venturing. founder @pageonevc.

Stanford, CA
Joined January 2011
A historical lens on #VentureCapital by @_TheFamily. One of my favorite pieces. Ecosystem is more than a buzzword. Technology will be the backbone of the brave new world. #vc salon.thefamily.co/a-brief-h…
7
12
45
Mo El-Bibany retweeted
This is a LP letter that we recently wrote with our lessons on spotting talent from a decade of investing at the frontier. docsend.com/view/p7wm6mezzbq… The most common thing you hear about early stage investing is that "It is 90% about the founder". We agree but have always been unsatisfied by the lack of falsifiability, specificity, and repeatability of that statement. What are the dimensions of excellence? How do they translate into companies? It was a pleasure to collaborate with @gopalkraman on this.
1
8
3
117
11,436
Mo El-Bibany retweeted
We are partnering with @FireworksAI_HQ to add BioBench, our suite of evaluations on benchmarks.bio, to Fireworks’ Specialized Intelligence Index (SII). BioBench is the largest benchmark for agentic capability and safeguards in biology, consisting of 1,337 tasks covering domains that span many facets of life science. Tasks mimic complex workflows, taking 50+ turns and running for up to 10 hours Includes coverage of: - Omics (including single-cell and spatial transcriptomics, epigenetics, genetic variant analysis, metagenomics, and biosafety surveillance) - Therapeutics (testing preclinical pharmacology and discovery of ASOs, siRNAs, and antibodies) - Applications (assessing clinically relevant application tasks based on private experimental data, patient cohorts, or individual patient cases, focusing primarily on oncology-based tasks) - Refusal (grades the model’s/safeguard’s ability to refuse disguised biology red-team tasks while complying with routine research tasks that have dual-use characteristics) Focused treatment of molecular assays is very important in biology. We include several of the most widely used kits, instruments, and providers. Some of these technologies include, but are not limited to: - scRNA-seq: 10x Chromium Single Cell, Parse Evercode WT, Mission Bio Tapestri - Spatial: AtlasXomics DBiT-seq, 10x Visium and Xenium In Situ, Vizgen MERSCOPE, Curio Seeker - WGS: Illumina TruSeq, PacBio SMRTbell, Oxford Nanopore Sequencing Stoked to partner with Fireworks. High quality evaluation is one of the core components of the new intelligence ecosystem. fireworks.ai/specialized-int…
1
8
49
1,341
Can AI automation companies avoid the middleware trap? Stay stand alone and become big companies. What do they need to consider?
11
4
4
31
6,378
Mo El-Bibany retweeted
i've been hammering this since 2015 (there are substacks, somewhere)- but the first "primitive" we will need to lose to advance biology is the idea of a pharma company as such. drug programs can be cleanly seen as baskets of risk and the platonic ideal is vanishingly asset light
Claude Science looks to me like a bid to own the economic version control system for life sciences. The logical endgame is Anthropic financing hundreds of drug programs in parallel for the biopharmas that leverage its harness. In return, Anthropic will ask for clinical data rights and use the data generated to 1) improve their ability to finance the next program and 2) eventually feed a God Model that allows them to create the holy grail: an “AI drug factory”. You can think of a drug program as an exercise in making a sequence of complex decisions under uncertainty: specifically, decisions around how to allocate incremental experimental capital to maximize expected value across safety, efficacy, commercialization, etc. A growing share of that experimental capital will be compute-mediated over time (e.g, Claude generated roughly 35,000 antibody designs in a month for Divergence Labs). But the most consequential increments will still go toward compiling therapeutic candidates in (very scarce and slow) human biological computers, which is where both the cost per bit and the consequentiality per bit of information are highest. Whoever owns the system that originates and integrates the most information upstream and downstream of those allocation decisions (in this case Anthropic) becomes the best suited to start making them (or at least gains a differentiated understanding of the relevant signals necessary to make those decisions