Ivan Zografski retweeted
Cursor Enterprise customers: get Kilo Enterprise with $0 subscription fees for up to 12 months.
We’ll match your seat count 1:1 for the rest of your eligible Cursor contract. Inference is excluded, and verification applies.
Apply by November 30, 2026: blog.kilo.ai/p/nothing-to-lo…
Ivan Zografski retweeted
november 12 is when openai stops providing models to cursor. if your team relies on GPT inside it, now’s the time to plan.
blog.kilo.ai/p/cursor-exodus
Ivan Zografski retweeted
a better architecture on paper isn’t a faster system. linear attention without engine work built for it can slow inference down. blog.kilo.ai/p/open-weights-…
Ivan Zografski retweeted
Need is a good reason to reach for AI. Habit is a slippery one. Read that twice.
🔗 solveo.co/post/use-ai-becaus…
Ivan Zografski retweeted
one engineer built a private API endpoint to figure out what his cloud code reviews cost. now it’s one prompt to an agent. blog.kilo.ai/p/mcp
Ivan Zografski retweeted
Writing code is only one part of software engineering. Understanding the problem, making trade-offs, debugging production, and knowing what shouldn't be built are part of the job too. LLMs keep getting better at writing code. That doesn't make engineering judgment obsolete.
before we build any agent for a client, it has to pass 3 questions.
most ideas die at question 2. that's the point.
the filter:
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1. who does this today, and how many hours a week does it eat?
2. what number moves if the agent works?
3. who signs off on what the agent produces?
no hours, no number, no owner: no agent.
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Ivan Zografski retweeted
We’ve just made public 125,091 DICOM radiology images from across my cancer journey (link below). The data is both longitudinal and multi-modal, dated and linked to my treatment timeline, so you can compare imaging across initial diagnosis, standard of care, first remission, “founder mode cancer care”, and second remission. It’s viewable in OHIF, the standard open-source viewer used in radiology research.
Given the long history of applying deep learning to radiology, we’re hoping to see a variety of methods and models applied to my data. If you find something interesting, please reach out to [email protected], or if you know a researcher who should see this, tag them below.
Thanks to Terra LaFerriere for organizing these images, and Kamil Slowikowski for building osteosarc.com into the resource it is.
Ivan Zografski retweeted
No exaggeration, this guy might be the best interview in pro sports right now
worth reading the plan docs before switching: legacy plans keep their included model pool, the new tiers above $8 have no third-party allowance. if your team runs claude or gpt daily, price that at api list first.
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