Aswin Shibu 🚀

5 years at @MixRank ✅50% YoY Growth over the last 4 years ✅40+ teammates across 14 countries ✅Profitable, healthy business ✅4 out of 5 Top Sales Platforms use us ✅3/5 Top Recruit solutions ✅ 2 world's best data-driven VCs use us today. ..and we're just getting started!

@ow Ah, cool insight! I was originally thinking of playing while my wife watches something on the TV. But sounds like Steam Deck is really for hardcore gamers who’ll game at all costs.

@helloaswin I have a Steam Deck too. It’s great but only really if you travel A LOT. I used to, but I don’t really use it much when I’m not travelling

picked up a ps5 on Black Friday after only having an Xbox since launch… holy crap i had no idea how much better the games are. microsoft really fumbled it.

Incroyable!

@ttunguz Haha, maybe the Agentic Web, if that’s not too cliche.

@helloaswin We need a rebrand! Maybe web AIr?

11 Predictions for 2026 Every year I make a list of predictions & score last year’s predictions. 2025 was a good year : I scored 7.85 out of 10. Here are my predictions for 2026 : 1. Businesses pay more for AI agents than people for the first time. This has already happened with consumers. Waymo rides cost 31% more than Uber on average, yet demand keeps growing. 1 Riders prefer the safety & reliability of autonomous vehicles. For rote business tasks, agents will command a similar premium as companies factor in onboarding, recruiting, training, & management costs. 2. 2026 becomes a record year for liquidity. SpaceX, OpenAI, Anthropic, Stripe, & Databricks IPO, with SpaceX & OpenAI ranking among the ten largest offerings ever. The pent-up demand from 4+ years of drought finally breaks. Fear of disruption by fast-growing AI systems drives defensive acquisitions exceeding $25b as incumbents buy rather than build. 3. Vector databases resurge as essential infrastructure in the AI stack. Multimodal models & world/state-space models demand new data architectures. Vector databases grow revenue explosively as they become the connective tissue between foundation models & enterprise data. 4. AI models execute tasks autonomously for longer than a workday. According to METR, AI task duration doubles every 7 months. 2 Current frontier models reliably complete tasks taking people about an hour. Extrapolating this trend, by late 2026, AI agents will autonomously execute 8+ hour workstreams, fundamentally changing how companies staff projects. 5. AI budgets receive scrutiny for the first time. Buying committees & boards push back on AI spend. Small language models & open-source alternatives rise in popularity as research labs determine how to specialize them for particular tasks, achieving state-of-the-art performance at a fraction of the cost. Developers prefer them for 10x cost reductions. 6. Google distances itself from competitors via breadth in AI. No other company achieves breakthroughs across as many domains : frontier models, on-device inference, video generation, open-source weights, & search integration. Google sets the pace, forcing OpenAI, Anthropic, & xAI to specialize in response. The era of every lab competing on every frontier ends. 7. Agent observability becomes the most competitive layer of the inference stack. Engineering observability, security observability, & data observability fuse into a single discipline. Agents require unified visibility across code execution, threat detection, & data lineage. This marks the beginning of the confluence I predicted in 2025 : the three observability spaces finally converge. 8. 30% of international payments are issued via stablecoin by December. The efficiency gains in cross-border settlement are too large to ignore. As regulatory clarity improves in major markets, stablecoins move from the periphery of crypto to the core of global trade finance, displacing traditional SWIFT rails for a significant portion of B2B volume. 9. Agent data access patterns stress & break existing databases. Agents issue at least an order of magnitude more queries to databases & data lakes than people ever did. This surge in concurrency & throughput requirements forces a redesign of the overall architecture for both transactional & analytical databases to handle the relentless demand of autonomous systems. 10. The data center buildout reaches 3.5% of US GDP in 2026. The scale of investment mirrors the historical expansion of the railroads. The only factor that slows overall building is perceived risk within the credit market, particularly in the private credit market. The massive growth in that asset class suddenly shows strains of increasing default rates, creating a potential bottleneck for the most capital-intensive infrastructure projects. 11. The web flips to agent-first design. Most developer documentation & many websites become agent-first rather than people-first. This shift occurs because many purchasing decisions are now informed first through agentic research. Consequently, the front door needs to be designed for robots, while the side door caters to people.

