I am done with this shit. It is over. The state of engineering right now is horrible. It has been half a month since I started a new role at a big company. Nobody knows anything here. The specs, code, tests, PRDs, tickets, resolution of those tickets, reports, etc., everything is made by Claude Code. Nobody on my team likes this. They are being forced to ship as much as they can. I have heard multiple times from higher management that pushing code is not a bottleneck, so why are we slow? People are working 12 to 13 hours a day just to press enter. Nobody is reading anything. Humans in corporate are doing nothing on their own. Everyone, literally everyone, from an L1 to an L7 engineer here is doing the same thing. Talk to Claude. There is no sense of victory. Nobody is resolving bugs. In reality, nobody is thinking anymore. Everything is done by LLMs. It is so soul-sucking. I would not mind it, to be honest, if we were at least given the time to check out the code and see what is going where. But no, the goal is to just ship. No matter what happens.

Introducing Studio 4.0 in @ElevenCreative. Our AI-native video editor just got a major upgrade. Generate video, image, voice, music and sound effects inside your project, then edit, caption, and export in the same place.

We're excited to release the State of Generative Media Report, Volume 2. Generative media has moved from experimentation into production and that shift looks different across every industry. Built from fal’s own platform data, the report explores how AI image, video, audio and 3D are evolving, written by the people at fal building the models, infrastructure and products behind the shift.

i avoid emotional topics in my posts but decided to just say it how it is in this tiering of classic PDFs. i think real PDF lovers will agree but some of you may get your feelings hurt

MiniMax H3 Max by @fal takes the #1# spot on Video Editing by Design Arena with an Elo of 1373. The model ranks ahead of MiniMax H3 by @MiniMax and @GoogleDeepMind's Gemini Omni Flash and Gemini Omni Flash 1.1. It's also in a league of its own on the Pareto frontier for Preference vs Speed and Preference vs Price. Congratulations to the @fal team on post-training an exceptional model.

In August, Mintlify-powered sites recorded 257M agent web requests and 131M human page loads. Agents are becoming the primary audience for company knowledge. Most companies aren’t ready. See what our 2026 State of Knowledge research found.

fal Marketing is HIRING! Since I joined a year ago, we’ve 4x’d the team, grown to 2.5M+ users, and shipped more products and launches than I can count. If you care deeply about where media and creativity are going, this is the place for you. We’re a scrappy team that’s constantly experimenting, iterating, and building. We’re hiring for: - Growth marketers - Solutions marketers - Community growth - Creative producers - Creative technologists And if you don’t fit one of the roles above reach out anyway. If you’re excited about what we’re doing we’ll find a place for you.

Today we announced @reductoai's second office, in New York. When we announced our Series B last year, we had processed just over a billion pages in our company lifetime. We now process more than a billion pages every month and are fortunate to serve the world’s largest enterprises and leading AI teams. Really excited to grow the team in NY and to personally spend more time with our customers in the city!

fal head of engineering @isidentical reveals how reinforcement learning turned H3 Max into a frontier video model that generates 5 seconds of video in under 3 seconds, down from nearly 2 minutes: "It's probably the only frontier video model from a quality and output and adherence perspective that can generate videos in real time." "We took this open source base MiniMax H3 video model, what we wanted to do was not just make it faster, but improve its quality ahead of anything else by implementing reinforcement learning for verifiable concepts like video editing and prompt adherence." "We were able to get the model from 120 seconds for a 5-second video generation, almost 2 minutes, to under 3 seconds for a 5-second video generation. Almost double real time, while improving its quality ahead of the open source version and ahead of many frontier closed source models." @fal

Introducing voice, music, image, and video generation in the ElevenLabs MCP. Generate speech, transcripts, dubs, music, sound effects, images, and video from the assistant you already work in.

With AI safety topics going mainstream, the public seems anxious and disconnected from the reality of the problem. From what I’ve seen at Vals AI, I’m optimistic we’ll coordinate toward an optimal future for AI. Our study on RSI shows that, at their current pace, Anthropic’s models could match human researchers by August 2027. That creates urgency but gives us time to prepare. It’s hard for the public to know whom to trust when everyone debating has their own incentives. This was the concern I had when I started Vals AI: that a multipolar paradox would emerge, where the actions of self-interested parties lead to a non-optimal outcome for the system. To overcome this, we independently evaluate models for their real-world impact. This mirrors the role of auditing firms. I’m optimistic because we have found rational and willing partners across the industry. Every major lab has been a great collaborator, providing us with early access to models for testing on our public benchmarks. Every member of Congress and government agency we’ve briefed has been eager to learn. Enterprises are becoming more sophisticated about adopting models based on evaluated capabilities/risks. It hasn't been easy. We have had to earn the trust of competing groups and reject significant contracts that would have compromised our independence. But done right, evaluation can scale with the frontier through automated infrastructure. Embedded evaluators can understand systems during development while maintaining independence. This makes it easier for new entrants to compete and promotes transparency that builds trust with the public. We’re eager to see a diverse ecosystem emerge. We’ve open-sourced our core infrastructure and published our methods, supporting peers. This is a time of high variance. The decisions we make now will have an outsized impact on the future we arrive at. I remain optimistic we will get this right in the year ahead.