A Product Guy. Leading AI at @monacoGTM, previously built @zedaIo.

San Francisco, CA
Joined April 2014
Looking to talk to sales folks who are using Claude/Grok Bot/Codex or any other AI agent workflow to create and close pipeline?
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Prashant Mahajan retweeted
Our Agent Platform replaces point solutions and solidifies Monaco as the only sales platform you’ll ever need. It allows you to create agents that can work on your instance 24/7, alongside the ones that we can ship to your instance on day 1. There is no limit with what you can do with these agents and we are here to help you craft best agents that would increase your ROI of Monaco. I’m excited to see the agents our customers will build! Shoutout to @mihail_eric, @prashantx31, Yunshu Guo Adam Tazi, Kulvinder Lotay for being the masterminds of our agent platform. Such a great work 🙏. PS: Our internal agent hackathon produced tens of agents, and some of them are shipping in today’s release.
Today Monaco is launching Agent Matrix. Monaco unleashes countless agents working together, goal seeking, with one outcome in mind: accelerate revenue growth. If you don’t have an army of agents working 24/7 to accelerate revenue growth, you’re living in the past. Apply for early access now.
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It has been fun building Agent platform at @MonacoGTM. Would love to have more feedback.
Today Monaco is launching Agent Matrix. Monaco unleashes countless agents working together, goal seeking, with one outcome in mind: accelerate revenue growth. If you don’t have an army of agents working 24/7 to accelerate revenue growth, you’re living in the past. Apply for early access now.
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Prashant Mahajan retweeted
100+ of SF’s most cracked GTM engineers follow everyone at gtmstack.fyi who did i miss?
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We are starting a new trend.
well done @MonacoGTM excited to see what trend this kicks off in sf
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Prashant Mahajan retweeted
Replying to @prashantx31
well deserved dude!
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From builder to seller. I have done complete circle.
100+ of SF’s most cracked GTM engineers follow everyone at gtmstack.fyi who did i miss?
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No one is even using or talking about Instinct. That lasted shorter than I expected.
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2 weeks from today is the greatest Sales Leader event of all time. The best VPs of Sales and CROs in the world all at the Julia Morgan Ballroom in SF competing for $100,000 in the no buy in Monaco Invitational poker tournament. The expense for the event itself is significantly higher than the cash prize - the best venue in San Francisco, a food and beverage program The White House would envy, celebrity guests, entertainment, and so much more. Attendance reserved for Monaco customers and prospects.
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Prashant Mahajan retweeted
There is a mountain of unworn clothes in the driest desert on earth, large enough to be photographed from space. It grows by 39,000 tons a year and almost none of it will ever rot. The Atacama, in northern Chile, is a place where it may not rain for a decade. On its edge is a duty-free port called Iquique. Every year about 59,000 tons of clothing arrives there from Europe, America and Asia. It is last season's stock that never sold, and the bags people leave at charity shops. Dealers pick through it for anything they can resell across South America. Two thirds of it is worthless. Nobody will pay to ship it back out, so lorries drive it into the desert at night and tip it. The local landfill refuses to take it. The reason given is that the clothing does not biodegrade and is full of chemicals. Most of it is polyester, which is plastic, and in a place with no rain and no soil life it will lie there for centuries. Some of it is set alight, and the smoke drifts over a town of 100,000 people. In 2025 a Chilean court ruled that the dumps had done serious damage to the land. For most of history this could not have happened. Clothes were wool, linen and leather. They were worn out, handed down and patched, and at the very end a rag merchant paid for the scraps. In Yorkshire, from 1813, old woollens were shredded and spun into new cloth. Anything left went on the fields, where wool breaks down in months and feeds the grass. Nobody ever had to find a desert for worn-out wool. We invented a fabric that cannot die, and then we started making it to be thrown away.
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We will be there!
I'm speaking at @vercel Ship tomorrow. What I'll cover: - how we build GTM domain expertise into our agent harness - strategies for effective collaboration between subject matter experts and engineers - who's flying the @MonacoGTM airplane Come say hi! vercel.com/ship
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And you are bearish?
JUST IN: Palantir CTO reveals many AI researchers have started smoking cigarettes to demonstrate their confidence that AI will cure cancer.
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This was the pitch of @Zedaio
Giving everyone access to the best AI models is just the start. At Ramp, an account manager used Glass to automate capturing feature requests from customer calls. We went from logging about 300 by hand each month to capturing 20,000. Glass also prioritizes those requests and emails customers when something they asked for ships. We've sent over 5,000 of those emails. We built Glass so one person’s better way of working could help the whole company. Today, we’re opening it up to others.
