wow, Locu made it to Top 10 Fastest Growing Startups of the Week ( 790%) no funding, no ads. just me, @_kraci and @martinboksa building something we actually wanted to use ourselves based on TrustMRR data by @marclou 🙏

How do you deploy AI agents for financial institutions without compromising on security, isolation, or scale? Rogo powers complex research, analysis, and deal workflows for leading financial firms, supporting complex tasks across tens of thousands of concurrent users. To meet the diverse needs of financial teams, Rogo relies on both specialist and general-purpose agents that can adapt to a wide range of workflows. With Claude Managed Agents and self-hosted sandboxes, Rogo gets the orchestration and post-training capabilities needed to design these agent systems, while E2B provides the execution layer underneath. Every piece of code generated by an agent runs inside its own E2B sandbox with full auditability and traceability. Each sandbox is powered by an isolated microVM, providing the kernel-level isolation critical for Rogo's customers. The result is a seamless agent experience backed by the security, reliability, and compliance requirements that financial institutions demand.

Excited to announce that E2B sandboxes are now available through Stripe Projects. As part of the Stripe Projects developer preview, developers and AI agents can now provision and authenticate E2B sandboxes directly from the CLI. We're proud to be working with @stripe on the future of agent infrastructure and the Agentic Provisioning Protocol. Try it: install the Stripe CLI stripe projects init my-app stripe projects add e2b/sandboxes Full announcement is in the comments.

One billion sandboxes created on E2B. Every one of them powered an AI agent solving a real-world problem. From early-stage startups to cutting-edge AI labs to the Fortune 100, E2B is the infrastructure behind some of the most widely used agents in production, and the RL environments used to train frontier models. Come build with us.

I think there should be new AI benchmark for Anthropic only - UX of the Claude desktop app. Once it’s polished and smooth, we’re cooked and probably reached AGI😁 So long way to go..

I think we have lost some sense of judgment and moderation when it comes to product building currently. The moment you turn something into a universally celebrated metric, whether that is token burn, prototype count, or percentage of agent-written code, you start losing sight of what actually matters. I have felt the same way for a long time about overusing data and A/B testing to build products. The moment you reduce product quality or productivity to a metric, you stop shipping value and start shipping numbers. A lot of what people are doing with AI makes directional sense. The missing piece is counterbalance: 1. AI should help engineers build better products. Leaderboards and adoption metrics can be useful as directional signals. They do not tell you what is being built, whether it is good, or whether it should exist at all. 2. Users do not care what percentage of your code was written by agents. They care about the outcome. Faster output is useful. Like usually, faster doesn't seem to add to quality, clarity, or stability of products. Power to build should not become an excuse to lower quality bars. 3. LLM-generated prototypes can feel like late-night whiteboarding sessions. They look exciting in the moment and feel productive very quickly. Then a few days later you realize the idea was shallow, distracting, or simply wrong. The same trap shows up in jumping straight to code and solutions more broadly. You may just be building the wrong thing more efficiently. Prototyping has its place. So do clear thinking, good design, and a real understanding of the user’s problem. In terms of activities or momentum, the main quest and the side quest can both feel productive but only one actually moves the mission forward. 4. Adding more to products is still dangerous as ever even if time or effort to add it has gone down. Every addition creates complexity, maintenance cost, and user confusion. New features should be pushed back unless they clearly show it should exist and how it improves the product. 5. Not everything needs to be an agent shaped. A simple scheduled task does not need a full LLM sandbox. Making something agentic because it feels current or impressive does not make it right-sized, correct, or effective. The core ideas are: - even if you can, maybe you should not. - more power we have to build should not reduce our need to think, it should increase it.

added a little detail to my portfolio website

I really wish Apple had some sort of a deep link to "Add widget" screen..

Daily execution for AI era

Locu helps you lock in and focus on your most important outcomes. We’re now featured on ToolFinder in “Most Popular Deals”. Grab 50% off for our launch! 🚀

man so many good takes from @theo here youtu.be/28z6OjsNsUk?si=GWIy…

december was fun!