Luigi Senese

Higgsfield is #5 on a16z’s new consumer AI monthly revenue leaderboard. Glad we passed the research team’s due diligence.

A very short story

Most AI video prompts fail before generation even starts. Not because the model is bad. Because the prompt says: “Cinematic man running through a city. Realistic. 4K.” That describes a vibe. It does not direct a shot. A professional AI filmmaking prompt should answer: → What should the audience notice? → Who is in the frame? → What exactly are they doing? → Where is the camera? → What lens are we using? → How does the actor perform? → Where does the light come from? → What physically reacts to the action? → Where does this shot begin and end? The framework I use is: INTENT → SUBJECT + ACTION → FRAME → OPTICS → CAMERA → PERFORMANCE + PHYSICS → LIGHT + SPACE → CONTINUITY Here is what that actually means. 1. INTENT Before writing anything, decide what this shot is doing. Reveal information? Create tension? Show scale? Capture a reaction? If the shot has no purpose, camera language will not save it. 2. SUBJECT + ACTION Do not write: “Man is scared.” Write the behavior: “He freezes at the doorway, eyes tracking toward the sound, shoulders tightening before he slowly steps backward.” Prompt visible behavior. 3. FRAME Define what the camera sees. → Wide = geography and scale → Medium = action and relationships → Close-up = emotion and reaction → Insert = important detail Then add angle, height and composition only when they matter. 4. OPTICS Lens choice changes the image. → 24mm = environment, perspective, speed → 35mm = natural spatial energy → 50mm = balanced human perspective → 85mm = compression and intimacy → Macro = tactile detail Do not add “35mm” because it sounds cinematic. Know why it is there. 5. CAMERA Use one motivated camera behavior. Static. Push-in. Pull-back. Tracking. Handheld. Pan. Tilt. Crane. Orbit. The camera should move because the story gains something. 6. PERFORMANCE + PHYSICS This is where many AI shots collapse. Direct: → eyelines → breathing → hesitation → posture → weight shifts → foot contact → momentum → clothing response → object interaction → balance and recovery “Runs fast” is weak direction. “Accelerates, loses traction for half a step, catches his balance and keeps moving” gives the model physical information. 7. LIGHT + SPACE Describe motivated lighting. Not: “Beautiful cinematic lighting.” Instead: “Warm sodium light from camera-right, cool ambient rain fill, hard reflections across wet asphalt.” Then describe only the environmental details that affect the shot. 8. CONTINUITY Every shot exists between two states. Define: → start position → screen direction → costume → props → injuries → scale → geography → end position This matters even more when generating multiple clips. And one major distinction: Text-to-video and image-to-video should not be prompted the same way. Text-to-video needs more visual information. Image-to-video already has the character, composition, lighting and environment. So stop describing the reference image again. Prompt the motion: → camera motion → subject motion → performance → environmental motion → timing → continuity The biggest rule: One shot. One camera setup. One clear beat. Do not cram five actions, three camera moves and two emotional changes into an 8-second generation. PS:) Follow for more! . .

I've been actively fighting almost guaranteed age-related loneliness for years, studies show after age 30 you start seeing friends less and when you get older especially men don't have any social life left! It's preventable, but it takes effort and initiative We've now organized 70 weekly coworking days where we meet with friends and work together, do show and tell, and try help each other make things (also hardware stuff more recently) We've also started organizing movie nights, art nights, barbecues, we watched the World Cup final on a projector screen in the garden with friends We did a collage night the other day where we bought cheap gossip magazines, colored paper, and Pritt glue, and gave everyone scissors to make their own art, I think nobody spent time on their phone for at least 4 hours, making things puts you in a flow state and it's fun to do it in a group because you talk about different stuff while making things than you would for ex having a dinner Movie nights are nice too but less popular I think cause everyone prefers to watch movies alone and also you can't really talk during a movie Coworkings range from having sometimes 20 people to sometimes just 2 people, people have their own lives, but me and @rameerez still try to organize them weekly One thing I realized is that we are usually the ones organizing stuff, but that's not a bad thing, there's even studies about this, there's usually a few people in a group who organize most of the events If nobody in your group organizes stuff, it doesn't mean nobody wants to do stuff, but you have to take the initiative to bring people together which isn't easy in a time where phones and apps and the internet are simply easier and cheaper dopamine than driving to a friends house for a party You can start with a coworking day, everyone brings their laptop, and you provide WiFi and coffee, then later you can try more types of events Having an active social life is just as important or in some studies even more important for health than physical fitness After a nice party I feel tired but satisfied, I had fun and didn't spend time on my phone or computer but instead talked and laughed with friends etc. We don't drink alcohol with very few exceptions and nor do our friends, so it's mostly just having really nice food and sparkling water or kombucha etc, and we don't really need alcohol, after a few hours it gets fun enough anyway! So I recommend everyone, take initiative, and organize something and get people together, it'll be fun! 😊