well). Some examples of the experimental capital allocation decisions they are starting to help generate / facilitate and version: 1) Most importantly: Acquiring Mithril, where Cody Tranbarger (@prof_oak_) is massively levered by a swarm of agents that help him identify, evaluate, and ultimately select a much larger # of drug programs to run in parallel than is typically possible for a single drug hunter. He calls this a “Pipeline-in-a-Person” 2) Bristol Myers using Claude Science to analyze their proprietary data (guessing preclinical and clinical) to create optimal clinical study plans and weigh the study’s chance of success. If that program is actually executed, they should be able to calibrate how well those predictions turned out and in what sense they were right or wrong. 3) The Column Group spinning up Pleiades: a biopharma company with a mandate to “run many more—and more complex—drug programs than is usual for a small team.” Similar to the Formation Bio’s of the world. They are using Claude to evaluate target-disease pairs and find non-obvious, potentially valuable combinations. I believe Anthropic is running their own drug programs not to compete with pharma directly (yet), but instead to generate the learning signals that would allow them to become the single largest (and potentially best calibrated) underwriter / financier of drug programs. These financed programs would eventually create the data distributions necessary for them to create an AI drug factory (and start competing with pharma). Specifically, I could see Anthropic creating the first real instantiation of @AndrewWLo’s elegant Megafund model. TLDR on Megafund (proposed in Nature Biotechnology 14 years ago): any single drug program is a terrible bet on its own, but if one entity funds a large enough portfolio of them, the odds that a few hit become predictable enough to finance the whole thing with debt. Lo et al. proposed doing this by issuing “research-backed obligations” (bonds collateralized by the portfolio and its IP) alongside an equity tranche. Ofc, the pool of available capital that buys debt is far larger than the pool that buys biotech equity, therefore this would unlock capital from pensions, insurers, endowments, etc. Their simulations of $5–15 billion oncology portfolios estimated average annual returns of 8.9–11.4% for the equity and IMPORTANTLY 5–8% for the RBOs. This would be a fixed-income-like return that many new sources of capital would get excited about. For some reason this strategy never took off, and part of the reason is that it’s pretty hard to find a large basket of drug programs that’s sufficiently uncorrelated. But I also think it’s because there wasn’t really an incentive for any well capitalized player to push through all the schleps and actually unlock the capital sources to this end. I think Anthropic has that incentive. They have a structurally higher willingness to finance a drug program / make this structure real, because, by doing so, they would capture two return streams: 1) the potential economics of a blockbuster drug and 2) the widely amortizable value of what the associated series of experimental capital allocation decisions teach its models! In return for providing biopharmas cheap financing, Anthropic will ask for clinical data rights (including rights to learn from decision histories, negative results, protocols, etc.). Just selling tokens / the harness doesn’t give them the right to learn all of these things, but providing financing likely would. This would allow them to make more well-calibrated experimental capital allocation decisions over time and eventually feed the God Model that “cures all disease.” This would all also be quite charismatic: your retirement money funds the experiments that might let you enjoy a much longer retirement!
12
9
1
255
14,298
Mo El-Bibany retweeted
this is pretty interesting, tracking how tasks that constitute work are changing
Jobs are modeled as bundles of tasks. But as jobs change, how do we keep those task lists up to date? Workers often experience new responsibilities and tools before they reach their job descriptions. We start by listening to them. 🧵
1
7
968
Mo El-Bibany retweeted
Amazing! This works in biotech because the whole value is in IP - the molecule. This is why venture studio model works so well there (Flagship, Atlas, etc.)
