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Lispr has been free for everyone since launch. It now runs on two plans, and the way we split them says more about the product than the prices do.

The standard move with a free tier is to cut features. English only. Three languages instead of thirty. The formatting held back as the thing you pay for. The free version gets built to be annoying enough that you upgrade.

In this time when we use LLM's for basically anything, what AI agents/tools would you want that you would actually pay for?
What are you spending a lot of money on and would probably save a lot of you time if you got the Agent out of box, or if configuration was much easier?

One of the most effective and affordable marketing strategies is WOM (word of mouth) getting other people to share your product and potentially spark curiosity or create a domino effect.

Over the past few days, several people:

have shared screenshots of my tool on social media,
sent me DMs saying they like it, or
left reviews on the Chrome Web Store.
I plan to use them in:
the landing page
 marketing materials (Chrome Web Store)
 possibly advertisement and "show off on socials"

You rename packages/cli to apps/cli. The next scan tells you a dependency started running code at install, and another one stopped. Nothing started you moved a folder.

0.34.0 is four changes that are the same sentence from different angles: a security signal is only worth reading if it fires on what happened, not on what you did to your own repo. An axis that cries wolf is one you learn to skip, and then it's worth nothing on the day it's right.

The new Lingo.dev is here, and it is live for every organization.

Lingo.dev is completely redesigned around the way you work, so everything now has a clear place, across five areas:

• Home  your starting point: a quick read on recent activity.

• Infrastructure  where you build your localization engines: the models, glossaries, rulesets, and brand voices you configure once and reuse everywhere.

• Studio  where localization connects to the tools you already use: the GitHub App, a Zendesk Help Center, a Payload CMS, plus the CLI and the API.

• Queue  one inbox for everything that needs a person: human review, localization engine suggestions, and triage, in a single list you filter and save as views.

• Observability  where you see whether the output is good, even in languages you cannot read: reports, AI reviewers, and a log of every review beside the translation it scored.

This is the foundation for everything we build next, and the new home for your localization work.

Not another chatbot builder. Not another connect your API to an LLM tool.
I mean the boring, painful infrastructure that you don't want to build every time you ship an AI agent.

Things like:

• Agent orchestration

• RAG

• 900+ integrations

• Evaluations

• Observability & analytics

• LLMOps

• Payments & usage tracking

Basically:

@Mastra launched an open-source, configurable software factory last week. Ranked #1 Product of the Day and #1 Product of the Week, the community loved it.

To keep the conversation going, @bookercodes and @suhdudeitsabhi are hosting a workshop this Thursday, September 17, at 4 PM UTC / 9 AM PST.

Are you totally against sharing your personal data to companies? or are you neutral and think your info doesn't matter that much? Not just words from dictation apps, but other personal details like schedules from a productivity app, or computer details from coding agents. Asking this cause I personally don't mind my app data being sent to companies, as long as they're not passwords, or important personal info. But this brings us to another question, where is the line?

Update from launch week.

The publisher path no longer waits on a review. You create a key, drop the SDK, send a message. If the auction is empty you still get a house ad. Same day.

If you tried the SDK last Tuesday and saw nothing, try again.

I want the boring reports:

Road to 1,000,000 @Votap users - Day 90 | Current: 1470
Today is the first test day. We created 6 video ads and 4 static ads, intentionally making them very different. Colorful, minimal, funny, serious, product-focused, completely weird. Now each gets the exact same budget and a fair chance to compete.
The goal isn t to squeeze the most installs out of this first test. It s to look for signals. Which ads get watched? Which get clicked? Which lead to installs, registrations and actual Votap users?
With a smaller budget, you can t spend thousands testing every creative. But you can look for hints. From these 10, we ll take the top 3, put more serious money behind them and start A/B testing variations.
Want to see where they re sending everyone? Try Votap - download it from the App Store!
More tomorrow.

We keep talking about AI agent costs as: model price tokens requests

But agentic systems add another cost: uncontrolled execution.

• An agent retries a tool 5 times.

• Calls an expensive model when a cheaper one would work.

• Loops through unnecessary steps. Hits APIs it didn't need.

• Delegates work to another agent.

We re trying to expand our social media activity and be present on more platforms.

But honestly, preparing and posting the same content across different platforms eats a lot of time.

I want to keep our voice and our content, without spending hours manually editing and publishing everywhere.

So, makers and marketers:

Building feels straightforward.

You have a problem, you open your laptop, you build, break things, fix them, ship features, repeat.

