Hrant Hovhannisyan, PhD

PostDoc and entrepreneur @BSC_CNS and @IRBBarcelona. Developing bioinfo technologies for Biotech and Pharma. Tweets about science and technologies

[Hrant Hovhannisyan, PhD @hrant_hov]

🚨BREAKING NEWS🚨

🎉👨‍🔬🧬Exciting times ahead! We just secured an ERC Proof of Concept Grant to advance our computational NGS multiplexing tech! 🚀👀 Hold onto your hats and stay tuned for the epic tech we're about to make!
@toni_gabaldon @ERC_Research #Genomics #Bioinformatics

[Hrant Hovhannisyan, PhD @hrant_hov]

Ready for #SpaceX IPO?

[Hrant Hovhannisyan, PhD @hrant_hov]

@naturebeauty760 Forum in Barcelona, and this is a very old photo, many more new buildings now

[Martin Varsavsky @martinvars]

España no tiene un problema de fertilidad. Tiene un problema de calendario.

En las clínicas de fertilidad que conozco bien, dentro y fuera de España, lo que veo todos los meses es lo mismo. La paciente española típica llega con 38, 39, 40 años. Llega tarde porque alquilar costó la mitad del sueldo, porque encadenó contratos temporales hasta los 35, porque su pareja también, porque pedir una hipoteca con 32 era ciencia ficción y porque nadie en España la felicitó nunca por querer ser madre joven.

Cuando llega, la biología ya ha decidido buena parte de la conversación. La reserva ovárica a los 40 no es la de los 30. Ningún protocolo, ninguna IA, ninguna donante, ningún congelado mágico revierte del todo lo que el reloj ya cobró. La medicina de la reproducción puede mucho, pero no puede devolverle a una mujer la década que el sistema le cobró en alquiler, en interinidad y en burocracia.

Por eso me parece deshonesto el debate público español sobre natalidad. Se habla de cheques bebé de 100 euros, de permisos parentales, de campañas. No se habla de lo único que mueve la aguja: que una pareja de 28 o 30 años pueda permitirse vivir, trabajar de forma estable y tener hijos sin pedir permiso al Estado para cada paso.

La tasa de fecundidad española está en torno a 1,1 hijos por mujer. Edad media al primer hijo, por encima de 32, la más alta de Europa junto con Italia. Eso no es un problema cultural. Es la consecuencia matemática de un país que ha hecho que tener hijos a tiempo sea un lujo.

La fertilidad asistida puede ayudar a muchas familias, y lo hace. Pero no es una política demográfica. Es un parche carísimo para un problema que se debería resolver veinte años antes, en el mercado laboral y en el de vivienda.

[Hrant Hovhannisyan, PhD @hrant_hov]

Just after 2 days after finishing ESCMID Global, where so many folks argued that AI struggles with clinical tasks and more capable models are needed, we see ChatGPT for Clinicians, which reminds us that sooner rather than later AI will become an integral part in clinics.

[Greg Brockman @gdb]

Introducing ChatGPT for Clinicians:

[Greg Brockman @gdb]

Introducing ChatGPT for Clinicians:

[Hrant Hovhannisyan, PhD @hrant_hov]

@heavensbvnny Definitely yes

[Hrant Hovhannisyan, PhD @hrant_hov]

@guillermocarone @arvidkahl @euromaximal Spanish small business and startup laws are designed for bars

[Hrant Hovhannisyan, PhD @hrant_hov]

@JoeyMannarino False generalization. There are certain types of crimes in certain regions (there are several autonomous regions in Spain) where certain types of police (there are several types of police in each region) require appointment. I live in Barcelona and went to police directly.

[Hrant Hovhannisyan, PhD @hrant_hov]

@guillermocarone Again I don't support this, but the precedence of this in Spain is very high, when people just agree to secretly pay in cash to avoid taxes. So instead of figuring each and every case they just set a market price and deviations from it

[Hrant Hovhannisyan, PhD @hrant_hov]

@JoeyMannarino Obviously exaggerated, but yeah Tax Agency works super efficiently compared to all other public agencies

[Hrant Hovhannisyan, PhD @hrant_hov]

@TeslaNewswire How to piss a Catalan person

[Amy Tam @amytam01]

https://t.co/b9f99xbcMx

[Hrant Hovhannisyan, PhD @hrant_hov]

When Karpathy posts, you read every single word

[Andrej Karpathy @karpathy]

A few random notes from claude coding quite a bit last few weeks.

Coding workflow. Given the latest lift in LLM coding capability, like many others I rapidly went from about 80% manual+autocomplete coding and 20% agents in November to 80% agent coding and 20% edits+touchups in December. i.e. I really am mostly programming in English now, a bit sheepishly telling the LLM what code to write... in words. It hurts the ego a bit but the power to operate over software in large "code actions" is just too net useful, especially once you adapt to it, configure it, learn to use it, and wrap your head around what it can and cannot do. This is easily the biggest change to my basic coding workflow in ~2 decades of programming and it happened over the course of a few weeks. I'd expect something similar to be happening to well into double digit percent of engineers out there, while the awareness of it in the general population feels well into low single digit percent.