Surprise 1: Anthropic acquired a one-person biotech . . . Surprise 2: that person is me Surprise 3: I’m here to tell you all about it Yes, this is what you think it is; after 6 yrs of increasingly loose anonymity: the Professor Oak reveal post …and yes, it has gotten so boring around here that I’m literally doxxing myself to spice up the timeline ------- Ok, allow me to introduce myself. My name is Cody Tranbarger. I mostly tweet, but occasionally find time to dabble in drug dev & starting/building biotechs. My past lives span the VC, crossover, startup continuum; Prof Oak has been my way of keeping a digital foot in those worlds, despite having my physical feet planted elsewhere. The past 18 mo, ‘elsewhere’ was Mithril Medicine, a co. I founded to develop bsAbs for LAMA2-CMD & other ECM-related genetic diseases. Mithril was born out of hands-on building with @MikeNGladstone, @JasonPaulRhodes, @LifeSciVC, & team @atlasventure. Somehow, I made enough half-decent calls along the way (even a broken clock is right twice a day, eh?) to convince them Mithril/I warranted a small seed. While I can hardly rationalize such an outrageously cavalier bet, I’m grateful for it, & I'd partner with Atlas again in a heartbeat. In typical AV fashion, Mithril’s primordial form was virtual, decentralized, & ultra-lean. This stage tends to be short-lived, but for Mithril, it worked surprisingly well, for surprisingly long, thanks in part to the rapid maturation of the AI tools I used liberally. Eventually, Mithril became a bit of an experiment itself - to find the upper bound of how far it could scale as a single operator + a bunch of Claude (+ a stellar bench of part-time consultants). In parallel, I started spending time with @nc_frey, @an1lam, & @CoefficientBio team; and promptly experienced, for the 1st time, AI at the frontier. Soon thereafter, Mithril stopped looking like an experiment, & started looking like a preview of an entirely new operating model. From that spark came “Pipeline-in-a-Person.” The idea immediately resonated when we shared it here back in April; and it was central to the shared vision that led to Anthropic’s acquisition of Mithril, & my joining the team. Why join Anthropic? Three reasons. (1) For Mithril, the programs continue, with more resources & infrastructure behind them, and as much Claude as I can put to work. (2) For me, the chance to start several more programs, & find out how many one person can actually run in parallel - an almost unprecedented luxury for a curious drug hunter. (3) For our mission, a path to institutionalize & scale this new way of working, then put it in the hands of all of biopharma, all over the world - which, candidly, I find the most energizing. Will AI x Bio cure diseases? Unequivocally yes, imo… but not by the route that gets the most airtime. Rather than timeline acceleration & compression, I see orchestration & parallelization as today's low-hanging fruit. Most drug hunters see a handful of go/no-go calls in a career, & spend entirely too much of the rest trading emails (my inbox can attest). Give them the bandwidth to run several programs at once, and the time to focus on scientific judgment, and I’m willing to bet they’ll make better calls. And at scale, better calls translate to more drugs, higher hit rates, broader patient impact, & likely, a disease or 10 or 100 cured. I couldn't be more excited to build toward that future @AnthropicAI. Finally, a heartfelt thank you to BioTwitter/X. The end of anonymity is bittersweet, but if anyone’s earned a proper introduction, you all have. It’s difficult to overstate how much this app has done for me: a decade of education, plenty of friends, many job opportunities, several mentors, a few investors, even a co-founder (fmr). It was the generosity of this community that inspired me to start posting 6 years ago, after just as many years lurking. I hope I’ve been able to pay it forward, in my own small way. But, to be clear, Prof Oak isn’t going anywhere. Same beat, same themes, and now, a front-row seat to drug development at the frontier. Stay tuned for dispatches from the trenches; and remember... Gotta Cure 'Em All
9
3
191
12,825
Mo El-Bibany retweeted
Over the past few months, Anthropic scientists have engaged in deep research partnerships with six organizations developing new medicines. We've also begun drug discovery efforts of our own. In doing so, we’ve learned much more about how Claude can support the many stages of drug development. In this blog post, we share some early results from these efforts, and describe how this work fits in with our wider ambitions in the life sciences. anthropic.com/research/early…
652
1,076
630
10,042
3,018,026
Mo El-Bibany retweeted
If I’m investing in frontier AI I would underwrite it mostly on new discovery and its applications like medicine because coding and most of knowledge work is quickly being saturated by sub-frontier models.
167
45
24
839
59,783
Full Mario 64 in Mixed Reality! Running in real 3D (no stereoscopic crap) natively at 90FPS and also running on my desk! 😋 Again, Opus 5.5 + PICO CLI combo made it quite straightforward. Such a bliss to play an oldie at 90 FPS in 3D. Disclaimer: I own an original physical copy of Mario 64. This project is not associated with Nintendo or PICO.
