchant of records now to buy us some optionality.

Paddle, the merchant of record, used to have quite excellent support (widget in their dashboard) which then turned into workable support by e-mail. Now they have added a layer of AI automation whereby any support e-mail receives an automated AI reply to which you have to reply to escalate to a human. Unfortunately that loop is broken. I never get a human into the loop at all (they must be so surprised and happy that their support backlogs have gotten so short! Some PM is probably celebrating having made their system completely self-explanatory)

In our case they have misrouted our payouts, and I'd be very happy if I could manage to get hold of a human.

Do you know anyone working at Paddle I could escalate to, or an email different from sellers@paddle.com that one can use?

Thank you!

edit: language+grammar

Comments URL: https://news.ycombinator.com/item?id=49033604

Points: 7

# Comments: 5

How will conflict resolution be handled? Or is it a last-write-wins type setup? It would be amazing to have this build on top of automerge or something like that! It could compile to and use the automerge js libs in the browser, and deal with automerge through a NIF server side? Ok, not knowing your implementation and plans, I have to confess I am talking a bit out of my arse here...

Here on hackernews there seems to be very little other than AI related stories. Maybe not all too strange given the crowd who frequents this site. From what I gather the mostly positive sentiment isn't as widely shared among the general population (0: 50% of americans are more concerned than excited about the increase use of AI).

How do you think about whether or not to mention, or advertise, the AI capabilities of your own products when marketing to the general population? Do you advertise them heavily, sell them as a feature, or just let them add value and fade into the background as any other implementation detail?

I am very torn on this myself. We have recently added quite some AI features to our search products [1], namely ai generated answers, and using ai vision to classify images and the likes, and while these are features I am very proud of, I am rather hesitant to put them front and center in marketing, lest I alienate the more non-tech crowd that really is our core customer base.

Again: I'd love to hear how you think about, and approach, this in your own product marketing!

Lots of love from Berlin

0. https://www.pewresearch.org/science/2025/09/17/how-americans-view-ai-and-its-impact-on-people-and-society/ 1: https://monocle-search.com and https://searchcue.com

Comments URL: https://news.ycombinator.com/item?id=48992019

Points: 2

# Comments: 0

It's a product we built after building Monocle Search for Squarespace, so we got a real head-start on this one. It's typeahead search for pages and documents, married with ai answers and "conversational search" where those add value. We are pretty proud of what we have built over these last two years (while SearchCue and the WordPress plugin is new, the underlying search tech is something we have painstakingly built up over the two past years).

I'd really appreciate your thoughts and feedback and I am more than happy to answer any questions you might have!

edit: non-native speaker typo

Comments URL: https://news.ycombinator.com/item?id=48991779

Points: 2

# Comments: 0

Affiliate marketing _does_ work to an extent, and is a kind of rideable wave I suppose?

Do you have concrete examples?

Speaking of paid ads: we tried google, bing, LinkedIn in the past. Do you have a preferred place that you recommend that you have seen better performance at than other places?

We have excellent feedback from the users who do find us, so there is product market fit for the subset of customers that have a need for our product strong enough to actively search for it, but maybe that's an issue in and of itself: the fraction might be too small, and furthermore, for the (hopefully) larger segment of the user base that don't have a need strong enough to actively go looking, we need to be sufficiently visible for them to chance upon us...? which I guess drives home the message even more that visibility is key...

Thanks!

We (that is to say my business partner and I) are building SaaS products, but we are really struggling to find enough users. This is an age old problem, but I find it has gotten particular bad after LLMs made it trivially to make apps and services. Whether these products end up good or bad is mostly irrelevant, the end effect is the same: the market just seems so heavily saturated with new products, that it's incredibly hard to break through the constant drone of people vying for attention (the irony of me finding a way to do the same isn't lost on me).

Even briefly mentioning what we are building in a comment on a "what are you working on" thread yesterday, had my inbox filled with AI outreach from questionable SEO, "How to optimize your product", "let me create a garbage video for you" style e-mails.

