Om

@zhmeishi Is it a check point for grok code fast ? Or a new model.. i hope it's economical like code fast.

Take many efforts to make it possible. Grok build coming soon!

@testingcatalog So no new coding Modal then

Early look at Grok Build and Computer 🔥 Yes, there is a strong assumption that both will arrive at the same time as a desktop app. > Grok Build UI has 2 versions, Local and Remote. The local version uses a Grok agent running locally for execution, which only makes sense if it were a desktop app. > Grok Computer is likely a Grok Desktop app with Grok Build built in. Since it will be web-based, there is a high chance that both macOS and Windows versions will drop at the same time. > Grok Build will arrive with Connectors support, Arena mode, and Parallel Agents mode. > Grok UI for Grok Computer may get an earlier-spotted Fire animation. Grok Build local 👀

@julientalbot974 @techdevnotes I saw it on open code idk if it helps

@omnaiduu @techdevnotes Peux-tu me donner l’id exact stp ? Je ne vois que le grok 4.20.

xAI has Released Grok 4.3 (beta)

@Star_Knight12 Dhh

Nobody has ever switched to TypeScript and gone back to JavaScript, Nobody

@matteocollina I wonder express server used with react router made difference, because tanstack start output is optimised for node with nitro. Is it fair ? Idk

We benchmarked TanStack Start, React Router, and Next.js running the exact same eCommerce app at 1,000 req/s on AWS EKS. The results were eye-opening.

@cneuralnetwork Cold start time??

running on modal now on a L4

@ishafoundation On landing page it's 18

Have you heard the news? #InnerEngineering is currently being offered for FREE. Register by today and complete the program within 60 days to receive a full refund. Today is the last day of this offer. Sign up now.

@Oblivious9021 Depends static vs dynamic Use cdn or edge acceratiion like AWS accelertor or cloudfront or cloudflare argo

Interviewer: Your page loads in 80 ms in Australia but 600 ms in India. Same backend. Same code. What would you use to fix this?

@brankopetric00 Even dynamic api ? Cloudfront should accelerate. Because of pop world wise. Interesting. I would use cloudflare argo routing

Your API serves 50 countries. Latency requirements: - US/EU: < 200ms - Asia-Pacific: < 200ms - South America: < 300ms Current setup: Single ECS cluster in us-east-1 behind CloudFront. US: 45ms. EU: 140ms. APAC: 380ms. SA: 290ms. APAC is failing SLA. CloudFront helps with static content but your API responses aren't cacheable — they're user-specific. Budget for infra: $3,000/mo additional. How do you fix APAC without breaking the budget?

@DhravyaShah @gnostrich @supermemory Enable argo routing if it's cloudflare specific

@gnostrich @supermemory Looking into this

is it just me or @supermemory latency is through the roof today? @DhravyaShah

@mehulmpt I like cloudflare. Too. There latency in india sucks. But yeah can be fixed argo routing. What plans do you use. ? Do you use there cdn.

R2 truly has the potential to steal tens of petabytes of data from AWS S3 and its customers. My biggest concern with R2 has been the subpar performance and availability. I'm happy to see progress on it!

@elithrar I like cloudflare so much. But there's latency issues in india until argo is put in action

(Unpleasantly) surprised to see Google significantly increase their egress costs here. 2x for egress out of North America to other peered (!) networks. Goes into effect May 1st.

@elithrar What's the point if cloudflare is slow in india

You can now tell us exactly where your existing cloud infra is and we'll place your compute as close as possible. single-digit latency to your DB and legacy cloud infra. no guessing.

@flybayer connectrpc.com buf.build/bufbuild/proto… Hope this helps..

So far the hardest problem with having Typescript frontend and Go backend is that there is no Zod for Go. And we are heavily using Zod for our new pipeline and module configs. We're currently using go-playground/validator and encoding/json with a ton of custom code on top. And tons and tons of json fixtures that we run against TS and Go 🤨

@flybayer @termiziyy Proto validate

@termiziyy How do you do runtime validation like required string lengths, regexs, and possible values of a field depending on the value of another field?

@flybayer Connect rpc helps.

@abhitwt Okayy. I hope freelancing works

@omnaiduu get a job or do freelancing

Skills that pay in this AI Era (2025): > Python + PyTorch / TensorFlow / Hugging Face > LangChain, RAG, Vector DBs (Pinecone, Weaviate, FAISS) > Full Stack: React/Next.js + Node/Go/Rust > APIs: GraphQL, gRPC, tRPC > Databases: PostgreSQL, MongoDB, Redis > DevOps: Docker, