Unclear if a durable trend, but CEOs and CTOs are back to coding with a fury, thanks to coding agents.
I have public company CEOs sliding into my DMs (and “InMail”) telling me about falling in love with shipping software again thanks to Claude Code and Vercel.
“Dream accounts” that we always wanted to work with, where in the past the C-suite would hardly understand the infrastructure until much later in the game.
Coding agents are the ultimate PLG-fication of the enterprise. Bad, legacy software can’t hide anymore. The stack that works is self-evident to the entire organization, from intern to CEO.
What does “open” really mean in medical AI?
Our latest blog explores Fully Open Meditron - the first fully auditable pipeline for clinical LLMs - and what it could mean for transparency, trust, and governance in healthcare AI.
Incredible research from @VaidyaSahaj and others!
Read or listen for more: https://t.co/j0CpJpTvtS
One of the biggest mistakes in healthcare AI is treating governance and compliance as a layer added later. If they’re not built into workflows from day one, scaling beyond a pilot becomes much harder. Our FDEs at @KostenDigital work on this every day.
Compliance challenges rarely begin with regulation—they begin with inconsistent processes.
Limited visibility, unclear ownership, and disconnected documentation increase risk across regulated environments. Strong digital governance creates traceability, accountability, and confidence across operations.
Organizations that embed compliance into their operating model reduce disruption and strengthen long-term scalability.
👉 If you’re thinking about compliance readiness, governance visibility, or improving process control, let’s talk.
https://t.co/hsBuoCGOxx
A big day for multi-agent AI to accelerate biomedical discovery, hypothesis generation, designing experiments with proof points of new candidate drugs (cancer, fibrosis, macular degeneration, antimicrobial resistance, and more)
2 @Nature reports @GoogleDeepMind@FutureHouseSF
https://t.co/u1EYvJ05VJ
https://t.co/8DpAolom0F
El empresario Peter Thiel posó junto a los otros dos integrantes del podio del torneo de ajedrez del Círculo Torre Blanca, en la Ciudad de Buenos Aires.
https://t.co/Mg8GNMN23n
Tesla Vision allows us to deploy airbags up to 70 milliseconds earlier if your Tesla detects an unavoidable collision
This can be the difference between serious injury & walking away from a crash
I’ve always believed the No.1 application of AI should be to improve human health.
That work started with AlphaFold, and now at @IsomorphicLabs with the mission to reimagine drug discovery and one day solve all disease!
We are turbocharging that goal with $2.1B in new funding.
New from @GoogleDeepMind: Announcing AI co-clinician, a research initiative exploring the potential for real-time multimodal AI as an assistive component of the care team. https://t.co/qQzc5fu7O3
We’ve agreed to a partnership with @SpaceX that will substantially increase our compute capacity.
This, along with our other recent compute deals, means that we’ve been able to increase our usage limits for Claude Code and the Claude API.
With so many tech events in Miami these days, you will not want to miss @RalphQuintero and @GianniDalerta 's event: a genuine, open, friendly, real tech gathering, nestled in South Miami, in one of the traditional taverns of our area. Loving the vibe and the real connections that happen there! ⬇️
Great points by @levie. Enterprise AI agents won’t magically appear. They demand a profound rebuild of legacy systems, governance, redesigned workflows, and relentless adaptation. The complexity is the opportunity: a new wave of specialists and vertical solutions will define who actually captures the value.
Whether it’s existing consulting firms, new ones that emerge, FDEs from agent vendors, or new internal agent engineering roles, the amount of work that is going to be created to implement agents in enterprises will exceed anything we imagine today.
The complexity of implementing agents in any existing organizations is very real. When I talk to large enterprises, as you move from a chat paradigm to agents that participate in meaningful workflows, there are a number of things they need to do.
First, you have to get agents to be able to talk to your data securely across your systems. In many cases, enterprises have decades of legacy infrastructure that contain the valuable context for AI agents. That’s going to take a ton of work to go modernize and move to systems that work well with agents.
Then, you need to ensure that you’ve implemented agents with the right access controls and entitlements, the right scopes to be safely used, and have ways of monitoring, logging, and securing the work that they do.
Next, you need to actually document the processes in the organization in a way that agents can utilize for doing the work. You also need to figure out what the new workflow looks like when agents and people are working together on a process, and who steps in where. Just replicating the old workflow will mute the gains. Oh and you likely need to create evals for your top new end-state processes.
Finally, you have to keep up with a rapidly changing set of best practices and architectural shifts happening in the agent space. While it’s fun for people to change their personal productivity tools on a dime, it’s 100X harder to do this in a business process. The speed of change is a blessing and a curse right now for anyone trying to keep a stable system design.
All of this means that individuals and companies that develop expertise on the above set of components (and more) are going to be needed to help organizations actually implement agents at scale. This is also the rationale for vertical AI agents right now that can go in deep on a business domain and help bring automation to it.
This is a huge opportunity right now whether you’re doing this internally or as an external business provider.
New poll from @Gallup and @WestHealth: 14 million clinic visits were skipped because Americans asked AI for health advice instead.
Let that sink in: 14 MILLION visits. Per month. Right now.
The U.S. generates ~89 million physician office visits per month. 14 million = about 16% of that. One in six. Gone.