Kling 4.0 is coming this October. Kling 4.0 Flash is live now for Ultra Yearly subscribers. Kling 4.0 brings video creation to a new level of visual realism, creative control, and narrative completeness. 🎞️ Upgraded Audio & Visuals: Stable dynamic motion, high-quality stereo audio, more accurate lip sync, up to 4K resolution, and 10-bit HDR output. 🔮 Omni Reference: Richer reference options with up to 15 multi-modal references, more consistent results, and enhanced video editing. 🎥 Seamless Storytelling: Multi-keyframe control supporting up to 10 keyframes, native 30-second generation. 🌍 Diverse Possibilities: Video extension, support for multiple languages, accents, and dialects. The stage is set. You call the shots!

We gave Claude Opus 5.5 access to 12 laptops. The task: turn one prompt into a complete launch video. Using Computer Use and Higgsfield MCP, it: > divided the work across every computer > created the visuals, built the animations > assembled a fully editable After Effects project. This is what an AI-native motion studio looks like.

Calling Higgsfield “just a wrapper” tells you surprisingly little about the economics of our business. In over 40% of cases, we get to decide which model does the work for our customers. As models become more interchangeable, the ability to move demand between them becomes a moat. If you’re mapping where value accumulates in AI, follow who owns the customer relationship. I went deeper on this with @HarryStebbings on 20VC.

Today Higgsfield crossed $1B in annualized revenue. We've grown 20x since September 2025. There’s a popular argument that foundation models will capture all the value in AI, leaving little for the application layer. Higgsfield is proving the opposite thesis, as better models expand what enterprises can achieve and increase the value of applications embedded in their workflows. That thesis is reflected in our business: 300% net revenue retention. 115% MoM growth in enterprise adoption since June. Positive gross margin since the beginning of this year. Thank you to our incredible team and everyone building it with us.

Jev is HERE and this is the CLEAREST explanation of what it is and what NEW businesses it unlocks. (and at the end I'll tell you how to get Jev even if you're on the waitlist) WHAT IT IS You know how you open your inbox and have to decide what's junk, what needs a reply, and what can wait? Jev does that part. It looks at each thing and says "this is junk, I'm 94% sure." It doesn't write anything back to you. It just sorts. 1,700 emails for 18 cents, instantly. That sounds kinda trivial but the important part WHAT IT UNLOCKS My explanation of Jev sounds small until you realize HOW MANY jobs are exactly this. Someone reading a stack of applications. Someone deciding which support ticket goes to which team. Someone looking at inbound and deciding who's worth calling back. A few ideas on what it unlocks: 1/ Instant quotes that are actually instant. Every quote form on the internet says "we'll email you by end of day." Build the version that answers in under a second, for roofers, movers, insurance, legal intake. 2/ Lead scoring as a product. Every agency and service business has a contact form full of junk. Score every submission and send the real ones straight to the owner's phone. 3/ Support triage for companies with no support team. The ticket gets classified and routed before anyone opens it. 4/ Clipping tools. Pass in a transcript, get the best moments scored in three seconds. Every clipping product just got a cheaper engine. 5/ Application piles. Grants, permits, insurance claims, job apps, loan docs. Someone reads that stack one item at a time today. 6/ Marketplace matching. Someone types what they need and gets matched to the right local business instantly instead of waiting for callbacks. 7/ Browser agents that actually move FAST. That makes bulk browser work practical: pulling quotes from five carriers, filing the same form for 200 clients, checking supplier inventory in real time etc. TLDR; find an expensive queue and put Jev at the front of it. HOW TO GET IT I didn't realize you can skip the waitlist because Jev is live on the Vercel AI Gateway right now, so you can start calling it today. In this episode, we share how. Episode now live on @startupideaspod (thanks to @ryanvogel for coming on and spilling the sauce today) Watch: youtube.com/watch?v=4mTLpuQp… Jev is a big deal because this is a whole new way to do AI Really cool Happy Jev day.

