John Gargiulo

Today, we’re launching Airpost. I’m 46. That’s not a cool age to found a startup. At least according to Twitter. I still call it Twitter. I’ve loved advertising all my life. Since I was 19 and my mom told me about a movie called “Nothing in Common” with Tom Hanks where he plays an ad exec whose main job seems to be shooting hoops with his creative partner. That sounded fun. Since then, traditional advertising has stayed… traditional. From my 1st job out of college writing TV ads for Snapple and Fox Sports, to leading product marketing at Airbnb, I’ve seen a lot. Now the AI era is here and an entire $1T industry is about to change. Who will change it? Why not me? Why not us? Introducing Airpost: a platform and service where world-class creative strategists use custom-built AI to build video ads. Fast. If you’ve ever sat down to make an ad with AI and realized 20 minutes later you’re still wrestling with that same clip… that’s why we built Airpost. Growth teams are busy. They’re asked to do too many things as it is. They shouldn’t have to be AI experts as well. Creative strategists shouldn’t have to stare at a white box trying to decide what to prompt. They should have a partner. That’s what we aspire to be. And that’s what we’ve built our tech to do. AI ads shouldn’t have to mean only AI footage. We have an exclusive library of over 300,000 video clips we’ve shot ourselves. Our engine uses these, along with client footage and AI footage to make the ads we deliver each week. We’re funded by the best investors and humans we know. We bootstrapped our performance creative agency, Ready Set, to 200 people. I was always told VCs didn’t add value. If that’s true, it must be other VCs, because ours have been awesome. Thank you Zach Perret, Nate Abbott, Peter Hebert, Max Mullen and all of the firms and folks who’ve believed in us so far. We’ve gone from 0 to $1M ARR in the six months since we quietly started working with early clients like DoorDash, Dr. Squatch, Calm and more. So far, every customer has renewed. To celebrate the launch, we’re giving away a superagent where you: 1) Put in your product URL 2) Get snippets of what your real users are saying on Meta, TikTok, Reddit and X 3) Paste them into ad scripts Comment “Airpost” and I’ll DM you the private link. It feels (a little scary but) good to be out there. Here we go! 🚀

These bath bomb videos are satisfying to watch. The opening/normal bits look incredibly real, then the transition to AI wonderland is compelling.

@paulg It's because most politicians have never run a business. Remember when Bloomberg asked everyone on the stage at that debate, "Who has run a business?" and no one's hands went up?

At one point my son and his friend kept looking for shortcuts to getting rich. Over and over I told them the way to do it is just to make something people want. If this is what I tell my own kids about getting rich, why won't politicians believe this is how a lot of people do it?

@garrytan I finally showed up to the GStack party today also. It's really helping build bigger and more robust software.

Many such cases

I built an n8n workflow that monitors your competitors' ads and sends you a note every morning on what they're doing new. We use this internally and our team did not want me to release it but here it is 😆 It just works: → You drop in a list of competitors → It pulls every new ad they launch from the Meta Ad Library → AI analyzes each ad, including the hook, offer, and CTA → Sends a digest to your Slack or email every morning automatically → Stores everything in Airtable so you can track it over time If you’re hitting a ceiling with your ads, this can help break through. Make sure we're connected and comment “Yes” and I'll dm the entire workflow.

Hilarious. I want to see the rest of the episode.

I'm looking forward to being able to make funny movies for my kids this way. Searching Apple TV for ones to watch taking too long anyway.

