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Anish Acharya
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Anish Acharya
@illscience
🦞AI Apps investing @ A16Z; A1111; Boards of Krea, Deel, Clutch, Titan, Arc Boats, Untitled, Happy Robot + more; If you’re not at the table, you’re on the menu
San Francisco Entrou em Mart 2009
2.6K Seguindo27.9K Seguidores
in 2021, I backed @arcboats at seed because Mitch and Ryan, two of the best engineers I knew from Credit Karma and SpaceX, were building the "Tesla of Boats."
they saw that electric wasn't just better, it was 10x better. no maintenance, cheaper, faster, access to protected waters. five years later they've scaled that insight across commercial maritime.: tugs, ferries, defense vessels.
@dontmitch is the kind of founder who sees what an industry needs a decade before the industry does. Congrats on the Series C!
Arc@ArcBoats
Arc has secured $50M in Series C funding to scale electric tugs, ferries, and defense vessels. Our first ship-assist tug hits the water this year, with a second already under construction. Ports are just the start. Thanks to our partners in this round. arcboats.com/blog/arc-boats…
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@buccocapital Bucco you've been on a rampage lately and I'm here for it man.
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“It organizes your files”
“It prioritizes your emails”
“It tells you insights about your calendar”
These are not real things. They are not making you more productive. It is making you an idiot
Yes, AI is great. But this is fake productivity. This is dumb. You are being dumb
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disagree, there are a few obvious areas where this falls apart:
- every product that touches on the uncomfortable aspects of human nature (sexuality / persuasion / disagreement) .. look at the challenges that OAI has had launching "adult mode" .. everything in companion etc.
- categories where the products exist to support human exploration of tradeoffs; figma is as much of a thinking tool as a making tool
- categories where the value is in human coordination / networks (AGI doesn't trivially overcome network effects)
- antifragility of startups broadly vs scale advantages of emerging incumbents .. startups often benefit from tail risk
finally - a venture fund who I will not name missed the entire early internet era because they thought google would "win the web" ... don't make this mistake!!
Yuchen Jin@Yuchenj_UW
Some people at frontier AI labs told me they believe startups are over. OpenAI, Anthropic, Google, xAI will absorb every industry as AGI nears. Coding today, science, medicine, and finance next. Then everything else. If they’re right, that’s a pretty boring end of the world.
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@illscience Yes.
Betting on more free time for everyone due to agents doing the work - community and 'live' will be 10x more valuable.
Btw, this concept reminds me of TLV so much it's uncanny.
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norman rockwell energy here -
automate the busy work and people have bandwidth for what actually matters - spontaneous community, living the way they want to live
essentially everything promised by hippie collectivism but delivered with the hot knife of market economies + technology + human ingenuity
everyone's focused on what AI takes away, this is what it gives back ..
signüll@signulll
what adam neumann is doing now is such an obviously good idea. most of american life unless scheduled is super isolationist so you rarely get those spontaneous interactions with ppl.. this sorta flips that around right at the point of where ppl spend majority of their lives. anyway, it’s super duper interesting to see the wework model applied to residential.
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Anish Acharya retweetou
We don’t usually share much of our playbook, but made an exception here.
Went deep on how Deel scaled globally - especially our M&A strategy.
Excited to celebrate 7 years and everything our team has built.
Couldn’t have done it without @shuooo ❤️
Molly O’Shea@MollySOShea
BREAKING: @deel Hits $1.4B+ ARR Co-founded by CEO Alex Bouaziz (@Bouazizalex) & CRO Shuo Wang (@shuooo), Alex shares their hypergrowth playbook.. Founded in 2019, at only 7 years old: - Deel has scaled to $1.4B+ ARR - Reached a $17.3B valuation - 40K+ customers across 150+ countries - 3+ years of being profitable Deel has rapidly become the #1 platform for hiring & paying employees worldwide. We discuss: • Scaling Deel to $1.4B+ ARR • Serving 40K+ companies across 150+ countries • Deel’s 10+ acquisition M&A strategy • Building a profitable hypergrowth SaaS company • The future of global hiring & distributed teams • How AI agents will transform the workforce Recent Financing: Oct 2025, Deel announced a $300 million Series E funding round, valuing the company at $17.3 billion co-led by Ribbit Capital (@RibbitCapital) as a new investor, alongside long-time partners Andreessen Horowitz (@a16z) & Coatue Management (@coatuemgmt). This was filmed in London February 12, 2026 𝐓𝐈𝐌𝐄𝐒𝐓𝐀𝐌𝐏𝐒 (00:00) Alex Bouaziz, Co-Founder & CEO at Deel (02:05) Working with co-founder & CRO Shuo Wang (03:54) What Deel actually does (05:05) Biggest customers (05:54) $17B valuation and latest funding round (06:35) How Deel approaches fundraising (07:50) Hitting $100M ARR and early growth (09:25) Why raise money if you are already profitable? (10:35) Inside the latest funding round (12:03) Why payroll is a huge global opportunity (14:21) How Deel expanded its product stack (15:21) The challenges of hiring globally (16:18) Running a 7,000 person fully remote company (18:29) Tips for building remote teams (19:50) Why Deel went global from day one (22:47) How AI is changing hiring (25:00) Deel’s moat in an AI world (26:19) A question from Micky Malka (26:57) From airlines to oil and gas: who uses Deel (27:58) M&A strategy and integration playbook (34:33) Biggest mistakes companies make with acquisitions (35:56) How to retain founders after acquisitions (36:34) Deel's new CFO (39:09) What it takes to be IPO ready (40:29) How AI could affect Deel’s future (42:55) The "Dubai founder controversy" (46:00) Leading in a competitive market (50:47) The biggest misconception about Deel (53:27) The right people around you (56:51) The "default optimism" (58:33) What’s next for Deel (01:01:05) The future of autonomous agents (01:03:35) Biggest lessons from Shuo (01:06:34) What makes a great salesperson (01:08:32) Partnering with Arsenal
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@garrytan Youtube worked cause creators made $$$ out of it + Youtube handled distribution.
who is doing this for software?