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Prashant Mahajan retweeted
Replying to @MonacoGTM
@MonacoGTM just hosted its first agents hackathon. For 4 hours on a Friday, our engineering and GTM teams collaborated to ship 23 sales-focused agentic workflows in our product. I have always believed that building a world-class AI sales platform requires not just world-class GTM or world-class engineering in isolation but bringing both sides to the same table to draw out the best in each other. If building vertical AI platforms sounds like your jam, we're hiring! DM me!
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Prashant Mahajan retweeted
Assorted things I've been mulling over regarding agents in the economy: • Companies are in some sense the original superintelligence. It's often the case that they can use their amortized cognitive surplus to advance their interests against those of certain consumers: relative to the optimization capacity of companies, consumers can be inattentive, underinformed, irrational, etc. (Think, say, of some of the classic insurance upsells at the end of a booking process, which is typically priced substantially above what a regular policy would cost.) Herbert Simon introduced the idea of bounded rationality, and firms often end up benefiting from it. Thanks to personal agents, we will probably get somewhat more rational in how we engage with companies. • How exactly will outcomes change? Well, certain kinds of price discrimination will work less well (how do coupons work if every agent hunts fastidiously for them?), and certain kinds of customer cross-subsidy will change (today, people who forget to cancel subscriptions subsidize those who don't). Taken across the economy as a whole, I'm not sure what the incidence of all of this will be. • In corporate strategy, people have long debated the relative importance of distribution and product quality. Perhaps you've made something better, but does anyone know about it? Won't people just continue to buy the ACME Corp Mousetraps? Personal agents will, I think, act as a kind of structural subsidy for product quality. How would markets look different if individuals always spent at least 10 hours researching their purchases? On the margin, focusing on making a product better is, I think, going to become a more effective strategy for companies. This is good! • It true, a corollary is that information about product quality will become more important and impactful. Today, most people have very limited ability to aggregate and integrate such data, but agents will have insatiable thirst for such signals. (It's often said that data is becoming more valuable because it helps in the training of models. That's obviously true, but I think there's a secondary way in which it's more valuable simply as a complement to cheaper intelligence.) • A big question is whether agents will increase superstar effects (rational agents all settle on the same product) or increase dispersion (because everyone has slightly different tastes and preferences, which agents are good at eliciting, finally overcoming the artificial clustering we've been subjected to). • Many internet companies have monetized demand routing, which is in turn often predicated on short attention spans. "I'll click on the first thing I see." This has led to some amount of inefficiency, as companies try to propitiate capricious ranking algorithms and incur various placement fees. It's not all deadweight loss (willingness to pay is itself a kind of signal, which is valuable to buyers), but it's not great. How will the nature and value of this routing change in a world of personal agents? I don't know the answer, but I think that the effects might be pretty big. • Much of what I'm writing hinges on the assumption that personal agents will be on the consumer's side. I suspect that that will be the winning strategy, but whether it's true, and what it means to be true, involves a lot of other questions. Taken as a whole, the market is a massively parallelized, decentralized, and highly imperfect value attribution machine, and, taking stock of all of the effects, it seems to me that the quality point may well be the biggest: that agents will change the nature of the backpropagation such that the rewards for better products increase. Maybe this is too optimistic, but I suspect (and hope) that companies that make things that they're proud of will feel that the universe is a little more partisan in their favor.
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Prashant Mahajan retweeted
Introducing ChatGPT for Dishwashing GPT-6 achieves state-of-the-art results on dishwashing benchmarks for long-running jobs and difficult stains. The Navier–Stokes Millennium Prize Problem is a $1 million challenge about whether the equations describing fluid motion can break down. In this video, I accidentally found a counter-example while trying to optimize my dishwasher. But in reality, OpenAI used 10,000 AI agents to find a proof in 88 hours: openai.com/index/navier-stok… Parody of the original GPT-6 Astra ad @OpenAI #ChatGPT_Partner #chatgpt Credits: Written and Directed by Joma Co-Writer - Henry Connor Coan IV @coan_henry Production by Dauntlus Studios @dauntlus.studios Producer/Co-Director - Marcus Liew @dauntlus Camera Operator - Amos Lee @amoselijahlee Art Director - Alethea Soo @aletheasoo Art Assistant - Alicia Lim @aliciatkl_ Assistant Editor - GPT-6 Astra Music: Tensions Run High by Soundridemusic youtube.com/watch?v=Ly9H63SL…
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Please stop saying I killed <some big company>
I just KILLED Palantir! Foundry lets you build your own company ontology. It uses @helixdb for the s3-backed ontology and @duckdb for transforming and analysing the data. It's open source so check it out: github.com/HelixDB/helix-fou…
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Reminder Google is launching Argon this month, with 1M token output. Excite to see X timeline.
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Human perspective shifts when you realize we are not living in year 2026, but around 12026 (the first human settlement). It took this much time for humanity to build AI.
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The First Brain: ~521 to 540 Million Years Ago And then the First Cell: ~3.8 Billion Years Ago
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