
🇦🇺 🇬🇧. Partner at @rampersand_fund. Prev @angularventures, Algo trader/founder. Dad. Husband. Knicks fan, globe wanderer, foodie, DMs open.
Sydney, London
Joined October 2009
- Tweets7.6K
- Following5.3K
- Followers1.4K
- Likes29.6K
Making an ad is the easy part now. Knowing which one to make next is the hard part. That's the new ✂️ Cuttable: ads that learn. Announcing their $20M Series A today. Proud to have backed Sam (@samkroon), Jack, and Ed Ring since day zero, and in every round since.
cuttable.com
Andrew Poesaste retweeted
on track
AI predictions for next 6-9 months
-> Anthropic/ OAI fail to ban OSS in the US
-> Anthropic/ OAI continue to innovate product but stall on fundamental tech breakthroughs
-> SOTA Gemini 4 launches at 10x lower cost
-> Elon open sources Grok
-> Anthropic/ OAI ARR growth stalls as enterprises move from tokenmaxxing to rational token consumption/ OSS
-> slow realization in public markets that AI may not replace human labor in next 1-3 years/ has not had a fundamental tech breakthrough in over a year/ lacks ROI/ AI hyper and lab spend not durable
-> moonboy VCs/ hedge funds/ softbank continue to fund Anthropic/ OAI equity raises in private markets as public markets for them are now fully closed
-> CXMT, YMTC announce capacity expansions significantly above market expectations
-> hypers deliver good q326 results on first look but fail to show meaningful AI ROI, guide to "significant capex expansion in fy27"
-> broad realization in public markets the AI dream we got sold on is not anywhere close to realization
-> 10yr hits >5%
-> hyper bonds reprice >10%, CDS hit 3x current levels, and AI credit market dries up as market realizes GPU ABF was not a good idea
-> hyper equities reprice 30-50% lower
-> ORCL falls below $30 as rumors of bailout make the round
-> market realizes memory is cyclical and LTAs won't hold
-> 50% of korean traders get wiped within a week
-> hypers cut fy27 capex
-> semis reprice >80% lower
-> fed cuts >150bps to avoid recession
This is one of the most important results in AI, period.
TLDR: neural networks are not tangled knots (polysemanticity is wrong). You can study their own neurons directly, without first "unfolding" them with a second model. 90% of neurons in Qwen-32B have one job.
Nick Cammarata started OpenAI’s interpretability team and is at Goodfire now. He’s been studying how LLMs work for a decade.
The stakes for understanding and aligning model behavior are the highest it’s ever been. Models have achieved superhuman results in math, can break production software systems, and changes the nature of white collar work. This work may finally allow us to intentionally design LLMs and shape how they behave.
Its a long, phenomenal read.
interpretability might be the most important scientific problem in the world right now, as I don't think we can solve alignment if we don't know what we're building. I think I have good news about it. I co-authored early work in mechanistic interpretability at OpenAI and came away pessimistic, because neural networks appeared to fold into arbitrary tangled knots. years later, I started openai's first large-scale automated interpretability project, finding about 2% of neurons legible with the primitive tools we had
with modern agentic tools and a much closer look, the picture looks totally different. the vast majority in models up to trillions of parameters are legible, and their circuits beautiful. many famous examples of tangled neurons turned out to be misunderstood. The roadblocks I expected mostly aren't there. I now think ambitious interpretability will be solved by the time we need it most, and possibly quite soon, as automated scientists keep improving. it may be a bitter lesson for interpretability: the simple thing, at absurd scale, works
already-clean.goodfire.com/
Overqualified for the benchmark. Underqualified for an invite.
Introducing The Cheeky Pint Benchmark.
We made our intern watch every episode of Cheeky Pint to bring you this breakdown of pints drank by guests to the nearest sixth.
Congratulations to @elonmusk who is currently in the lead with three full pints of Guinness.
People are hyper-focused on the shallow agent use cases, but Noah is pointing at something way bigger: a complete reordering of the internet’s interface and social graph.
When you move from middleman ad platforms to weighted, agent-to-agent trust primitives running at the edge, the whole web interface collapses. No search boxes, no app fatigue.
Whether Instinct actually wins the space or gets crushed by compute costs is TBD, but the underlying graph primitive they're building is a massive deal.
Instinct Founder Noah Shinn on Meta's Muse:
"I think it's a great product. It's a different take.
Instinct is meant to be simple and very easily accessible, versus a new application and a new interface.
I just spend very little of my time thinking about competition.
You walk outside, you go to the nearby cafe, and you think about how many people in that cafe are actually using AI in the way they imagined they would, or the way they want to be using it. I would say very little.
It's still an open space."