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@dani_avila7 @garrytan Thanks Daniel I agree .. our lives are already infinitely better than 100 years ago and will be even more so in the near future.
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@garrytan I really like the last point, I also tend to take an optimistic view of what AI can do for human quality of life in the sense of reducing time spent on tasks.
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software's youtube moment, luxury (expensive!) apps, and why the moral panic around coding agents is silly...
notes on my chat with @GuillaumeMbh
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Notes for pre-AI companies making the transition:
- The goal is to be the point of economic diffusion between model progress and customer value. That means if the models get 3x better your customer receives 3x+ value.
- Models are making uneven progress across domains ("jagged intelligence") so you want to represent your problem in the domain where models excel. Can you take your business problem and reframe it as code, math, or structured logic?
- The biggest mistake is trying to over-engineer around the models. Default to exposing them to more. Even techniques like context engineering will likely have a limited shelf life as context windows expand and model progress continues.
- The way you organize your company matters. Start from an extreme: instead of AI marginally improving individual productivity, put the model in charge of an entire business unit and have individuals handle exceptions and do the work models can't (i.e. take the customer out for a steak dinner). Start with something unglamorous and low-visibility and see how it performs.
- The product is likely going to split into two surfaces: a traditional UI that supports human interaction and workflows + a terminal-like surface that's self-modifying and handles ambiguous cross-functional tasks (yep .. openclaw for the enterprise).
- Your customer knows even less about these models than you do. You need to start guiding them toward the most ambitious version of their future. If you're in an industry that really values its employee base, paint a picture of AI allowing them to hire more and increase worker NPS — not hire fewer and improve the bottom line. Helping them be sufficiently ambitious will be as hard as aligning the technology with those ambitions.
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We wrote the first check into Quince and never shared our thesis publicly
At the time, D2C was radioactive and 'affordable luxury' sounded like an oxymoron. Today they raised at $10B. We couldn't be more excited.
Here's why we believed — and why we think it's still early!
8vc.com/resources/quin…
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glimpse into the post AGI workplace
the new division of labor is computers working with computers and humans working with humans
this is going to be the most pro-social technology we’ve ever created
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@illscience The world isn’t ready for the amount of telegram bot slop the normies are gonna ship
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openclaw in 2026 is what chatgpt was in 2022 - a viral glimpse into the very near future ..
Olivia Moore@omooretweets
🚨 The @a16z consumer AI Top 100 is back! For the sixth time, we ranked consumer AI websites and mobile apps by usage (monthly unique visits and MAUs). This edition, we changed the rules. Here's why - and what the new list says about where consumer AI is heading 👇
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@purepathwill Not sure - it seems like a very different audience than broad ChatGPT for now - but agree it would be hard for a bigger company to ship something like this given all the inevitable lawsuits, internal committees etc
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@illscience Would you agree that in many ways OpenClaw has done the same thing to OpenAI that OpenAI did to Google?
They've released something a company with much to lose would fear was too risky, and it turned out to be exactly what people wanted.
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I think the most underrated bit is communicating through messaging apps - it subtlety sets your expectations that it can do whatever a person can do
And, more discussed, the self modifying nature (adding skills, integrated coding agent etc)
Finally the inverted context model of being on your laptop - it can see all your stuff by default instead of being drip fed context
What do you think @signulll ?
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@illscience what do you think was the key reason why openclaw actually resonated?
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@arshdilbagi Super thoughtful notes here - I’m a big fan of the product and agree with the core thesis here.
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The hard part about LLM failures is that their outputs rarely look like failures.
The demo “works.”
The output sounds coherent.
The user actively uses the product.
And your dashboard looks normal.
Meanwhile, the system can be wrong, unsafe, or quietly driving up token spend. And you won’t notice until the damage adds up.
Prompts often serve as business logic (policies, safety, and product context). But many teams ship them without the basics, such as versioning, reviewable changes, end-to-end traces, and eval gates.
In production, it doesn’t crash. It degrades via wrong answers, policy misses, and surprise spending.
No crash. No error. No alert.
I cover this exact issue in my @Stanford CS 224G guest lecture on AI Observability and Evaluations.
Here are the core ideas:
• If you only log the final output, you’re guessing. Full traces show where it broke.
• Evals are feedback loops. Use clear pass/fail criteria tied to outcomes.
• Run evals continuously on production traces and don’t wait for support tickets.
The moat isn’t prompt cleverness. It’s a measured improvement.
Full lecture + blog below 👇
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Anish Acharya retweetou
🚨 The @a16z consumer AI Top 100 is back!
For the sixth time, we ranked consumer AI websites and mobile apps by usage (monthly unique visits and MAUs).
This edition, we changed the rules. Here's why - and what the new list says about where consumer AI is heading 👇
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