We build agents all day, and the thing I keep noticing is that they almost never fail in the middle. They fail at the very last step, when something has to happen in the real world.
Ours kept dying in the same spot: a signup form that texts a six-digit code. Everything up to that point ran fine, and then it just sat there waiting for a human to go and read a text message.
I'm curious what everyone else's version of this is. Not the thing your agent does badly - the thing it does perfectly, right up until it has to stop and hand it back to you.
Verification codes? A booking that only happens by phone? A supplier who answers email once a week? Something that needs an actual human voice on the other end?
Mostly I want to know whether the wall sits in the same place for everyone, or whether it moves depending on what you're building.

I run a dozen or so Claude Code sessions at once, one per project, and the terminal ended up mattering more than I expected. Most of my attention goes to working out which session is waiting on me.

So I'm curious what everyone else runs their agents in. iTerm2, Ghostty, Warp, the one built into your editor, tmux?

And why that one? Was there a feature you actually needed, or were you already in it?

The Digital Omnibus pushed high-risk obligations out to December 2027. Article 50 transparency was not pushed anywhere - it applies now. And if your generative feature shipped before 2 August, your marking deadline is 2 December, twelve weeks out.

Every summary I read of the Digital Omnibus said some version of "Brussels blinks, AI Act delayed." That's accurate about the part of the Act most small teams will never touch, and misleading about the part most of us are already inside. I went and read the Commission's own pages this week rather than the coverage, and the gap between the two is wide enough to be worth twenty minutes of your time.

A user gives an agent a task. Maybe it needs to read invoices, update a CRM record, check an internal dashboard, or call a few APIs on their behalf. The easy model is to let the agent act with whatever access the user already has.

But I am not sure that makes sense once the user has a lot of authority. If I can delete a workspace, change billing, export customer data, or invite an admin, does an agent helping me with one task need access to all of that too Giving the agent its own identity and narrower permissions sounds safer. But then another question comes up: how narrow can those permissions be before the agent keeps hitting boundaries halfway through the task?

So I am curious how teams building agents are thinking about this today.

Does the agent inherit the user s authority? Does it get its own identity with access only to specific APIs or actions? Or are you handling this another way? And where do you draw the line between the user is allowed to do this and the agent is allowed to do this for the user ?

Road to 1,000,000 Votap users - Day 80 | Current: 1467
50% of people who click through to our App Store page install the app.
70% complete registration, including phone verification and profile setup
23% of installs started the trial.
1 in 7 trials has converted to paid so far.
The data isn t perfect yet. AppsFlyer is delayed in places, hence somehow having more first voters than registrations, and the sample is still small.
Here s what excites me: we haven t optimized or A/B tested ANYTHING yet. This is the baseline. Now we start breaking the funnel apart and seeing how far we can push it.

Indie hackers don't really have one "home" on the internet.

Some communities are built around founder stories and advice. Others are better for blunt feedback, technical discussions, audience building, accountability, or meeting other founders.

That matters because the best community for you depends on what you're actually trying to get from it.

Whenever I launched something in the past, hardly anyone knew about it. Looking back, it was mostly because I was afraid to talk about what I was building.

Fortunately, I've grown out of that. These days I talk about my product much more (maybe even more than I should ), and it's made a huge difference in getting it noticed.

I wanted to share a few things that worked surprisingly well for my Chrome extension (a LinkedIn activity tracker that alerts you before you hit LinkedIn's limits and trigger account restrictions).

In professional communication which feels more pressing for you - to be understood or to understand the other?

We initially built WIT more around the first situation - when we are anxious about sending an important message across the world, and WIT helps finding possible mismatches in meaning across American, Indian and Singapore English.

there's no changelog for PopTask anywhere, the app store "what's new" box is read by roughly nobody, so from now on every update lands in this thread, small ones as replies, bigger ones as their own post

what's shipped since july:

In the first half of 2026, 3,869 products shipped on Product Hunt. We ran the whole stream through LinkedIn and Crunchbase to see what people launch, who the founders are, where they came from and what actually improves your odds.

Part 1. The landscape: the AI wave and the dilution of attention

i try a lot of AI products and my honest hit rate is low. most of what i install is gone inside a week, and usually not because it was bad. it just never turned into a habit.

the few that stuck have almost nothing in common on paper. the only thread i can find is that they took away a step i was already doing, instead of adding a step i probably should be doing. the ones that asked me to build a new routine all died.

SEO was about being found on Google.

Now AI is becoming the new discovery layer.

For those thinking about GEO...

What s the biggest change you ve made so far?