CEO at https://xitter.cf/t.co/AKHxUDls4a Autonomous SMBs ~ founder/ceo jour (acq. $20m @avec_alan) investments: https://xitter.cf/t.co/iyEfuZEWeZ

Joined October 2008
Today, we’re launching Beside out of stealth with $32M from @IndexVentures & @eqtventures (+ many great investors/angels) to build the conversation layer for AI. 20k+ individuals and 600+ businesses now run their day through Beside: we answer the phone, text messages, take notes & update your tools. We began by rebuilding the Phone & Messages app on iOS We’re now launching with macOS & Android. Read our story here: fortune.com/2025/11/11/besid…
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Maxime Germain retweeted
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/
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AI adoption will create the biggest move away from interfaces because The Best Interface is No Interface Interfaces to complete a task was just a bandaid until better technology emerged Except for entertainment
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Maxime Germain retweeted
Dusting off this tweet from April because this gap in shared understanding of LLM capability is *widening*. It's now less "two groups of people speaking past each other" and more a sharp funnel. - Napkin math somewhere around 6B people (~75% of the population) have barely come in contact with LLMs at all. - Around 1-2B (~20%) are casual and infrequent users of free-tier ChatGPT-like products. This group sees derpy chatbots and treats them a bit like a better Google search, a writing aid, or etc. Maybe an agent tries to book you a flight. I have non-tech friends who (reasonably, imo) say they have not much use for it at all. Even many professionals outside of math&code are in this tier. For example, execs and many other functions spend a lot of their time talking to other people, so while they understand what is happening intellectually, it is still second-hand and a bit abstract. - Now we get to professional use of frontier-grade LLMs in math&code. Somewhere around 20M people (0.2%) see first-hand that large, complex projects that used to take them weeks/months can now be completed by agents with a prompt. Building apps, copying apps, translating apps, decompiling apps from binaries... This has all happened very quickly and recently - less than 1 year ago, I was writing code manually by hand, typing memorized computer code commands into a code editor character by character, occasionally pressing Tab to autocomplete a little chunk of code. - And finally we get to the ~5,000 people (~0.00006%) with access to frontier-grade systems internally. The external world has seen the preview. It looks like swarms of thousands of agents collaborating over weeks on software mega projects: minting zero days, running cyber attacks and defenses at machine speeds, discovering new science, advancing the frontier of mathematics. Things that would have taken top professionals in the industry years of work. Meanwhile, human review and comprehension are starting to fall behind. For example, people are still involved in the "archeology" of the OpenAI-HF incident from many months ago. Mathematicians may be poring over the 722 manuscripts on frontier mathematics for a while. The funnel is driven by a combination of factors: 1. The impact scales with ambition, problem size, and horizon. A question with a paragraph answer barely stresses the system. You need a reservoir of big, difficult problems that you really care about. This aspect drives the consumer / professional dimension of the funnel. 2. The jaggedness of the system (which I have written about a lot separately). Capability peaks in domains that are digital, verifiable and economically valuable. This is because LLM capability emerges from reinforcement learning on verifiable rewards on a curated environment mixture driven by revenue potential. This aspect primarily drives the area (e.g. math&code) dimension of the funnel. 3. Access. Free-tier, paid-tier, internal. So this is the weirdness of the moment. The general public has mostly not interacted with these systems. When they have, it looks like a derpy chatbot. The majority of professionals still see only a modest uplift. And a small sliver of professionals are experiencing the vertigo of the curve going vertical. And it is all happening at the same time.
