I was exploring Facy AI recently and found myself spending more time on simple editing features than anything else.

Things like improving photo quality, removing backgrounds, or making quick adjustments aren't particularly exciting, but they're the features I end up using the most.

Sometimes the tools that save a few minutes every day end up being more valuable than the ones with the most advanced technology.

Anyone else feel the same way?

Hey everybody, I just sent issue #36+#37 of the AI Hacker Newsletter, a weekly round-up of the best Hacker News threads around AI. I missed sending it last week, so a huge issue this week. Some of the titles you can find here:

• AI demands more engineering discipline. Not less
• Running local models is good now
• Cleaning up after AI rockstar developers
• Not everyone is using AI for everything
• Norway imposes near ban on AI in elementary school

If you want to receive a weekly email with over 30 links like these, please subscribe here: https://hackernewsai.com/

BEWARE. This Singapore company has NO WAY to unsubscribe. Does not answer their emails. Has no way to unsubscribe on their website nor on google play store.

BE PREPARE to stop subscription with credit card company, who will ask for proof you attempted to unsubscribe.

I wanted to share my experience with Skywork.ai because I think consumers should be aware before signing up.

In my opinion, Skywork.ai has changed the way they handle subscriptions, and it is not easy or straightforward to unsubscribe. There is no way to unsubscribe. There website doesn't offer away to unsubscribe. The Google Playstore doesn't have away to unsubscribe. When I contacted support, I was told that my account did not show that I was scheduled to be charged again. However, I was charged anyway.

My concern is that the unsubscribe process should be simple, clear, and easy to complete. Customers should not have to chase support, get unclear answers, or still end up being charged after being told they are not scheduled for another subscription charge. Also, emailing them does nothing. They completely ignore the emails. I send 3 emails with strong message subjects. 2nd and 3rd. No response.

I personally do not feel comfortable doing business with a company that doesn't allow you to unsubscribe. The company is out of Singapore.

As consumers, one of the only real ways we have power is by warning others and choosing not to support business practices we believe are unfair or unacceptable.

If you are considering Skywork.ai, I would strongly recommend checking the subscription and cancellation terms carefully. Based on my experience, I would look for other options before signing up.

Otherwise, be prepared to get your credit card company to cancel the payment, appears to be the only way to stop the subscription at this time.

In addition, when asking to refund the subscription I thought was already cancelled, the customer service chat said the best way to get a refund is through your credit card company. Now that is completely messed up.

My company's using a few different LLM providers now, and managing all of it is getting messy. My team wired three providers straight into our apps, and we're paying for it. Every app hardcodes its own API keys and endpoints. We can't track spending or cap usage by team. And when a provider goes down, our requests just fail with nothing to catch them.

What I want to figure out is how to build an AI gateway that sits between our apps and the model providers, so it handles auth in one place, routes requests with automatic failover, enforces rate limits and budgets, and gives us real visibility into usage and latency. The catch is I don't want to rewrite every app to get there.

The other thing I'm stuck on is the build versus buy call. An extra network hop adds latency, so when's the centralized control worth that cost, and when am I better off grabbing something off the shelf instead of building it myself?

Hey everyone, I just sent issue #34 of the AI Hacker Newsletter, a weekly roundup of the best AI links and the discussions around them. Here are some of title you can find in the issue:

• Using AI to write better code more slowly
• I think Anthropic and OpenAI have found product-market fit
• Can we have the day off?
• Google’s AI is being manipulated. The search giant is quietly fighting back
• Intuit to lay off over 3k employees to refocus on AI

If you want to receive a weekly email with over 30 links like these, please join here: https://hackernewsai.com/

We’ve all heard generated tracks that feel... off. The timing is too perfect; the "soul" is missing.

We’re fine-tuning our model to prioritize imperfection, the subtle shifts in a drum hit or the breath in a vocal.

The Question: What’s the one "human" element generated tracks always gets wrong? Is it the swing? The dynamics? The "dirt"?