Rebooting the Silicon Valley TV show would be such a lay up (exhibit 9456):
- faux acquihires
- cuck rounds
- P of Doom and Dario
- researcher draft and agency
- Huggingface hack
- Forgetting you are an investor in a portco
🔥 Incredible session at the @Sierra_Ventures CXO Summit, thanks for hosting @shomikghosh21
Andrew Feldman (CEO/Founder, Cerebras) + Sachin Katti (VP Compute Strategy & GPT-Infra, OpenAI) + @dylan522p Patel (King of compute, SemiAnalysis)
Three of the sharpest minds in compute unpacking what it actually takes to build medium term and be a great partner in the process. Food for thought for Australia.
Brilliant, a winning team brings different strengths :)
my first week at sequoia many years ago: i go to the kitchen to grab coffee. sir @michael_jmoritz is there pulling an espresso shot. i ask him about the machine and he teaches me how to pull my own. he then leaves the kitchen.
craft is everything.
a minute later, @dougleone walks in. he sees me steaming milk on my own and goes, "kais, we didn’t hire you to make friggin cappuccinos in the middle of the day. go call companies."
hustle is everything.
both were right! sequoia is a beautiful firm full of beautiful contradictions.
Peak 2026: a $230 keypad to drive your coding agents, and a website where you pray to Tibo for your usage limits back.
659,000 begs and counting. codex-resets.com/
How is AI actually changing how we build products?
@rampersand_fund's Product Counsel are surveying ANZ's top builders to find out. Product, eng, design, founders.
What's getting better? What's getting lost? Where do you draw the line? 10 mins:
productcounsel.com.au/the-bu…
Back in SF 🌉 in a week, 21–24 Sept ✈️
Several of @rampersand_fund 's fastest-growing companies are moving to the Bay.
US seed investors: I'd love to compare notes on what's coming out of ANZ.
Aussies and Kiwis in SF: let's catch up.
DMs open.
Tactical consumer growth ideas
We grew from ~0 to $500M ARR, adding $250M last year alone while being EBITDA profitable.
1,300-word post on every growth tactic that worked for us:
1. What got us from 0-$400M ARR in the US works in every country.
2. Retention and Monetisation Hacks.
3. Localization > Translation.
4. Experiment with $1M internal seed checks.
5. Pivoting to only AI content production unlocked 100% ARR growth.
Pocket FM is like Netflix for audio-only dramas, with our own pool of one-person studios.
1. Acquisition Playbook for 0-$10M ARR in any country in 6 months
We run a 90 sec video trailer of an audio drama as an Ad and ask users to download the app if they're interested in the rest of the story.
Our core insight after spending >$100M on acquisition is: If the clickthrough rate (CTR) for an ad goes from 2% to 2.25%, our customer acquisition cost (CAC) decreases by ~ 30%.
We remodelled our system around this insight and built an AI-first 2.25% CTR ad manufacturing machine that works in every country.
For every new country, we take our hit shows -> use LLMs to extract and most intriguing moments -> Write a 5-min script combining all the best parts. The first 60 seconds has to have a hook every 5 seconds and needs to end with a crazy cliffhanger to force a download mid-scroll.
If a marketing video is not hitting our benchmarks (2.5% CTR and 55% 3-second through-play), a creative director gets involved to change the hook or cliffhanger to get the numbers there.
AI lets us make 1,000 Ads per show, and in total we do ~17.5k Ads per month. When a business creating scales from 1k to 10k Ads, the normal thing is for CAC to skyrocket. But with what I just shared, we 7-8x'd our User Acquisition budget without increasing our CAC materially.
It took us 8 months to figure this out, but then the timeline from 0-$10M in every country got shorter and shorter:
US revenue grew to $25M in 19 months. (US is now 78% of total)
Germany to 21M in 11 months.
France to $10M in 3 months.
2. Retention and Monetisation Hacks.
We knew we wanted to create an audio entertainment platform, but there was no standard format. For the first 2-3 years, we tried 10 different formats before landing on the winner.
After we got it right with audio drama (8-12min chapters, written for mobile fiction, serialized, episodes have strong hooks and end on cliffhangers), avg daily streaming time went from ~25mins to 150+.
Audio drama made us realize that Pocket FM was creating a whole new medium. There was no playbook for anything that we were doing. Everything had to be thought & built from scratch.
This is what we did for each major bullet:
- Monetization: Users have some free daily minutes to listen; then it's pay per episode. We also added the option for users to unlock episodes by watching ads, which is doing extremely well. Ads scaled from zero to a ~$90M run rate in 12 months.
- Engagement & production: You don't become obsessed with an app you open once a week. To have users engage daily, we make the next episode free every day. Also helps them build the habit.
- Discovery. Huge problem because people consuming Pocket FM enter the app, tap the show, and lock the screen. We fixed it by doing "playlists" of episodes. Once users's free minutes on a show are done, we ask users if they want to pay. If they say no, we play a new show, one where they haven't used their free mins. And we stitch episodes of different shows together that way, creating natural discovery.