The CWC had me all hyped up for Xabi-ball. And everything looked promising up until the Atletico game. But it’s been a disaster since. What changed? 🤔

@eldsjal Been reading a lot of Brandon Sanderson’s series but picked up a short book by him, Tress of the Emerald Sea is a short and lovely delight.

The holiday season is a good time to pick up a new book. This year, I ended up borrowing a few recs from friends after seeing their Wrapped stories. I've been working my way through those lists but curious what books everyone is listening to right now?

@jeffzwang Congrats on the launch!

We told the world we built SOTA people search, and 80%+ of people are just searching their own name 🤦

@sojoodi Nice! If you’re looking for judges, I’d love to contribute too!

We’re hosting our first Toronto hackathon in January: Build for Builders. Top AI + tech leaders will be judging, hanging around, and yes… hiring. If you’re a builder who ships, this one’s for you: luma.com/wxljxszx

@dwlz Oh yeah, I had always-on-display for all of 5 minutes before permanently turning it off. I haven't bought a new phone since my 13, and I'm seriously debating getting a foldable just for changing things up.

So, I finally did it. I upgraded my iPhone 12 Pro Max to the 17 Pro Max. Sad reflection, but after a few hours, the only thing that really struck me is that now the phone screen doesn’t turn off.

@kepano 4 hours to answer that question? 😁 Now I have to listen to it, haha.

in which I attempt to answer "why are you so crazy?"

@davidgan Was this a tool that pulled context from Slack and Docs? If so, can I ask if there’s someone who can help explain how we can set this up on our end too? Happy to compensate for the time! Thanks in advance!

Fortune wrote about something I've been building at Cursor! fortune.com/2025/12/08/cur…

@auren @vacanti Yup 💯. It makes sense to try and be resilient because the data is always going to be needed. All the takes from this episode sound pretty valuable!

counterintuitive take from @vacanti on web scraping: he used to stress about sites blocking scrapers. then realized: the harder sites make it to scrape, the MORE valuable scraping becomes. creates bigger a moat for companies that can do it. demand >> supply friction

@iandmacomber You shouldn't actually be using anyone else. Just use MixRank. :)

Took a call with a B2B enrichment vendor today. They asked how many employees we had and where we were located. Instant pass.

I haven't seen such effortless passing since Guti or the man himself, Xabi Alonso. Like this one: youtube.com/watch?v=YOA_wl…

@peer_rich @stripe We use Maple Billing to pull this info from Stripe. They have advanced MRR metrics and rev-rec stuff if you're interested but we weren't so we have basic stats.

man @stripe you are so funny hahah > be me > try to get accurate MRR exported out of stripe for over a year now > stripe's api doesnt give me MRR > only stripe sigma does > ok, signed up for stripe sigma > sigma gets me an accurate csv > however sigma doesnt send the data to postgres > decided to signing up for stripe data pipelines > requires a sales call > stripe uses super whacky UX for scheduling a call > anyway lets do it > books a call into the future > stripe SDR replies "this is more of a support question, let me cancel this call" > support doenst get back to me > sales call gets cancelled > back to square one @patrickc few questions: - why so hard to pull accurate MRR out of stripe? - why is your sales scheduling experience so bad? - why is your sales qualification so bad? (we're doing $6M ARR, your SDR should be excited to speak to us not disqualify and cancel the meeting)

@dwlz Oh yeah, that sucks. I think usage-based trials have worked for us in the past. 100 free credits, and then a CC beyond that.

@helloaswin It's only a 3 day free trial, but we do have inference costs. I think a lot of users' cards just aren't valid. E.g., Stripe will happily accept them on trial start and only finds they aren't valid after an attempted capture. Many debit cards with $0 balances for example.

This is a normal day for us. Look at how many failed payments there are! I understand why products do $1 test payments now. We're moving to having a free version with a paywall after you hit limits. It's just not worth the hassle otherwise. Bye bye free trial.

@neilsuperduper How many B parameter model can you run? 128GB RAM must’ve cost a pretty penny.

yeah if you only work from an office with a high speed connection and only use frontier models for coding / conversational usecases this is valid but a very narrow view of offline models. used offline models constantly on my last trip (spotty internet connection) & use them all day every day in superwhisper. 128gb m4 mbp btw

@neilsuperduper lol, was this place good?

benihana toronto permanently closed