Prompt 2: Paste this in Kling 10-second cute 3D animated comedy short, ultra-detailed stylized animation, cinematic DreamWorks/Pixar-style lighting, expressive character acting, exaggerated comedy physics, cozy American suburban atmosphere, vibrant cinematic colors, realistic food textures, cinematic smoke and fire simulation, smooth 24fps animation, emotional and hilarious tone. **SHOT 1 (0.00–1.00s)** – Wide establishing shot, slow push-in, eye-level: Warm American suburban kitchen during golden sunset. Football game softly playing on TV. A messy-haired 17-year-old American son in oversized hoodie proudly places an absurd gigantic burger onto the kitchen island. Across from him sits his retired firefighter dad: broad shoulders, gray beard, faded flannel shirt, intimidating calm energy, sipping iced tea. **SHOT 2 (1.00–2.00s)** – Tight close-up, slight top angle: The burger is absolute chaos: onion rings, mac and cheese, towering bacon stack, sauce exploding everywhere, collapsing structure barely held together by a toothpick. Dramatic steam rising. **SHOT 3 (2.00–3.00s)** – Extreme close-up on dad: Dad takes one huge bite. Silence. Slow chewing. Eyebrows lower slightly. Tiny disappointed side-eye toward son. One eyebrow lifts like a barbecue judge silently saying “what the hell is this?” **SHOT 4 (3.00–4.00s)** – Close-up on son, fast push-in: Son’s confident smile instantly dies. Eyes widen. Tiny panic sweat bead forms. He whispers: “...oh no.” **SHOT 5 (4.00–5.00s)** – Hero wide shot, low angle: Backyard grilling station at sunset. Dad now wears faded apron reading “MEAT COMMANDER.” Massive grill smoking behind him. Son nervously watches from patio doorway holding failed burger remains. **SHOT 6 (5.00–6.50s)** – Fast-paced cinematic grilling montage: Burger patties slammed onto flaming grill in slow motion. Fire erupts upward dramatically. Metal spatula spins through air. Cheese melts perfectly over sizzling patties. Smoke rolls across camera lens. Dad flips burgers effortlessly through giant flames like an action hero. **SHOT 7 (6.50–8.00s)** – Tight cinematic food glamour shot: Perfect cheeseburger assembled beautifully in extreme detail: toasted brioche bun, juicy beef patty, melted American cheese, crisp lettuce, tomato, pickles, clean sauce layer. Elegant simplicity. Cinematic lighting glistening across burger. **SHOT 8 (8.00–9.00s)** – Medium two-shot at backyard table: Dad silently slides burger toward son without breaking eye contact. Son takes one massive bite instantly. **SHOT 9 (9.00–10.00s)** – Final wide cinematic pull-back: Son emotionally overwhelmed, clutching burger with tears in eyes like sacred treasure. Dad casually grills another burger in background while fireworks from nearby baseball game light up the evening sky. Warm smoke drifting through frame. Cozy hilarious ending.

