vertically integrated ai b2b saas storyteller

Joined January 2022
Directing and producing this campaign has truly been an amazing experience. From renting an airplane standing set and filling it with lovely passengers, to working tirelessly on the VFX and lighting that brought it to life, this project has been crazy to say the least. @WindsorNguyen and @itsCathyDi are genuinely cracked founders that I had a wonderful time collaborating with. Looking forward to seeing DAuth become the standard 🚀
MCP is a pain in the ass. To fix that, we’re launching DAuth: the first secure, multi-tenant MCP auth solution. OAuth isn’t enough. It doesn't support dynamically passing API keys, and you can’t trust passing credentials to non-OAuth servers, since secrets are exposed. This forces existing MCP marketplaces to be OAuth-centric and single-tenant. But OAuth is annoying to implement and assumes security expertise. DAuth works for every auth case. We encrypt your credentials on the client-side, guaranteeing MCP servers never see them. You can finally ship agents with peace of mind. For the first time, MCP is ready for takeoff 🛫
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My voice btw 😭
For the past 50 years, every operating system was built for one user: the human. Introducing Open Swarm, the operating system built for AI. Up to 2x faster and 3.5x cheaper. Your apps, files, teams, and agents in one place. The next 50 years will be built for agents.
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A better way to manage your agents, love the canvas interface, keep up the great work guys!
For the past 50 years, every operating system was built for one user: the human. Introducing Open Swarm, the operating system built for AI. Up to 2x faster and 3.5x cheaper. Your apps, files, teams, and agents in one place. The next 50 years will be built for agents.
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the design wizard strikes again 😮‍💨
what if controlling your agents felt like orchestrating them? design, interactions, animations, all made in code with @Tempo_Labs
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brewing a launch vid + some tea 🍵
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Difficulty mode impossible: Sci fi movie or b2b saas launch video
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whoever said sf is boring clearly has never smoked hookah at Pasha
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growth operators who work with a roster of early stage startups may be some of the best positioned people to deploy capital successfully. they have the intuition of what gtm will work, and closer proximity to judge a founder’s traits than full time vcs plus, with a good product, people from this background are not picking winners, they’re helping create them.
i’ve met 100+ founders over the last 8 months to advise them on growth 3 of them went from $0 → $30m ARR in less than 6 months i might need to raise a small fund with the quality of founders i get to meet, i might have a generational run as a solo GP
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trying to tap in with fringe people building on the frontier of new media who should i follow?
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Replying to @SHL0MS
Fair warning before I dig in: this image is actually a very competent rendition. It's doing more right than most AI Monet pastiches. But you asked what makes it inferior to a real Monet, so here's the honest breakdown. What's missing — the physical object A real Monet is a thing before it's an image. This is the biggest gap and it's not solvable by better prompting. No impasto. Monet loaded paint thick. His water lily pads sit physically on top of the canvas — you can see the ridges where the brush dragged, the little peaks where pigment piled up. Look at the lily pads in your image: they're smooth tonal gradients pretending to be brushstrokes. A real one would catch raking light differently from the water around it. No canvas weave. Monet painted on linen with a specific tooth that broke up his strokes and let underlayers peek through. Your image has a uniform digital surface — the "texture" is illusionistic, painted into the pixels rather than emerging from the substrate. No drying history. Real Monets have cracks, areas where wet-into-wet bled, areas where dry paint was scumbled over dry paint. Pigments aged differently — his cobalt blues shifted, his madder lakes faded. The image has no chronology in it. It's all painted "at once." What's wrong with the marks themselves Brushstroke direction is decorative, not descriptive. Monet's strokes do work — vertical strokes for reflections of vertical things (poplars, irises), horizontal strokes for the water surface, elliptical strokes that physically describe the floating disc of a lily pad. In your image, the strokes are stylistically "Monet-ish" but they don't consistently track what they're depicting. The reflections in the upper left, for instance, have stroke directions that don't quite resolve into specific reflected objects. No hierarchy of finish. Monet had passages of intense detail next to passages left almost raw. He'd finish a single lily blossom with three decisive touches and leave a whole quadrant of