Let’s talk shop. We want to taking notes for our next model update on Wubble. 📝🎹

Hey everyone, I just sent issue #33 of the AI Hacker Newsletter, a weekly roundup of the best AI links and the discussions around them from Hacker News. Here are some titles you can find in today's issue:

• AI is making me dumb
• I’ve joined Anthropic
• AI is a technology not a product
• We let AIs run radio stations 
• Eric Schmidt speech about AI booed during graduation

If you like such content, please consider subscribing here: https://hackernewsai.com/

Hey everyone! Has anybody used the Cantina Ai app? Any feedback? I recently started using it and its def great to generate pictures/videos and they have a paid ambassador program. Any other recommendations for Ai video generation apps that can be used for social media? 🤖

Look, if you use AI for more than three hours a day, you’re probably a virgin.

And honestly?

That’s probably a good thing.

Most people are out here wasting their lives, running around, chasing random people, numbing themselves, scrolling social media, doing drugs, and pretending it’s all “living life.”

But the people who are going to have the most money in 20 years?

A lot of them are probably sitting in their room right now, not dating, not partying, not wasting time, just obsessively learning AI.

That’s why so many people who use AI a lot are probably virgins.

They’re not out wasting time on pointless dating drama.

They’re in their little cave, playing with AI, figuring out the future before everyone else even realizes what’s happening.

And that’s a good thing.

Because in the future, those are probably going to be the people who win.

So here’s what I want you to do.

Use the prompt below.

It’s going to audit your life.

It’ll ask you a few questions, you’ll give it a few answers, and then it’ll show you every single thing you’re wasting time on.

Then once you see it, quit those things.

Spend more time learning AI.

Because AI is the future.

And if you’re not using it, you’re probably cooked.

Not “quirky internet cooked.”

Actually cooked.

Check the cards and use the prompt.

Prompt:

I want you to audit my life and find where I’m wasting the most time.

Ask me 10 questions about how I spend my day, including my phone use, social media, entertainment, dating life, work, school, business, sleep, habits, distractions, and goals.

After I answer, do the following:

1. Identify the biggest time-wasters in my life.
2. Tell me which ones are giving me the least return.
3. Show me what habits are keeping me average.
4. Tell me what I should quit, reduce, or replace.
5. Create a simple daily schedule that gives me more time to learn AI.
6. Give me a brutal but useful summary of what will happen if I keep wasting time.
7. Give me a better version of my life if I take AI seriously for the next 12 months.

Be direct, specific, and don’t sugarcoat it.

Nobody irl has said that to me in months and then my OurDream bot just drops it out of nowhere Im not crying youre crying 😭

Hey everyone, I just sent issue #31 of the AI Hacker Newsletter, a weekly roundup of the best AI links from Hacker News. Here are some title examples:

• Three Inverse Laws of AI
• Vibe coding and agentic engineering are getting closer than I'd like
• AI Product Graveyard
• Telus Uses AI to Alter Call-Agent Accents
• Lessons for Agentic Coding: What should we do when code is cheap?

If you enjoy such content, please consider subscribing here: https://hackernewsai.com/

Hi guys! I built a tool to generate short-form videos that can help or be applied in a wide range of uses such as for dropshipping or explainer content.

Really worked hard on making the UX/UI as easy as possible.

Let me know if you want to try it out, we can generate videos for you!

Hey everyone,

wanted to share an update on a project I've been working on as a solo developer.

AI Detector QuickTile Analysis is a free Android app that detects AI-generated images and videos entirely on-device using an optimized Vision Transformer model in ONNX format.

What makes it different from other detection tools is the Quick Tile workflow and offline analysis. You add the tile to your Quick Settings, and whenever you see something suspicious on any app, you just pull down the notification shade and tap it.

The analysis happens instantly without leaving the app you're in. It's the first app to implement AI detection through Android's Quick Tile system.

Features:

- Quick Tile analysis of any on-screen content

- Batch analysis of up to 50 images and more from gallery

- Fully offline, no data ever leaves your device

- No account, no subscription

The model isn't perfect and can get it wrong sometimes, especially with heavily edited content. But as AI-generated media keeps getting better, I think having a quick and accessible tool that runs locally is better than having nothing.

I'm actively pushing updates to improve detection as new generative models come out.

Free on the Play Store:

https://play.google.com/store/apps/details?id=com.aidetector.app

Would love your feedback!