Prompt 1: Paste this in ChatGPT 10-second cute 3D animated comedy short, ultra-detailed stylized animation, cinematic DreamWorks/Pixar-style lighting, expressive character acting, exaggerated comedy physics, cozy American suburban atmosphere, vibrant cinematic colors, realistic food textures, cinematic smoke and fire simulation, smooth 24fps animation, emotional and hilarious tone, shallow depth of field, highly expressive faces, polished feature-film quality. CONCEPT: A teenage boy proudly serves his retired firefighter dad an absurd “ultimate burger.” Dad silently judges the disaster, takes over the grill, and delivers a perfect cheeseburger masterclass that emotionally destroys the son. **SHOT 1 (0.00–1.00s)** — Wide establishing shot, eye-level, slow push-in: Warm suburban American kitchen during golden sunset. Football game quietly playing on TV. Family magnets on fridge. Condiment bottles and baseball gear visible in background. A messy-haired 17-year-old American son in oversized navy hoodie proudly presents an absurd giant burger on the kitchen island. Across from him sits his retired firefighter dad: broad shoulders, thick gray beard, faded red flannel shirt, calm intimidating energy, sipping iced tea while silently evaluating the situation. **SHOT 2 (1.00–2.00s)** — Tight cinematic close-up, slight top angle: The burger is complete chaos: giant onion rings, overflowing mac and cheese, stacked bacon tower, dripping sauces everywhere, greasy smashed patties collapsing under their own weight, tiny toothpick barely holding the structure together. Dramatic steam rising upward in cinematic lighting. **SHOT 3 (2.00–3.00s)** — Extreme close-up on father’s face: Dad takes one massive bite. Silence. Slow chewing. Eyes narrow slightly with disappointment. Tiny side-eye toward son. One eyebrow slowly lifts like a professional barbecue judge witnessing culinary terrorism. **SHOT 4 (3.00–4.00s)** — Close-up on son, fast push-in: Son’s confident smile instantly collapses. Eyes widen dramatically. Tiny panic sweat bead appears near forehead. Mouth slightly open in fear. Warm kitchen lighting reflecting in terrified eyes. **SHOT 5 (4.00–5.00s)** — Hero wide shot, low cinematic angle: Backyard grilling station glowing under orange sunset sky. Massive smoking grill behind dad. He now wears faded black apron reading “MEAT COMMANDER.” Smoke and sunlight create dramatic action-hero silhouette. Son nervously watches from patio doorway still holding remains of failed burger. **SHOT 6 (5.00–6.50s)** — Fast-paced cinematic grilling montage: Burger patties slammed aggressively onto flaming grill in slow motion. Fire erupts upward dramatically. Metal spatula spins through air. Cheese melts perfectly over sizzling patties. Smoke rolls across camera lens. Dad flips burgers effortlessly through giant flames like a barbecue action hero. **SHOT 7 (6.50–7.50s)** — Tight cinematic food glamour shot: Perfect cheeseburger assembled beautifully in extreme detail: glossy toasted brioche bun, juicy grilled beef patty, melted American cheese, crisp lettuce, fresh tomato slices, pickles, clean sauce layer. Elegant simplicity. Cinematic food-commercial lighting glistening across burger surface. **SHOT 8 (7.50–8.50s)** — Medium two-shot at backyard picnic table: Dad silently slides perfect burger across table toward son without breaking eye contact. Son grabs burger carefully with both hands and immediately takes one giant emotional bite. **SHOT 9 (8.50–9.50s)** — Extreme close-up on son’s face: Immediate spiritual awakening. Eyes water emotionally. Knees wobble slightly. Tiny distant bald eagle scream implied for comedy. Heavenly warm glow behind him as fireworks begin softly appearing in background sky. **SHOT 10 (9.50–10.00s)** — Final wide cinematic pull-back shot: Cozy suburban backyard at nightfall. Son emotionally overwhelmed, clutching burger like sacred treasure while tears roll down cheeks. Dad casually grills another burger in background surrounded by smoke and warm firelight. Baseball stadium fireworks softly exploding overhead. Warm wholesome comedy ending.

Made this 3D Pixer style animation using just 2 prompts. Tools used: > ChatGPT for the image > Kling for the video Feel free to copy the prompts from the next tweet 👇

