The world hasn’t recalibrated to that reality, but it’s here. We're seeing it firsthand at Robo. Full post on why software will eat traditional content marketing is on the blog

What if I told you that your idea for a viral product could be live by Christmas?

🚀 Empowering Creators and Innovators with AI-Driven Tools 🎙️ Thrilled to announce the latest Glasp Talk #38 featuring an incredible conversation with Joseph DeBruin! Joey is a passionate entrepreneur, product builder, and writer on a mission to empower creators and innovators

Such an inspiring conversation with Joey DeBruin at Glasp Talk! 🌟 His journey from neuroscience to empowering creators with AI-driven tools like Robo is fascinating. I loved hearing about his insights on leveraging AI to break down barriers for non-technical founders and the

Everyone religiously says says "don't outsource custom software." But that only made sense when software was expensive. Why 2025 is the year of the roboagency 🧵

And that's also why Robo is doubling down on biotech After years at neuroscience labs, ResearchGate, and Benchling, we know the opportunities for specialized AI agents to accelerate R&D. More thoughts here: flyingpenguins.io/p/software-is-…

The clear opportunity in AI x Science isn't what you think: It's not about replacing scientists. It's about taking products that already work elsewhere and porting them into scientific workflows ⬇️

We've built a pretty simple AI system that has totally transformed how we do market research in biotech. Here's our stack if you want to recreate it:

Biotech runs on BD and complex market/regulatory analyses, and most people seem to think that's out of scope for AI. I couldn't disagree more :)

I've been testing using Deep Research to investigate the status of competitor drug candidates for a given biotech company and it already saves a huge amount of time. The limitation relative to what companies want is you can't compare it to your own candidate data (bc that data

Know an experienced engineer in Europe interested in AI for science? Send them our way 🫡

It took about 25 minutes for AI to process 7000 abstracts from last year's AACR conference and produce this network graph of all of the collaborations happening around antibody drug conjugates (ADCs). Unsurprisingly, academic institutions are much more densely interconnected

What happens when you set AI agents loose on 20,000 AACR abstracts from the past 3 years? You get ... a lot of insights.

Over the weekend, I had a team of AI “consultants” digest 13,000 abstracts from the past 2 years of AACR— and produce a deep-dive report on the progress of ADCs.

If you're in the oncology/biopharma world our AI agents are building a 𝐜𝐨𝐦𝐩𝐫𝐞𝐡𝐞𝐧𝐬𝐢𝐯𝐞 𝐝𝐚𝐭𝐚𝐬𝐞𝐭 𝐨𝐧 𝐀𝐀𝐂𝐑 𝟐𝟎𝟐𝟓 abstracts with 𝟔𝟎+ 𝐟𝐢𝐞𝐥𝐝𝐬 𝐨𝐟 𝐦𝐞𝐭𝐚𝐝𝐚𝐭𝐚. Happy to share free access for anyone doing something interesting with it💡 Includes:

Things have changed a ton for us over the past month — we've gone from quietly building the first version of our AI platform for biotech to being totally underwater trying to onboard new companies. Outside of product stuff what's bottlenecking us now is mapping out the details