My conclusion so far are:

  - e-mail outreach (and particularly cold outreach) really doesn't work, and I never found it quite ethical to start with
  - communities like LinkedIn are also heavily dominated by AI slop and people at corporates who are bored and looking to build an audience (maybe an unfair characterisation and maybe more a view into my feed than the state of the platform as a whole?)
  - indiehackers etc I have never gotten to work, but that might be a skills issue
  - "being present in forums etc where our users are" seems the best bet so far, but very hit and miss
  - we have had some very minor success with influencer marketing
  - paid search ads etc have resulted in lots of clicks but absolutely abhorrent conversions in our case, whereas conversions for the more organic channels like forums etc are excellent (maybe a targeting issue...)

Lots of love from Berlin

Comments URL: https://news.ycombinator.com/item?id=48918150

Points: 9

# Comments: 12

Longer version: Our usecase isn't entirely aligned with how Meilisearch is meant to be used, I think. For one, we have a very high number of indices (at the time of using Meilisearch we had multiple per site that uses our service) and we wanted to have these replicated to edge nodes we have placed around the globe to keep latency down. In the end I was ending up spending an inordinate amount of time wrangling Meilisearch to get indices up and running across our different edge nodes. And, I am not sure if it was a regression in the last Meilisearch version we used, or user error, but at some point some index creations would just never get done, and would hold up our entire indexing pipeline. So long story short: the amount of effort needed to orchestrate and keep all the individual Meilisearch nodes up to date and in sync just turned out to be too much hassle.

The system I built afterwards works vastly better because it's actually bespoke and tailored to our use case. I can create the search indices on our crawler nodes entirely in isolation, run all sorts of preprocessing and optimizations once, and then just ship the final search indices to all the nodes that then serve them, and as a result I need wastly less computational resources on those edge nodes too, since no actual indexing work ever needs to be done on them.

It also means (double edges sword of course, because Meilisearch already gives you so much functionality out of the box) that I had to re-implement a whole lot of stuff around relevance tuning, snippet generation, ranking, etc, but as a result I have also been able to build interesting functionality than we didn't get out of the box before. And lastly, since the search index is now served as part of our main search node application things also get really fast, as I have no latency whatsoever to speak of going from app to Meilisearch.

We are just launching a new site-search product. The TL;DR is: we crawl your site (pages, documents, images) and you can add our search to your site by adding a JavaScript embed.

We built this on a shared search stack that we have also used on another search product of ours (namely Monocle Search [1] which is aimed at Squarespace sites first and foremost), so the search is fairly solid and battletested.

We aren't yet 100% sold on the positioning of this product. I'd love feedback and thoughts on whether it speaks to you at all. The audience (at least as we have seen it from our other search product) seems to be everything from small sites of individuals to SMBs, i.e., quite a range.

Our aim is to be affordable, yet priced such that we can keep the lights on.

I'd love feedback of any sort, and if anyone is interested I'll happily expand on the tech behind our service too (in short: Elixir + Rust + Postgres + Tantivy + lots of various agentic loops for "conversational search" + nodes spread over the world, and a metric ton of tuning)

Comments URL: https://news.ycombinator.com/item?id=48892845

Points: 1

# Comments: 0

We used Meilisearch as the search backend in the beginning but have since replaced it with a quite sophisticated search stack built around Tantivy [2]. We now support crawling and indexing of pages, most common office documents and PDFs, run OCR and feature extraction of images you might have, offer typeahead search with the aim of giving you providing answers as fast as you can type, as well as more classic agentic/conversational ai search.

There have been quite a number of interesting optimization challenges to solve in case anyone is interested. We have search nodes distributed around the globe to provide the lowest possible latency regardless of where the end-user sits.

We are also working on some other smaller side projects, but they aren't quite ready to launch yet.

[0]: https://monocle-search.com

[1]: https://searchcue.com

[2]: https://github.com/quickwit-oss/tantivy

It also compresses the context at around 100k tokens.

In case anyone is interested: https://github.com/sebastian/pi-extensions/tree/main/.pi/ext...