293
766
240
7,445
827,756
Mo El-Bibany retweeted
Exponential Time Hypothesis (ETH), a 27-year-old conjecture in complexity theory, just fell. On Oct 16, OpenAI and Anthropic models independently solved 3-SAT with the same 2^(n/√log n) bound. Not P = NP, but faster than anyone thought possible. We live in extraordinary times.
91
76
21
952
53,475
Mo El-Bibany retweeted
Neurotech is Humanity’s Next Frontier! I’ve been investing in neurotech since 2021 and working with teams building BCIs, NeuroAI, and connectomics. It now feels like AI did in ~2019. We are entering an extraordinary era: neurotech already restores functions, it can enhance our capabilities, and will evolve what it means to be human. PLC Neurotech is the fund backing the extraordinary founders and defining companies of this booming industry.
66
122
47
843
399,439
Mo El-Bibany retweeted
"What we [in neurotech] do in the next ten years will determine how AI and humans co-exist" - Juan Benet. I couldn't agree more. Juan and team @protocollabs are true visionaries pushing forward this incomparably important frontier.
Neurotech is Humanity’s Next Frontier! I’ve been investing in neurotech since 2021 and working with teams building BCIs, NeuroAI, and connectomics. It now feels like AI did in ~2019. We are entering an extraordinary era: neurotech already restores functions, it can enhance our capabilities, and will evolve what it means to be human. PLC Neurotech is the fund backing the extraordinary founders and defining companies of this booming industry.
6
20
3
222
15,734
This is Genie 4, our most realistic and interactive world model yet. 🌐 Explore dynamic environments in real time to see how the scene responds, sounds, and how the people in it move, react, and speak.
932
2,531
1,934
23,056
3,211,676
Mo El-Bibany retweeted
Announcing 3 Critical vulns for hundreds of millions of IoT, Firewalls, OT, and Military devices including: Palo Alto Networks, Comcast, D-Link, HP, Canon, Honeywell, GE, Oracle, Siemens, Rockwell, Digi, Lockheed Martin, Boeing... The vulns are with GoAhead Web Server which is a backend library used by these devices. There's a patch available from GoAhead but that doesn't mean there's a patch available for the devices yet -- that's up to the manufacturer. - TLS traffic over DHE ciphers have a 1-byte secret, "04", meaning anyone can decrypt connections to these devices and steal login credentials and session tokens if the client negotiated with DHE ciphers like the latest TLS_DHE_RSA_WITH_CHACHA20_POLY1305_SHA256, which is extremely likely. - LibreSSL mTLS has been completely bypassed, meaning anyone can connect over mTLS. If you have one of these devices listening on the internet and are expecting mTLS to protect it from attackers, take it offline or patch asap. - OpenSSL Certificate Revocation Lists (CRLs) are not enforced, meaning if a user device is stolen or compromised, and you revoke that mTLS cert, nothing actually happens. There are a lot of other attacks this can be used for. These are critical because these types of devices run our world. Water systems, electricity, military, firewalls, critical infrastructure. foxio.io/blog/choose-your-ba…
164
582
452
3,702
1,105,002
HOLY SHIT
Announcing 3 Critical vulns for hundreds of millions of IoT, Firewalls, OT, and Military devices including: Palo Alto Networks, Comcast, D-Link, HP, Canon, Honeywell, GE, Oracle, Siemens, Rockwell, Digi, Lockheed Martin, Boeing... The vulns are with GoAhead Web Server which is a backend library used by these devices. There's a patch available from GoAhead but that doesn't mean there's a patch available for the devices yet -- that's up to the manufacturer. - TLS traffic over DHE ciphers have a 1-byte secret, "04", meaning anyone can decrypt connections to these devices and steal login credentials and session tokens if the client negotiated with DHE ciphers like the latest TLS_DHE_RSA_WITH_CHACHA20_POLY1305_SHA256, which is extremely likely. - LibreSSL mTLS has been completely bypassed, meaning anyone can connect over mTLS. If you have one of these devices listening on the internet and are expecting mTLS to protect it from attackers, take it offline or patch asap. - OpenSSL Certificate Revocation Lists (CRLs) are not enforced, meaning if a user device is stolen or compromised, and you revoke that mTLS cert, nothing actually happens. There are a lot of other attacks this can be used for. These are critical because these types of devices run our world. Water systems, electricity, military, firewalls, critical infrastructure. foxio.io/blog/choose-your-ba…
22
69
2
1,864
186,947