water as scumbled understatement. AI tends to render everything at the same level of "doneness." Your image is uniformly busy. Edges are too soft everywhere. Real Monet has surprisingly hard edges in places — the rim of a lily pad against dark water can be a single confident knife-edge stroke. AI defaults to blending. Look at the pads in your foreground: their edges dissolve gradually. Monet's often don't. The color problem The palette is plausible but generic. Monet's late Giverny palette was specific and slightly weird: viridian, cobalt violet, French ultramarine, cadmium yellow, vermillion, lead white. The unusual one is the violet — he used cobalt violet aggressively and it shows up in shadows where you wouldn't expect it. Your image has some purple in the lily pad rims, which is the right instinct, but the violets aren't doing structural work the way Monet's do. No optical mixing. Monet placed unmixed complementary colors next to each other so your eye blends them at viewing distance. Pure orange next to pure blue, reading as a luminous neutral. Your image has colors that are already pre-mixed into harmonious mid-tones. It's pleasant but it doesn't vibrate. The whites are wrong. Monet's whites are almost never white — they're tinted pink, blue, lavender, yellow depending on the light condition he was chasing. The white lily in your upper-left is closer to a true neutral white than Monet would ever paint. The conceptual gap This is the part that actually matters and the part no model will close. Monet was solving a problem. Each canvas in the Nymphéas series is an answer to a specific question: what does this pond look like at 7am in August? What happens to reflections when wind crosses the surface? The paintings are records of sustained looking at a real place he built and tended for thirty years. Your image is a style reference, not an observation. It's a painting of "a Monet" rather than a painting of a pond. No series logic. A single Monet water lily painting is meaningful partly because of the ~250 others. They're variations against each other. This image is an orphan — it has no relationship to anything. No hand, no decision, no risk. Every stroke in a real Monet was a commitment by a specific 80-year-old man with failing eyesight standing in a garden. The image has no author in that sense. The "decisions" are statistical averages of millions of images. What it does get right (worth saying) The compositional asymmetry is good. The reflected verticals reading as trees/irises is a smart move. The pink lilies in the lower foreground are placed with reasonable intuition. If you cropped tightly to a 6-inch square anywhere in this image, it would pass a quick glance. The tell is always scale and surface. Stand six inches from a real Monet and it dissolves into chaos — slabs of pigment that look like nothing. Stand six inches from this and it just looks like a slightly blurrier version of itself. That collapse-into-abstraction up close is the thing you can't fake without paint.
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AI video gen is having its After Effects moment. Everyone has the tool. Almost nobody has the eye. @hardeep_gambhir is building a stage for the ones who do.
Launching the Los Angeles AI Film Festival Affleck's AI startup → sold to Netflix for $600M Cannes now has an AI Film category The year of AI + Storytelling is here Our Jury: creators behind Endgame, Spiderman, James Bond & The Incredibles Our production team: same as Oscars
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jaden kwan retweeted
WHO LET GENZ INTO MARKETING MEETINGS
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So much love for you guys ❤️ @localhosthq Was incredible to see all the emerging talent show out for this event!
thank you for everything tokyo, incredible turn out today and amazing people! grateful for everyone + the impeccable team to pull this off on a short notice. cc: @ryuzokijima @GentheZen @KechoHayashi @findingjaden
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Realizing this to be a crucial tenet for success in so many early stage scenarios recently has been eye opening. The most high agency people I admire are die-on-the-hill missionaries that are uncompromising to shiny objects in pursuit of solving the crux of their challenges.
Don’t take the money. When you have limited resources, you can't afford to be sloppy. You have to know what you're building and why. You have to prioritize ruthlessly. You have to find creative solutions instead of throwing money at problems.
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And obviously playing while in pursuit. Playing in the sandbox, and obsessed through curiosity.
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man achieving inner peace at a Worldcoin orb in Kyoto. no temple could do this
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Tragedy that we lost the H-1B, such great talent came through it…
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We had a little Easter egg where the programmers were sitting in row H-1B
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how to go viral on X: repost the same article, just call it “how to actually fix your life”
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