Judging by my tl there is a growing gap in understanding of AI capability. The first issue I think is around recency and tier of use. I think a lot of people tried the free tier of ChatGPT somewhere last year and allowed it to inform their views on AI a little too much. This is a group of reactions laughing at various quirks of the models, hallucinations, etc. Yes I also saw the viral videos of OpenAI's Advanced Voice mode fumbling simple queries like "should I drive or walk to the carwash". The thing is that these free and old/deprecated models don't reflect the capability in the latest round of state of the art agentic models of this year, especially OpenAI Codex and Claude Code. But that brings me to the second issue. Even if people paid $200/month to use the state of the art models, a lot of the capabilities are relatively "peaky" in highly technical areas. Typical queries around search, writing, advice, etc. are *not* the domain that has made the most noticeable and dramatic strides in capability. Partly, this is due to the technical details of reinforcement learning and its use of verifiable rewards. But partly, it's also because these use cases are not sufficiently prioritized by the companies in their hillclimbing because they don't lead to as much $$$ value. The goldmines are elsewhere, and the focus comes along. So that brings me to the second group of people, who *both* 1) pay for and use the state of the art frontier agentic models (OpenAI Codex / Claude Code) and 2) do so professionally in technical domains like programming, math and research. This group of people is subject to the highest amount of "AI Psychosis" because the recent improvements in these domains as of this year have been nothing short of staggering. When you hand a computer terminal to one of these models, you can now watch them melt programming problems that you'd normally expect to take days/weeks of work. It's this second group of people that assigns a much greater gravity to the capabilities, their slope, and various cyber-related repercussions. TLDR the people in these two groups are speaking past each other. It really is simultaneously the case that OpenAI's free and I think slightly orphaned (?) "Advanced Voice Mode" will fumble the dumbest questions in your Instagram's reels and *at the same time*, OpenAI's highest-tier and paid Codex model will go off for 1 hour to coherently restructure an entire code base, or find and exploit vulnerabilities in computer systems. This part really works and has made dramatic strides because 2 properties: 1) these domains offer explicit reward functions that are verifiable meaning they are easily amenable to reinforcement learning training (e.g. unit tests passed yes or no, in contrast to writing, which is much harder to explicitly judge), but also 2) they are a lot more valuable in b2b settings, meaning that the biggest fraction of the team is focused on improving them. So here we are.
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Maxime Germain retweeted
this is quite moving. a whiff of what might be coming for more and more of us. A pretty wide diversity of reactions to the math results.
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Maxime Germain retweeted
convergence to the mean when everyone looks at everyone else to decide what to make, we eventually stop making anything of our own. we copy what works. borrow the language, the aesthetic, the features. we call it learning from the market, following best practices, staying competitive. together, everything starts to feel familiar. polished, interchangeable. nothing wrong. nothing alive. the mean isn’t necessarily bad. it’s where everything lands when we remove the reasons for it to be different. numbers are easier to compare than feelings, so we make things that produce numbers. we study what gets attention, then shape ourselves around it. eventually the feedback stops informing the work and starts authoring it. we’re no longer asking what we want to say. we’re asking what will be rewarded for saying. ai makes this loop frictionless. it can draw from more references than we could see in a lifetime. but access to every perspective isn’t the same as having one. it hasn’t lived a particular life that makes one detail unbearable and another beautiful. when we ask it to choose for us without bringing any intention of our own, we get something plausible, easy to approve. then we ship it, measure it, copy it, and feed it back into the next round. a tidal wave of mid. this changes not just the work, but the people making it. we describe ourselves in categories platforms can distribute and markets understand. designer. founder. creator. pick a niche. build a brand. be consistent. the parts that don’t fit become inconvenient, even when those contradictions might produce our most interesting work. we become easier to classify and harder to tell apart. i think we need to approach making things more like artists. an artist develops a perspective through the work. making, noticing, choosing, failing, returning. learning what matters even when nobody else cares. craft gives that perspective a form precise enough for someone else to experience. the life outside the work matters too. the places you’ve lived, the people you’ve loved, the things you’re embarrassed to care about. these aren’t distractions from having something to say. they’re how you come to have something to say. we understand this with music, paintings, photographs, movies. we expect a person to be present in the choices. we want to experience something we wouldn’t have encountered without them. software can do this too. a piece of software expresses beliefs about how life should feel. what deserves your attention. what you should be free to change. whether a task should feel like paperwork or play. even a small interaction can carry someone’s care, humor, or curiosity. but we rarely talk about software as a medium. we talk about it as an industry. markets to capture, workflows to optimize, competitors to catch up with. we add a feature because someone else has it, without asking whether it belongs. products accumulate the same parts and lose what made them worth choosing. underneath the branding, it’s all the same thing. artists learn from others too. the question is whether you’re absorbing those influences into a point of view, or using them to avoid developing one. what are you trying to let someone feel, understand, or do? why this particular shape? what have you noticed that the existing tools don’t seem to notice? those questions don’t have answers you can borrow from a competitor’s roadmap. if we can make almost anything, deciding what deserves to exist becomes more important, not less. speed gives us more chances to exercise judgment. it doesn’t remove the responsibility. i don’t want a world where every person becomes a more efficient distributor of the same ideas. i want people to use these tools to go further into what they actually care about. to make things specific enough that we can feel someone behind them. what is the point of everyone being able to make something, if we all end up making the same thing?