My 30+ observations on the greatest opportunities in AI agents right now: And some ideas that are keeping me up at night. 1. The new buyer on the internet is an AI agent. Imagine billions of new customers showing up with money to spend but they only shop via MCP. That's what's happening. No MCP server means you're invisible to the fastest growing buyer on the internet. 2. Every franchise system in America (30,000+) needs an agent layer and none of them have one. One founder per franchise vertical. That's 30,000 businesses waiting. 3. Everyone said "distribution is the only moat" a year ago. Now I'd add that the only moat is distribution plus memory. The company that has your audience AND your agent's accumulated context is impossible to leave. 4. Consumer mobile is more interesting than it's been since 2012. Apps can finally DO things for you instead of showing you things. The next wave of $100M apps are being built right now. 5. The most interesting startup nobody has built is an agent marketplace where you rent access to someone else's trained agent. A recruiter spent 6 months training a sourcing agent on healthcare hiring. That agent is worth renting to every other healthcare recruiter on earth. The agent itself becomes the product. 6. A sorta strange phenomenon that's happening right now is agents are developing preferences. Give the same agent the same task 100 times and it starts developing patterns in how it approaches it. Nobody is studying this yet. But the agents that develop good patterns are worth more than the ones that don't. That's a new kind of asset. 7. Dead internet theory is about to become dead SaaS theory. Half the apps you use will quietly replace their support team, their onboarding team, and their content team with agents. You won't notice for months. Then you'll realize you haven't talked to a human at that company in a year. 8. The most valuable data in the world right now is sitting in the support tickets of small or mid tier SaaS companies. Every ticket is a customer telling you exactly what to build next. Mine this. 9. The most interesting pricing problem nobody has solved is how do you price a product when your costs change every time OpenAI or Anthropic updates their model pricing? Your margins can swing 40% overnight based on a decision made in San Francisco. The company that builds dynamic pricing infrastructure for agent-based businesses solves a problem every AI company has. 10. The best AI products feel like they're reading your mind. The worst ones feel like filling out a form with extra steps. 11. An interesting arbitrage I've noticed lately is hiring a human VA for $20/hour to supervise an AI agent that does $200/hour work. The human just checks the output. 12. The managed AI agent business is becoming the new agency model. $5k/month per client. You build it, run it, maintain it. The client gets a digital employee they never have to think about. This will be a $50 B+ category. 13. The first "shadow agent" scandals are about to drop. Employees running personal agents on company infrastructure without telling anyone. Using company API keys. Agents accessing internal docs. IT departments have little visibility into this right now. Lots of opportunity to build companies here. Definitely a painkiller not a vitamin type of business. 14. Right now there are probably millions of agents running on autopilot that their creators forgot about. Still burning tokens. Still sending emails. Still scraping websites. Still costing money. The "find and kill your zombie agents" tool is a product that writes itself. 15. Companies are starting to hire based on someone's agent portfolio instead of their resume. "Show me 3 agents you built that are running right now." It's REALLY early but it's starting. 16. Your Slack archive is a product. Every company's internal Slack has thousands of messages explaining how they actually do things. The company that lets you point an agent at your Slack history and auto-generate SOPs and agents from it will be enormous. 17. We're watching the cost of intelligence fall faster than the cost of distribution. Which means distribution is now the expensive thing. 18. The most underrated asset a human can have in 2026: the ability to sit in a room with another human, make eye contact, and have a real conversation. As AI handles more of the transactional stuff, the humans who can do the relational stuff become disproportionately valuable. The soft skills people used to dismiss as fluffy are becoming the hard skills. The hard skills people spent decades acquiring are becoming the soft ones. 19. There are MANY huge companies to be built around the fact that most people's agents are running on their personal laptops which they also use to browse the internet, check email, and download random files. The attack surface is enormous. One compromised Chrome extension and your agent's API keys, customer data, and workflows are exposed. 20. There's a new type of burnout forming that doesn't have a name. It's not from working too hard. It's from context switching between human work and agent work 50 times a day. Reviewing agent output, correcting it, approving it, reviewing again. The mental load of supervising agents is different from the mental load of doing the work yourself. Some founders are telling me they were less tired when they did everything manually because at least the cognitive pattern was consistent. 21. The cheapest form of market research: search "[your industry] spreadsheet template" on Google. Whatever people are tracking manually is your product. 22. Half the YC companies pivoted within 8 weeks of demo day. Not because they failed. Because agents let them test 5 ideas in the time it used to take to test one. The concept of "committing to an idea" is dissolving. Serial pivoting is becoming the default because 1) AI lets you move fast 2) the world is moving fast. 23. The loneliest job in tech right now is being the only person at your company who understands what the agents are doing. You can't explain it to your boss. You can't hand it off to a colleague. If you leave, everything breaks. You've become a single point of failure for an entire automated system. That person needs a title, a team, and a backup plan. Most companies haven't figured this out yet. 24. Your browser history is the most valuable training data you own and you're giving it away for free. Every site you visit, every product you research, every competitor you study, every pricing page you screenshot. That behavioral data, structured and fed to an agent, would make it understand your business better than any onboarding call. The company that lets you turn your browser history into agent context builds something nobody can replicate. 25. Everyone is building AI wrappers. Nobody is building AI unwrappers. The tool that takes an AI-generated document and tells you which parts a human wrote and which parts were generated. 26. Stripe just became the most important company in the agent economy and they barely had to do anything. Every agent that sells something needs Stripe. Every agent that buys something needs Stripe. They're the payment rail for the entire agentic internet by default. 27. The most undervalued API in the world right now is the US Postal Service address verification API. It's practically free. Every local business lead gen agent needs it. Every real estate agent needs it. Every direct mail agent needs it. Boring government infrastructure is quietly becoming the backbone of agent-native businesses. 28. The concept of "business hours" is for humans. Your agent closed a deal in Tokyo at 3am, processed the payment, sent the onboarding email, and updated the CRM before your alarm went off. 29. What happens when agents start recommending other agents? Your research agent finds that a competitor's sales agent is better and suggests you switch. Agent referral networks are forming organically. The first agent affiliate program is probably 6 months away. 30. Cal dotcom closed their source code. That's the canary. When open source companies start closing up, it means agents were cloning their product too easily. Every open source company is quietly asking the same question right now. 31. "AI for pet groomers" sounds like a joke and that's exactly why it will work. 150,000 of them in America. Zero tech. All scheduling by phone or IG DMs. The joke ideas always win. 32. The thing that will seem most obvious in hindsight: we spent 2025-2026 arguing about which model is best while the entire value was in the orchestration layer. The model is the CPU. Nobody buys a computer based on the CPU anymore. They buy it based on what they can do with it. Makes so much sense in hindsight. What else will be obvious in hindsight? I'll share more notes soon. I can't sleep with all that's going on. Maybe you too. What an incredible time to be building.