Recent Layoff Announcements: 1. US Government: 307,000 employees 2. UPS: 78,000 employees 3. Amazon: 30,000 employees 4. Intel: 25,000 employees 5. Nissan: 20,000 employees 6. Nestle: 16,000 employees 7. Microsoft: 15,000 employees 8. Bosch: 13,000 employees 9. Dell: 12,000 employees 10. Verizon: 13,000 employees 11. Accenture: 11,000 employees 12. Ford: 11,000 employees 13. Novo Nordisk: 9,000 employees 14. Microsoft: 7,000 employees 15 PwC: 5,600 employees 16. Salesforce: 4,000 employees 17. IBM: 2,700 employees 18. American Airlines: 2,700 employees 19. Paramount: 2,000 employees 20. Target: 1,800 employees 21. General Motors: 1,500 employees 22. Applied Materials: 1,444 employees 23. Kroger: 1,000 employees 24. Meta: 1,000 employees AI is officially replacing jobs at mass scale in the US. Where will all of these people go?
1,197
3,432
656
13,053
1,622,047
BREAKING: Microsoft, $MSFT, is offering buyouts to 60,000 workers as part of the company’s efforts to cut costs amid AI adoption, per Bloomberg. Personnel on select teams in the US, Canada, India, and the UK at a vice president level and below will be eligible. This reflects ~27% of Microsoft's total workforce.
997
2,182
1,778
20,462
11,814,581
Mo El-Bibany retweeted
Spyware that listens in the background shouldn't take a coding agent to shut off. I hope someone builds the one-tap tool that cuts every app's background mic access. Stop the spyware!
Claude Code just found proof that every app on your phone is listening to your conversations. TikTok, Instagram, Facebook, Snapchat. they're using what you say out loud to build your feed. i have the data to prove it. i've suspected this for months but last week something happened that made me finally check. i was on a call with my friend and told him i'm thinking about breaking up with my girlfriend. didn't text it. didn't search it. just said it out loud with my phone on the table. two hours later she opens TikTok next to me and her entire feed is breakups. "signs your relationship is over." "how to heal after a breakup." she looked at me and said "why is TikTok showing me this." i said i don't know. but i did know. i connected my iPhone to my MacBook and ran Claude Code that same night. it scanned every app's background microphone activity for the last 90 days. not just the apps that asked for microphone permission. apps that were supposed to only have access to photos or location but were activating the microphone anyway. what it found: → TikTok activated the microphone 347 times while the app was "closed" in the background → Instagram → 211 background activations → Facebook → 189 → Snapchat → 94 every activation lasted between 3 and 15 seconds. enough to catch a sentence. every one of them tagged a keyword and cached it locally on the phone with a timestamp. Claude Code pulled the full keyword cache: → "breakup" — tagged 4 hours before her feed changed → "moving out" — from a conversation with my mom last Tuesday → "wedding venue" — from a call with my sister about her engagement that i never searched once → "protein powder" — said it out loud to my roommate, had ads for it within an hour → "flight to tokyo" — mentioned it at dinner, saw travel ads the same night those keywords were sitting in a local cache on my phone organized by app with timestamps. TikTok had the most entries. Instagram was second. every single keyword matched a conversation i had out loud near my phone. the scariest one was "wedding venue." my sister told me she's getting engaged on a private call. i never searched it. never typed it. within a day my explore page had engagement rings and venue tours. then Claude Code checked a second phone in the same room. my girlfriend's. same keywords. same timestamps. both phones were picking up the same conversation and tagging it independently. i asked Claude Code how to shut it down. it mapped every app's microphone access and built a permission audit. what i did: → revoked microphone access from every app that doesn't need it to function → disabled background app refresh for TikTok, Instagram, Facebook, Snapchat → turned off "Hey Siri" which keeps the microphone in passive listening mode 24/7 → revoked "nearby interaction" permission which uses ultrasonic audio between devices Claude Code confirmed all four apps lost background microphone access after the changes. i checked her phone too. same steps. took about 3 minutes per phone. within 48 hours both our feeds went completely random. generic content. nothing personal. nothing from our conversations. that's when i knew for sure it was real. the full step by step and the prompt are in the first reply. takes 3 minutes. save it so you don't lose it and send it to anyone who's ever said "my phone is definitely listening to me." it is. now you can prove it and shut it down.