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Maxime Germain retweeted
Replying to @illscience
yes and I don’t mean the loop disappears it’s more that the domain-specific playbooks we’re encoding around it increasingly get absorbed by the model the best general-purpose loops already abstract a lot away - very very little prompting or guidance. tools exposure only. Muse, inspired by OpenClaw architecture, is a good example but the moment you ask it to run a business and it still breaks down without tons of specialized workflows and prompting: build an SEO-optimized website for a local business, manage its ad spend, etc. today, we’re doing a lot of the agent’s thinking for it: when to act, what to do, in what order, how to respond to the result. much of what makes the best vertical agents work is their builders having explicitly encoded that judgment / behavior I expect frontier models to acquire that operational know-how pretty quickly making the unique knowledge required obsolete gather goals, business-specific context, and access to tools, and they should increasingly figure out the workflow themselves. we shouldn’t need a bespoke playbook for every task. knowing how to orchestrate a particular workflow becomes less differentiated. the moat will shift from teaching the agent how to do the job to giving it data and access others don’t have. increasingly so companies standing on this data / action access will either lockdown as they build their own (service titan/podium - amazon/perplexitiy/muse - google is already making api access harder) until they figure out a toll system / something they benefit from
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there are some people cooking things that are not Muse / Instinct - this new era of software is thrilling
Currently using two stealth agentic consumer AI products that costs $1k - $3k per month in tokens. The world is about to change drastically.
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Maxime Germain retweeted
Action!
beside motion pictures™ coming soon
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Astra has a lot less guardrails on pentesting/reverse engineering which is appreciated (and scary)
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Phenomenal! Congrats @ClementDelangue
Super happy to share our intention to join forces with NVIDIA in a $12,930,300,000 acquisition 💛💚 10 years after starting Hugging Face, open-source AI is at an inflection point. Thanks to the community, we’ve shown that it can be a complement, and even an alternative, to closed-source APIs. But for it to happen at larger scale, it needs more compute, more support, more collaboration and more visibility. That’s why we went to talk to Jensen, who offered to do exactly that with us. In addition to doubling down on NVIDIA’s massive contributions to open-source AI (I called them the “King of American open-source AI” earlier this year), they’ve committed to strongly supporting Hugging Face and our mission while keeping the platform open, independent and compute agnostic. The founders and the team are all staying to keep pushing this mission forward. Together, we think we can make open source the default way to build AI, with the goal of empowering 100 million AI builders to own their intelligence rather than rent it. Excited about the next 10 years! 🤗🤗🤗
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Maxime Germain retweeted
i built an internal marketing tool over the weekend it uses our real app so i can screenshot, record, and use coded sequences for landing pages
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Beside AI receptionist remembers the context of past conversation with a customer on each interaction
The most memorable businesses remember you. Caller Memory makes that possible. Your AI Receptionist can bring the same care and personal touch to every conversation. Now available on Beside for iOS, Android, and web.
