Hey everyone, Elitza here, founder of own.page

A few days ago, own.page reached #2 Product of the Day on Product Hunt.

As a solo founder competing against products backed by much larger teams, this wasn't something I expected - but it was something I was determined to achieve. There were moments during the launch when I thought it would be incredibly difficult.

But this incredible community showed up.

That's a lot of AGI, with some substantial firepower:

Anthropic has raised $65 billion in Series H funding led by Altimeter Capital, Dragoneer, Greenoaks, and Sequoia Capital, valuing the company at $965 billion post-money.

From Coatue, who lead the round:

...what s changed since three months ago (the last round was only three months ago, believe it or not)?

Three things:

1. We ve seen the shift from co-pilots that help make us more efficient to agents actually doing long-form work tasks on our behalf. This has meant an explosion in both productivity and ROI for customers.

2. Anthropic introduced Mythos Preview, a whole new model class that demonstrates a step change in intelligence level as seen in the METR chart below. It not only shows dramatic improvement to coding and long-running agents, it is also defining a new frontier for security.

3. And finally > use cases spreading from coding to everything else.

1. I've always been on the personal brand side. More and more founders are building it now (sometimes even before the product is ready while it's still in development, before seed fundraising). The CEO builds their position so the product sells more easily at the official launch.

2. But I have experience with people who built the product, scaled it, and only then did we discover who was behind it.

Honestly, with the first approach, I'd be concerned that people invest more in me as a person than in the product. People would idealise the founder and overlook the product's flaws (which could hurt development and constructive feedback).

+ I noticed the most common mistake that many people who started building a personal brand first, connected their product to their personal accounts (emails, social media, etc.) and started having a problem selling these things, because they cannot "give someone keys" to their personal profiles.

We teamed up with Vercel and we want you shipping this Friday.
May 15 is Vercel Day. Launch your product on Product Hunt that day with the Vercel Day tag and you're on the official Vercel Day leaderboard alongside every other builder going live that day. Top launches win prizes and get serious visibility from a crowd that's already paying attention.
This is the move if you've been waiting for a reason to launch. You've got four days.
What are you building? Drop it below

Major Update

This update introduces a wide range of new effects, major workflow upgrades, and important macOS performance fixes. We focused on making DASCA more powerful and consistent across panels, effect controls, and 3D tools, while also improving export reliability and interaction quality for everyday use.

New Features

Thank you to everyone using the app. We ve received some feedback from our users and have made updates accordingly. These will be released in the App Stores shortly. Issues Resolved:

* In some cases, the system was unable to detect the language.

* In certain usage scenarios, the SSH connection would disconnect.

* Colours were not always displayed correctly.

A lot of people try to raise funding before they even begin.

And then sometimes I read those zero to hero stories. (Maybe they re a bit "polished" by the media to have publicity.)

In any case, building products has become much easier from a technical perspective, which also makes it cheaper especially for software startups.

There are founders you d love to NOT work for. And then there are founders whose company you wouldn t want to leave, no matter what.

A big part of that comes down to people, their values, and their character.

And often, that starts with the founder.

Hey everyone

Just shipped Netfox 0.3.3. No new features this round a focused polish pass on accuracy, privacy, and reliability based on real usage. What's better:

On a Tuesday, the first enterprise question is usually not can you capture AI code? It s who can see the records, how long do they live, and what happens when a policy blocks a change?

That s the part LineageLens is built for. Base gives you local capture. Lite gives a shared team record. Plus and Max move the data into a backend where auth, permissions, retention, and policy live next to the provenance records instead of around them.

The useful thing here is not another dashboard. It s a self-hosted record of prompt, model, tool, file, and outcome that engineering, security, and platform teams can actually govern on their own infrastructure.

I keep seeing AI governance tools start with visibility, then discover that the real enterprise questions are identity, retention, and review. If the record cannot be scoped, retained, and exported on your side, it is not really governable.

2 significant things are circulating on the internet simultaneously this week:

• A tweet about how a human beat a machine (a 10-hour livestream in which a human sorted packages and compared it to the productivity of a robot).

• Or an announcement of a Microsoft AI chief that predicts AI will automate most white-collar work within 18 months.

While I don't think there will be a complete replacement of humans in either case, I do think we will see mass layoffs. My guess is that it will be white-collar jobs first.