Someone added himself into iconic Game of Thrones moments using AI. Pretty funny/worth a watch Credits: aihaslogic (Reddit)

Then I asked it convert it into a video and gave it this prompt. "Make a realistic live sports broadcast video of a Morocco vs Brazil crowd shot. Keep the exact woman, outfit, crowd, and stadium mood. Keep the top broadcast graphic completely fixed and unchanged: no text morphing, no number changes, no flicker, no logo warping. Shot 1: a broadcast telephoto camera slowly zooms in on the woman with slight realistic stadium-camera shake. She looks toward the big stadium screen after noticing herself on it. We do not see the screen, only her reaction. Her expression changes from focused surprise to a subtle cold attractive expression, not a smile. Shot 2: cut to a tighter extreme close-up from a slightly different broadcast angle. She keeps the same cool, self-aware expression with very subtle eye and lip movement. Keep nearby spectators natural and slightly out of focus, still looking in the same general direction. Preserve the live TV realism, shallow depth of field, and authentic broadcast look." That's it. You don't need Gemini or any other model for it.

Then I took a screenshot from one of the frames, and gave it to Kling using this prompt: "Create a hyper-realistic live sports broadcast screenshot-style image based on the attached reference broadcast frame. First, analyze the attached image and use it as an inspiration reference for the main character. But the new girl should be wearing a Brazil tshirt. Then analyze the attached stadium broadcast reference image and near her should be people wearing different team tshirts. Understand language, framing style, lens behavior, crowd composition, focus falloff, and live-TV realism. Scene: a Morocco vs Brazil football match in a packed stadium. The main character is a young woman seated in the spectator stands, captured by a professional long-zoom stadium broadcast camera, exactly like those live crowd-reaction shots shown on the giant stadium screen and on TV. She is the clear focus." This is the image it gave me:

I tried the viral AI broadcast trend using Kling AI. This is the exact workflow I used (it only involves 3 steps):

8. Instagram in 2005

7. Zoom in 2013

For fun, I asked ChatGPT image 2.0 what some big apps today would look like in a different era. I asked it to think about: > the interface we'd be using at that point > the hardware limitations of that time > the communication style > typography > psychology of users Here’s what it came up with: 1. TikTok in 2009