3. Localization > translation.
78% of our revenue is still concentrated in the US. Localisation is fixing this: You might write a show for a Spanish audience where language, jokes, folklore, have a certain flavor; if you merely translate the show for, say, a Norwegian audience, that color is lost and hurts the show in the Norway. Listeners would relate more if the show was written by a Norwegian.
That's why, instead of translating, we localize shows to different regions. We use AI to take the spine of stories and adapt their whole cultural layer to the other country.
The results: a US show that was localized for a German audience had 50% higher retention than the translated version.
Localization + our user acquisition playbook led to:
- $10M+ ARR in France within 3 months
- $21M+ ARR in Germany within 11 months.
And this expands writers' addressable market.
We get messages of writers thrilled to have revenue coming from the US, India, EU, LatAm, without them doing much incremental work.
4. Experiment.
We give $1M checks to new internal initiatives, and the team has 12-18 months to prove their thesis. If they prove it, we double down.
This is how Pocket Saga came about, our AI video microdrama app. It's an AI video equivalent of Pocket FM. Same shows and structure, but as a vertical 2-min mobile video series.
We launched it two months ago and it's at ~$15M ARR.
Pocket's broader thesis is to help creators tell their stories to as many people as possible. Start with audio drama -> multiple languages or localize to diff countries -> microdrama -> more formats like movies, TV shows, and games.
Best of all is that writers get revenue streams not only from countries they wouldn't have tapped into, but also from formats they wouldn't have thought possible.
5. Pivoting to only AI content production unlocked 100% ARR growth.
In mid-2024, we pivoted to only AI content production.
Our growth took a very direct hit. Pocket was already at $200M ARR, growing 50% YoY, and we flatlined for a whole semester.
Six months later, the business exploded.
After the switch, we went from ~25k hours of content produced per year to over 2.5M hours, which are also higher quality. Because AI orchestrates the writing and more data is fed into it, more blockbusters come out.
Over 90 titles have $1M+ in lifetime earnings and 13 crossed $10M.
Quality control is done with LLM as a judge, and LLMs are quite tough.
Results are very encouraging:
- 12-month revenue retention went from 44% to 76%.
- In the past year, we added $250M in net new ARR.
__________________________________
Pocket Entertainment (Pocket FM + Pocket Saga) has become the largest AI entertainment platform.
We have the largest storytelling catalog with 770,000 titles, 550k creators, and 5.5B hours of playtime with minute by minute retention & engagement data. We are using all of this data to improve every aspect of our business.
Our Bet: In the next 3 years we will be able to produce Naruto-like series for $1000.
Netflix has to spend $17B to find 100 Blockbusters per year.
What happens when you can produce 1M high quality shows for $1B?
The streaming wars caused a $300B reallocation of market cap.
The AI entertainment wars may be a $1T+ reshuffling of market cap.
We are at a unique spot. Unlike other AI creator tools like Runway or Midjourney, we own both the supply and demand side of AI content.
We've attracted over 550,000 writers who are producing an annualized 2.5M hours of content every year. This pairs with 137B+ minutes streamed.
Because of this, growth is accelerating as we scale further.
We have multiple S-curves inflecting at the same time:
- AI produces better and more ads -> scale faster in new countries
- Writers + AI produce more shows -> more blockbusters
- Localisation -> more reach per blockbuster
- Audio to video format expansion -> larger TAM -> more creators
Every aspect of our business is designed to improve another, and everything is aligned so that the number of blockbusters continues to rise.
If you're interested in building at the intersection of ai, tech and entertainment, DM me.
I dropped out of a PhD in AI safety partially for the opposite reason. I didn’t believe AI existential risk was as important as the doomers think.
My biggest pet peeve is that no one can really provide tangible pathways to why it matters.
During my PhD, my research group (half of whom specialized in engineering risk analysis) did an internal study trying to assess concrete catastrophic AI scenarios.
The basic premise was that while we don’t know how AI will evolve, the ways in which humans perish are pretty consistent through history: the horsemen of the apocalypse. And institutions have obviously been very motivated to analyze concrete risks from things like plague, war, etc.
You can do a decent risk model by asking how a super-intelligent AI can perturb each of those models.
The result: most of the issues (eg cyber-risk) are akin to what economists call structural unemployment - big problems but ultimately resolvable in the long run and not a dealbreaker.
The only real concerning issue was bio-risk and it feels like the intervention points there lie more with bio than with AI as a whole (although a holistic approach is needed).
In trading, this is a dark variant of a joke “Bermuda trade”: you take the other side, and if you’re right, you get paid; if you’re wrong, you now live in Bermuda.
Except in this case, if you’re wrong, humanity goes extinct.


