I was reading this recent @OpenAI article about Gartner naming OpenAI a Leader in enterprise AI coding agents: https://openai.com/index/gartner....

"Software development is becoming more agentic." This is a good summary of what is happening right now. We are moving from AI that helps you write faster, to AI that can take over tasks (actions, use tools, make changes, run tests, and bring the work back for human review). That is a very different behavior.
The article gives Cisco as an example. They used Codex for a big part of their AI Defense platform and reduced delivery time from several quarters to a few weeks.

AI is incredibly good, I d even say almost perfect.

And for many people, that uniformity of perfect templates is starting to feel annoying.

One thing that surfaced while tightening LineageLens this week: capture is not the hard part. Agreement is.

If the extension, backend, and MCP server describe the same AI edit with slightly different field names or status values, you do not have provenance, you have three believable stories about the same event. That matters because reviewers and assistants start trusting whichever surface they looked at last.

The question I keep coming back to is simple: if a record can look applied in one place and accepted in another, is that still a single source of truth?

We thought we were ready.

Bigger deals. Fewer customers. Better margins. That was the dream.

So we built enterprise features. SSO. Advanced permissions. Audit logs. A whole new pricing tier starting at $2,000/month.

We spent 6 months. Three engineers. One dedicated product manager. Endless meetings about "enterprise readiness."

For months, we celebrated our power users at Murror the ones journaling every day, sometimes multiple times a day. They had the highest session times, the most entries, the best retention curves. On paper, they were our success story.

Then we started reading what they were actually writing.

Wild to say but Brew took the #1 spot just from word of mouth!

If you have not tried it yet, it is free: https://brew.new.

There seems to have two types of developers:

• Human in the loop: Those who like to control the behavior of their agents as it works, looking at the context usage, reading reasoning blocks, and approving individual file edits.

• Agent first: Those who prefer to review the output of agents, rather than individual actions, and run one or more sessions in parallel.

What type of developer are you when working with AI coding agents?

We built LineageLens because teams were wasting reviewer time guessing where unfamiliar code came from. Archival logs are useful for audits, but reviewers need provenance in the flow of review: a prompt, a model, and a confidence score attached to the diff. Recent product work focused on small, high-leverage UX and correlation improvements drag/drop captures, click-to-insert in vscode extension so provenance is readable and actionable in minutes, not days. I'm curious: in your org, how do reviewers triage unfamiliar code today reproduce prompts, ask the committer, or revert and re-implement? What one capability would make provenance useful for your reviewers tomorrow?

I've been working with LineageLens and just added a custom agent adapter so our internal CLI tool is attributed with prompts, model metadata, and confidence evidence. The registry design makes this surprisingly low-friction: implement a detect(input) that returns a NormalizedAgentContext (tool name, model, session ids, confidence, and evidence), register the adapter, then run the quickstart proxy to validate captures.

Why this matters: your team can capture private or bespoke tools without sending data to a vendor, and you get prompt code linkage in PR reviews and dashboards. I followed the recent repo changes (custom agents landed in late May) and found the adapter API predictable: detection should be conservative, emit evidence items, and choose appropriate ordering so your specialist adapter wins over the fallback.

If you ve extended LineageLens for an internal tool, what heuristics did you use to build confidence and avoid false positives?

I will go first.

"Do you do backlinks?"

Every week. Sometimes every day. From prospects. From agencies. From people who read one SEO blog post from 2018.

Backlinks are not the problem. Backlinks are a solution to a problem that has changed.

AI has undoubtedly made our work easier and faster.

An article that would have taken me several days before (defining the topic, doing research, interviewing experts for unique insights, validating data, and writing the final piece) can now be turned into a solid article in under two hours. (in my case, when I publish a weekly newsletter)

I'll go first,
During the launch of @Bitgrain , I thought maybe some 10 20 people might upvote or it can be even lesser, Surprisingly it got featured and the numbers went up crazy! I got mails from people who loved the product. It was unexpected but loved it!
btw do see @Bitgrain : )

Yesterday s discussion about who is more likely to be replaced (white-collar vs. blue-collar workers) raised another question for me.

So I m asking:

What do we need to do to keep our jobs in the age of AI and robotisation?

Excited that we made the #3 spot via just word of mouth, no paid marketing. If you have any questions after trying https://zero.xyz (it's free! tell your agent to install the CLI!) with the $5 welcome gift, ask 'em here!