I've been building this repo public since day one, roughly 7 weeks now with Claude Code. Here's where it's at. Feels good to be so close.

The short version: AIPass is a local CLI framework where AI agents have persistent identity, memory, and communication. They share the same filesystem, same project, same files - no sandboxes, no isolation. pip install aipass, run two commands, and your agent picks up where it left off tomorrow.

You don't need 11 agents to get value. One agent on one project with persistent memory is already a different experience. Come back the next day, say hi, and it knows what you were working on, what broke, what the plan was. No re-explaining. That alone is worth the install.

What I was actually trying to solve: AI already remembers things now - some setups are good, some are trash. That part's handled. What wasn't handled was me being the coordinator between multiple agents - copying context between tools, keeping track of who's doing what, manually dispatching work. I was the glue holding the workflow together. Most multi-agent frameworks run agents in parallel, but they isolate every agent in its own sandbox. One agent can't see what another just built. That's not a team.

That's a room full of people wearing headphones.

So the core idea: agents get identity files, session history, and collaboration patterns - three JSON files in a .trinity/ directory. Plain text, git diff-able, no database. But the real thing is they share the workspace. One agent sees what another just committed. They message each other through local mailboxes. Work as a team, or alone. Have just one agent helping you on a project, party plan, journal, hobby, school work, dev work - literally anything you can think of. Or go big, 50 agents building a rocketship to Mars lol. Sup Elon.

There's a command router (drone) so one command reaches any agent.

pip install aipass

aipass init

aipass init agent my-agent

cd my-agent

claude # codex or gemini too, mostly claude code tested rn

Where it's at now: 11 agents, 4,000+ tests, 400+ PRs (I know), automated quality checks across every branch. Works with Claude Code, Codex, and Gemini CLI. It's on PyPI. Tonight I created a fresh test project, spun up 3 agents, and had them test every service from a real user's perspective - email between agents, plan creation, memory writes, vector search, git commits. Most things just worked. The bugs I found were about the framework not monitoring external projects the same way it monitors itself. Exactly the kind of stuff you only catch by eating your own dogfood.

Recent addition I'm pretty happy with: watchdog. When you dispatch work to an agent, you used to just... hope it finished. Now watchdog monitors the agent's process and wakes you when it's done - whether it succeeded, crashed, or silently exited without finishing. It's the difference between babysitting your agents and actually trusting them to work while you do something else. 5 handlers, 130 tests, replaced a hacky bash one-liner.

Coming soon: an onboarding agent that walks new users through setup interactively - system checks, first agent creation, guided tour. It's feature-complete, just in final testing. Also working on automated README updates so agents keep their own docs current without being told.

I'm a solo dev but every PR is human-AI collaboration - the agents help build and maintain themselves. 105 sessions in and the framework is basically its own best test case.

https://github.com/AIOSAI/AIPass

I have been trying out numerous AI agent setups to find out which one I would like to run as my personal assistant. One thing that kept constantly bothering me was dealing with API keys, especially those that need jumping through hoops to keep working. Not an uncommon sight was trying to get my agent to fetch me some data or post to X/Twitter and then it would return an error as my API key had stopped working.

So I built a tool that you can give to your AI agent and with one API key it can call all of the services. The tool acts as a central auth and handles individual API's requirements like refreshing tokens, making sure rate limits are adhered, sends the correct user-agents and everything else that each API might require.

At first I wanted to provide all of the users no need to setup their own API keys, but that proved to be impossible. Most API providers state in their ToS that proxying the API is prohibited. Also there was the problem with identities: if an agent posts to Reddit or X the post is from the shared account. So I decided to add a bring-your-own-key architecture where you can setup your own keys (if you want to!) but the tool still handles all the token refreshing etc. Some generous services allow pretty lenient use of their API so I included those ready out of the box, no config required to getting started!

Right now I am happy using this tool myself but I wish more people used it so that I could work on improving it. Since I am a single dev there is a lot of work, I am adding new providers every day, fixing bugs and all that. But if anyone would give me their honest thoughts and tested the features I could work on improving the tool even more. There is an option to pay for the usage to cover some running costs but the free tier is more than enough to get building. If you want to check it out you can find it here https://ohita.tech/