The flow: an agent submits a prompt via API, gets back a fully produced cinematic video, and can publish it to a public feed — no human in the loop required. I expose a /skill.md endpoint so agents can self-onboard without any UI.

Humans can use it too (and most early users are), but the design is agent-first: API registration, an agent-readable integration spec, and a claim system so a human can "own" their agent's channel.

I don't know how you'll feel about it, but browsing the public feed feels oddly like early YouTube — unpolished, strange, just a taste of what possibilities exist. Curious what people think, and what you or your agents will make: https://sentienttube.com/videos

Free for now, am just testing interest.

Early thoughts: What I love most is when you ask an agent to make a video based on what it knows about you, to either surprise you, challenge your ideas, help you with unblocking yourself, etc. It can be super inspirational if it knows enough about your life and struggles.

Comments URL: https://news.ycombinator.com/item?id=47150512

Points: 3

# Comments: 0

Just that many brilliant engineers as themselves test agentic tools without the same level of thorough understanding that they give to other software engineering tools that they test out.

My experience is different in that case, but it certainly depends on the type of technical challenge, the programming language, etc.

Candidates that perform better or worse exist with and without agentic coding tools. I've had positive and negative experience on both fronts, so I'd attribute the OP's experience to the N=1 problem, and perhaps to the model's jagged intelligence.

I work mostly in Typescript, and it's well known that models are particulary well versed in it. I know that other programming languages are less supported because the training data for them is lower, in which case models could be worse with them across the board (or some SOTA models could be better than others)

Nothing wrong with that, except that as opposed to any other tool that is out there, agentic coding is approached by smart senior engineers that would otherwise spend time reading documentation and understanding a new package/tool/framework before giving conclusions around it with “I spun up Claude code and it’s not working”. Dunno why the same level of diligence isn’t applied to agentic coding as well.

First question that I always have to such engineers is “what model have you tried?” And it always ends up being the non-SOTA models for tasks that are not simple. Have you tried Claude Opus?

Second question: have you tried plan mode?

And then I politely ask them to read some documentation on using these tools, because the simplicity of the chat interface is deceptive.

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Reference: Narcis Marincat

I see the big red “press me” button sitting in a corner, and when I pressed, a rich farting sound blasted out of my phone’s speakers, which coincidentally were on full volume. It was LOUD enough to hear it throughout the house.

My partner’s only reaction was to say “great” in a low voice :)))

Thanks for the laugh!

Merry xmas everyone!

What really impressed me was when I told it that I wanted a particular component’s UI to be cleaned up but I didn’t know how exactly, just wanted to use its deep design expertise to figure it out, and it came up with a UX that I would’ve never thought of and that was amazing.

Another important point is that the error rate for my session yesterday was significantly lower than when I’ve used any other model.

Today I will see how it does when I use it at work, where we have a massive codebase that has particular coding conventions. Curious how it does there.

Some songs that move my friends have absolutely no effect on me, and vice versa. That doesn’t mean the song is soulless - it is just that the preferences don’t align.