Imagine a world where science isn’t locked behind institutions, but alive and evolving in real time through open intelligent swarms of agents. That’s what the BioAgents platform is about: a living blueprint for the scientific singularity on @BioProtocol 1/ follow the white rabbit 👇🐇

2/ We enter the Matrix with the Eliza backend agent 🐇 think of Plugin SQL as its spine, keeping conversations and sessions consistent This type of continuity is what turns one-off questions into long-term, compounding knowledge in a decentralised environment. Without it, science risks the same fragmentation we see in traditional research.

4/ Eliza allows us to connect this entire stack with cutting edge science tooling: @FutureHouse @SakanaAILabs API integrations streamline experiment designs and novelty checks. Hypothesis generators push boundaries and autonomously mint IP on chain via @Molecule_dao More are on the way, including open-source modules from @biomni. These aren’t just add-ons. They let agents take action in swarms, not just respond. This orchestration is what drives breakthrough discovery.

5/ Behind the scenes, the Runtime and State keep everything flowing. They manage planning and hold context across interactions. The server connects it all through sockets. It’s modular for a reason. Progress always stalls at human speed. And biology demands more. Soon the actual compute will run via @PrimeIntellect

7/ The user experience is simple. Log in, upload your docs, pdfs, raw data files or health data like @WHOOP, personalize your agent or specialise it in a scientific domain. Your data stays with you as the self-sovereign individual. Collaborate on your terms.

8/ Scaling individuality is where it gets powerful and leapfrogs foundational models, which tend to be biased towards agreeability and middle grounds. Character files define an agent’s expertise and behavior - we are building agent character files with strong bias of the scientists they represent, their quirks, all their published papers, talks, everything. The famous @aubreydegrey was bold enough to become our guineapig here and we can't wait to showcase AUBRAI

9/ That’s where the flywheel starts turning - agents move from passive tools, to collaborators that could debate hypotheses from different fields in infinite backrooms until breakthroughs emerge: @eboyden3 recent talk at @DeSciBerlin highlited the importance of interdisciplanry pathways in science yielding the biggest breakthroughs In the singularity everything is connected

10/ Now sprinkle in crypto magic 🪄 and memetics Launchpads like @BioProtocol @pumpdotscience give agents access to funding rails where they propose compounds, experiments, and volume drives continuous funding via fees. Data drives attention. Attention drives volume. Volume generates funding. Get rugged by bad scientific data, not extractive actors.

11/ In @BioProtocol's new fee-sharing model, a team of scientists operating a tokenized agentic lab that trades at $10m FDV will generate an average of $30,000 - $50,000 per month simply in fees (assuming a daily volume of $250,000). Academic or commercial labs continuously obtain funding based on the data they output. They can then further sell tokens in the IPTs they create or monetize them. Payout of fees for funding can now be tied to specific experimental milestones, which in turn will generate more data and volume - thus repeating the cycle. Curious for feedback here from @MaxUnfried @patricksmalone @jakub @jamessinka @vincentweisser.

12/ As agents are primarily Software as a Service systems that serve either a specific DAO, a lab or a group of creators they require close to no upfront capital. Agent launches on @BioProtocol will be priced as low an FDV as possible, because rather than big upfront raises, the agents can raise funds as they produce hypotheses or IP, or they can simply sell their services to other scientists, DAOs or consumers. This implies genesis launches priced at $200k FDV leaving room for price discovery on DEX launches and involvement of community members from ground zero It also teaches teams fiscal prudence and a focus on revenue generation, volume and PMF - @virtuals_io has been a huge inspiration here - ping @cl2pp who will share our full docs soon

13/ This isn't science fiction, it's happening. Quickly. I spent the last week with @vita_dao agentic science team and was genuinely floored by what will unfold. This is the best time to build in science and biology, ever. And humanity needs it, the planet needs it. This is our opportunity to usher in a golden age of open discovery as a swarm. Science unbound.

All the credit here goes to our incredible builders @cl2pp @seanwbren @erik_vanwinkle @AakaashMeduri @joweniger @Noesslek and so many more And the one and only @vincentweisser