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🧑‍🍳 cooking so much more
Summer cleanup at Beside. We've made Beside Phone for small businesses way better: 1. Spam Shield – likely spam flagged on the ring screen, filtered into its own view, and you can mark a caller spam or not-spam. 2. Call flow visualization – see how a call moves through ringing, the AI Receptionist, transfers to teammates, and voicemail on one screen. 3. Call Recap – tabs for the summary, the transcript, and the recording, with the next action in reach. 4. Knowledge – four sections the AI Receptionist answers from, so it stops guessing about your hours and services. 5. Settings – full pages instead of modals across business hours, alerts, call summaries, and blocked contacts. 6. Referrals – a dashboard showing your balance, what's pending, and what's paid. Get $200 per referral. 7. Plus closed periods for business hours and verification codes (OTP) can be found in-app settings. Now live in iOS 2.21, Android 1.22, and web.
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we made so many improvements to Beside Phone these past months - a lot more coming / announced shortly 👀 for now: Quotes
Quotes are available today in Beside. Our agent answers the call, captures what the customer wants, and drafts the quote with line items. You just hit send. Beside is helping the real economy run on AI.
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Maxime Germain retweeted
I grew Polsia from $0 to $10M run rate in 5 months. Solo + AI. Zero employees. Everyone asks me how. Presenting aisloP episode 2: “The Rise”
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Currently using two stealth agentic consumer AI products that costs $1k - $3k per month in tokens. The world is about to change drastically.
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let's go @avec_alan team!! congrats @jcsamuelian @Gorintic 👏
I'm incredibly proud to share that Alan is raising €480m (Series G), valuing the company at €5.5bn: the largest round in our history, led by @Prosusgroup , alongside our amazing long-term partners Teachers' Venture Growth and @IndexVentures (@janatindex ), and new investor Dara Holdings. 🚀 Ten years ago we set out to do something simple and hard: turn healthcare from reactive to proactive. To build a partner that helps people act before a problem becomes a bigger problem: bringing insurance, prevention and care together in one experience. Because health can't wait. Today that conviction is no longer a bet. It's a model that works: → 1.1m+ members → €800m+ in ARR, growing 53% YoY → Profitable in France, live across France, Belgium, Spain and Canada So why raise now, and why Prosus? Because we're at the meeting point of two powerful forces: a company that has proven its model, and the leadership we are taking in AI for health. AI will make personalized prevention, navigation and support available to everyone, and that changes what's possible for the millions of people we can help. And I couldn't be more delighted to do this next chapter with the Prosus teams. Prosus is one of the world's great technology operators, with $100B+ under management and a track record of building category-defining consumer platforms across the globe. They came with deep conviction, a long-term horizon, and exactly the expertise we need now: international expansion, consumer products, AI infrastructure, and an ecosystem we can plug into. I have loved every single interaction with their team: Fabricio, Fahd, Makram, Denis, Helen, Euro and many others! It makes so much sense because we share the same belief: the future of health is built at the intersection of insurance, prevention, care and AI. Great health is a universal right and prevention should be too. This round gives us the means to move faster: expand to new countries, deepen our presence where we already are, invest even more in AI and product, and pursue the strategic opportunities ahead. To our members, our 850+ Alaners, and everyone who has believed in this mission:thank you. 🙏 We're still at the very beginning of what Alan can become. Prevention insurance is the category we're building. Let's make it the new global standard. If this is the kind of mission you want to spend your energy on, we're hiring. Come build it with us. 💙
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Crazy to witness Opal rising to 1m DAU and accelerating! Congrats @kschlenker and team
Today we're announcing the new Opal to build the operating system for attention. 1 million people already use Opal every single day. We raised $10M. Personal AGI is coming.  The bottleneck won't be access to intelligence. It will be attention.
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Maxime Germain retweeted
Polsia just raised $30M at a $250M valuation. Approaching $10M annual run rate. One Founder + AI. Zero employees. Polsia runs companies autonomously. It also ran its own fundraising. I just showed up for signatures.
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