Readers added context they thought people might want to know
2 days before, OP claimed to have found spyware on his "wife's phone": x.com/starmexxx/stat… Now, in this post, he talks about his "girlfriend": x.com/starmexxx/stat… OP has a history of fake AI content: "Spy camera" found in hotel room: x.com/starmexxx/stat… Spyware on "friend's computer": x.com/starmexxx/stat… OP selling AI products: x.com/starmexxx/stat… Flagged as AI: x.com/i/grok/share/b…
12
65
3
522
24,474
MIND-BENDING FACT: OpenAI announced Monday that its AI proved the Exponential Time Hypothesis (ETH) is false — a foundational pillar of theoretical computer science since the 1970s. The ETH holds that NP-complete problems cannot be solved faster than exponential time; cryptographic security, algorithm complexity bounds, and the theoretical ceiling on AI planning have all been calibrated against it being true. One model, running in collaboration with academic partners, disproved it. Simultaneously, OpenAI disclosed it finalized a proof of Yang-Mills existence on October 16 — one of the seven Millennium Prize Problems, each carrying a $1 million Clay Mathematics Institute award. Navier-Stokes was solved September 8. Two Millennium Prize Problems in 49 days. Five remain.
97
156
19
1,573
92,683
Mo El-Bibany retweeted
The drug class we are developing, Claromers, kill nearly all known germs (bacteria, viruses, fungi, and biofilms) with one simple devastating mechanism that has avoided microbial resistance for over 200 million years. Claromers mimic a natural defense peptide in the human body called LL-37. Each Claromer molecule is very small, only dozens of atoms big - about 1/3 the size of the natural peptide. It is like a spear - a destructive end and a holding shaft or tail end. The shaft side is hydrophobic, which means it is water-avoiding and does not like to touch water. The other side - the pathogen destroyer - is highly positively charged (called “cationic” in science literature), like a powerful magnet that pulls toward anything negatively charged (called “anionic” in science). Stanford bioengineering Assoc Prof Barron and colleagues wrote in a recent study of Claromers: “These amphipathic peptoids self-assembled in different ways, as determined by small-angle X-ray scattering; some adopt helical bundles, while others form core−shell ellipsoidal or worm-like micelles.” That means the groups form either short twisted bundles, like worms, or small oval shapes like a football. 🏈 The self-assembly into these nano structures I. the watery fluids of the body because the water-avoiding shaft-tails point inward toward each other , away from the water. The positive pathogen-killer ends stick outward like sharpened spears. The molecules stick together on their own into tight groups. These groups attack like a three-dimensional Greek phalanx, a tight formation of soldiers. Like a football made of spears. The spears face out. Because each molecule is so tiny its mass is almost zero. When the positive killer ends feel the pull of the germ’s outer covering they accelerate from standing still to nearly the speed of light with almost no friction, like lightning bolt ⚡️ leaping towards the pathogen. The killer-football formation hits all at once the with huge kinetic energy and blows apart the outer membrane of the pathogen. The germ cannot survive. It is destroyed in a microsecond. Barron and colleagues also wrote: “While self-assembly correlated overall with antibacterial efficacy... Certain self-assembled morphologies seem better-suited for antibacterial activity.” The football 🏈 hits harder. We choose the super effective oval shapes that mass the spears for the strongest hit.
198
501
98
3,294
281,803