Jev is really good at content filtering and asset selection. DeepSeek + Higgsfield turn the selected assets into ad creatives.

JEV is INSANE. We gave it 700 high-intent leads and personalised outreach messages. In 40 seconds, it predicted how each message would perform, assigned a confidence score and detected lead-message mismatches. All for just $0.09. JEV can also score leads, analyse buying signals, match each prospect with the best message and identify the campaigns most likely to perform based on data. Coming soon to @GojiberryAI+ MCP. Comment “JEV” for early access.

AGENT HARNESSES ARE THE NEW GPT WRAPPERS What exactly is an agent harness? A harness does 4 things: 1. Runs the model in a loop so it keeps working step after step instead of answering once and stopping. 2. Gives it hands to read files, call tools, open portals, and run code. 3. Manages its memory so hour three of a job still knows what happened on hour one. 4. Enforces the rules about what it can touch and when it has to stop and ask a human. WHY IT'S INTERESTING - The market is MEGA. I think about it like a wrapper let you sell software ($800B market) but a harness lets you sell the work ($5T+ market)! - It doesn't depend on any one company's model. The knowledge about the job lives in the harness, so you can run GPT today, Claude next month, an open model like Google Gemma, Qwen, Deepseek etc on your own machine after that, and it keeps working. A wrapper was one model doing everything and a harness is a router. - It gets better the more you use it. See, every correction a human makes becomes a rule the harness keeps, so what you have after 500 jobs is a completely different product than what you had after 5. Wrappers only got better when OpenAI got better. - You can charge for finished work! The harness knows when a job is done, so you can price per claim, per filing, per review, per resolved exception, or per closed month. This helps compete with SaaS! - Most jobs are just the same handful of decisions, repeated, using the same few tools. That's true for most of the 800+ occupations out there, which is why almost all of them could have a harness built for them. Lots of space for startups to be building. -The frontier labs won't come for these. OpenAI is not going to learn how a freight claim gets denied in Rotterdam or which prior auth your specific payer rejects. Those markets are too small for them and the knowledge only exists inside the job. They'll keep making the models better, which just makes your harness better which is cool. - OH, AND really important, you can ACTUALLY build one now. OpenAI's Agents API, Claude's managed agents, Vercel's eve, LangChain harness framework etc. They all make it way easier to build agent harnesses. Agent harnesses truly are the new GPT wrappers. This is just the beginning.

I think a lot of people also get caught up in looking at people like you doing what you do and think that their only path forward is the same kind of 'sexy' projects that get 50k users overnight (without realising it took a decade of grinding to get there). No-one wants to work on the unsexy problems for boring industries. Vet clinics, pest care, HOA/community management, self storage, funeral homes, linen rental - boring stuff through which billions of dollars are flowing.

We Must Pace the Frontier: I’ve written a new essay on why the AI industry should slow down, with a three-part plan for doing so. Anthropic is unilaterally committing to the first of these steps. We’ll provide third-party evaluators with permanent, employee-level access to our systems, so that they can verify adherence to our safety measures, report on incidents, and assess models’ alignment during training. You can read the full post here: darioamodei.com/post/we-must…

since you guys loved the exploding tesla.. I used GPT-6 Astra to create a 3D website that pulls apart the male anatomy into 2,234 modeled pieces! we are in a renaissance of learning

GPT-6 Astra isn’t just for chatting. People are using it to build games, automate trading, create content and make real money. 10 ways you can use Astra to start making money today.

I think cold email is going to die. Every email inbox will have an agent gatekeeper soon, and the only way through will be a warm intro or being interesting enough that the agent decides you're worth its person's time.

Nothing—and I mean nothing—beats Zurich.