IDEs/agent swarms/fallability. Both the "no need for IDE anymore" hype and the "agent swarm" hype is imo too much for right now. The models definitely still make mistakes and if you have any code you actually care about I would watch them like a hawk, in a nice large IDE on the side. The mistakes have changed a lot - they are not simple syntax errors anymore, they are subtle conceptual errors that a slightly sloppy, hasty junior dev might do. The most common category is that the models make wrong assumptions on your behalf and just run along with them without checking. They also don't manage their confusion, they don't seek clarifications, they don't surface inconsistencies, they don't present tradeoffs, they don't push back when they should, and they are still a little too sycophantic. Things get better in plan mode, but there is some need for a lightweight inline plan mode. They also really like to overcomplicate code and APIs, they bloat abstractions, they don't clean up dead code after themselves, etc. They will implement an inefficient, bloated, brittle construction over 1000 lines of code and it's up to you to be like "umm couldn't you just do this instead?" and they will be like "of course!" and immediately cut it down to 100 lines. They still sometimes change/remove comments and code they don't like or don't sufficiently understand as side effects, even if it is orthogonal to the task at hand. All of this happens despite a few simple attempts to fix it via instructions in CLAUDE . md. Despite all these issues, it is still a net huge improvement and it's very difficult to imagine going back to manual coding. TLDR everyone has their developing flow, my current is a small few CC sessions on the left in ghostty windows/tabs and an IDE on the right for viewing the code + manual edits.

Tenacity. It's so interesting to watch an agent relentlessly work at something. They never get tired, they never get demoralized, they just keep going and trying things where a person would have given up long ago to fight another day. It's a "feel the AGI" moment to watch it struggle with something for a long time just to come out victorious 30 minutes later. You realize that stamina is a core bottleneck to work and that with LLMs in hand it has been dramatically increased.

Speedups. It's not clear how to measure the "speedup" of LLM assistance. Certainly I feel net way faster at what I was going to do, but the main effect is that I do a lot more than I was going to do because 1) I can code up all kinds of things that just wouldn't have been worth coding before and 2) I can approach code that I couldn't work on before because of knowledge/skill issue. So certainly it's speedup, but it's possibly a lot more an expansion.

Leverage. LLMs are exceptionally good at looping until they meet specific goals and this is where most of the "feel the AGI" magic is to be found. Don't tell it what to do, give it success criteria and watch it go. Get it to write tests first and then pass them. Put it in the loop with a browser MCP. Write the naive algorithm that is very likely correct first, then ask it to optimize it while preserving correctness. Change your approach from imperative to declarative to get the agents looping longer and gain leverage.

Fun. I didn't anticipate that with agents programming feels *more* fun because a lot of the fill in the blanks drudgery is removed and what remains is the creative part. I also feel less blocked/stuck (which is not fun) and I experience a lot more courage because there's almost always a way to work hand in hand with it to make some positive progress. I have seen the opposite sentiment from other people too; LLM coding will split up engineers based on those who primarily liked coding and those who primarily liked building.

Atrophy. I've already noticed that I am slowly starting to atrophy my ability to write code manually. Generation (writing code) and discrimination (reading code) are different capabilities in the brain. Largely due to all the little mostly syntactic details involved in programming, you can review code just fine even if you struggle to write it.

Slopacolypse. I am bracing for 2026 as the year of the slopacolypse across all of github, substack, arxiv, X/instagram, and generally all digital media. We're also going to see a lot more AI hype productivity theater (is that even possible?), on the side of actual, real improvements.

Questions. A few of the questions on my mind:
- What happens to the "10X engineer" - the ratio of productivity between the mean and the max engineer? It's quite possible that this grows *a lot*.
- Armed with LLMs, do generalists increasingly outperform specialists? LLMs are a lot better at fill in the blanks (the micro) than grand strategy (the macro).
- What does LLM coding feel like in the future? Is it like playing StarCraft? Playing Factorio? Playing music?
- How much of society is bottlenecked by digital knowledge work?

TLDR Where does this leave us? LLM agent capabilities (Claude & Codex especially) have crossed some kind of threshold of coherence around December 2025 and caused a phase shift in software engineering and closely related. The intelligence part suddenly feels quite a bit ahead of all the rest of it - integrations (tools, knowledge), the necessity for new organizational workflows, processes, diffusion more generally. 2026 is going to be a high energy year as the industry metabolizes the new capability.

[Hrant Hovhannisyan, PhD @hrant_hov]

@zarahussain999 Electricians very likely

[Hrant Hovhannisyan, PhD @hrant_hov]

@hthieblot Don't Waste Your Time - TechBio

[Hrant Hovhannisyan, PhD @hrant_hov]

@Jason Qualcomm

[Hrant Hovhannisyan, PhD @hrant_hov]

#PublicationAlert!
Our long-standing collaboration with HKI Jena and colleagues about the role of albumin in virulence of C. Albicans is now published in Nature Communications!
See the full paper below
https://t.co/951kH70rwG

Congrats to all contributors!

[Hrant Hovhannisyan, PhD @hrant_hov]

@johnrushx Coz most Americans don't know the rest of the World exist

[Garry Tan @garrytan]

The sweet sweet moment you find product market fit (wait for it)