sankalp
@dejavucoder
LLMs and shitposting into crafting ai product and evals dm open to talk on ai engineering/post-training
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prompt caching is the most bang for buck optimisation you can do for your LLM based workflows and agents. in this post, i cover tips to hit the prompt cache more consistently and how it works under the hood (probably the first such resource) sankalp.bearblog.dev/how-prompt-cac…
its a good rl environment, sir
Today we started rolling out SimGym — a system that creates “digital customers” that behave like real ones. They browse your site, complete tasks, and reveal optimization opportunities. You can even run A/B tests with *zero* live traffic! Spent a year developing it.
i approve of this eval
when i run gpt-5-codex-max reviews on opus 4.5 PRs (opus 4.5 produces way less slop than sonnet 4.5 but it can miss some spots of changes. if you are moving v fast, make sure to review extensively too. ask opus to self-review as well)
hope gpt 5.2 will help clear the tech debt
the downstream effects of claude 4.5 opus will be studied
winter dryness led me to gworlmax and buy cetaphil. its effective but i wish they added some fragrance to it coz it smells bad...
alex fazioooooo my saviour. whenever my twitter algo momentum is low he comes to like all my recent tweets
Sydney Sweeney is donating her coding agent experience logs to the Agentic AI Foundation, a directed fund under the Linux Foundation. In 1 year, her logs on X about coding agents have become go-to reference. Joining AAIF ensures the community always stays up to date with SoTA.
if you use kimi k2 for production use cases, what provider do you usually use
sometimes you have to consider the possibility that you are being dumb
We are a Small Research Lab based out of india and we just dropped a one of a kind SoTA multimodal multilingual document retrieval model. can embed and query documents across 22 langauges : English, Spanish, French, German, Italian, Hindi, Marathi, Sanskrit, Kannada, Telugu,…
Today we are excited to launch NetraEmbed SoTA multimodal multilingual document retrieval model. > Supports 22 languages > ~ 150% improvement over existing baselines > NayanaIR-Bench a open source multilingual document retrieval benchmark
peanuts - a tiny AI powered wearable by anya forger
i knew nano banana pro was very good but i didn't realise it was this good { "subject": { "description": "25-year-old Japanese woman with a curvaceous figure, standing in a meadow before Mount Fuji, gentle breeze lifting her hair", "pose": "relaxed stance, one hand…
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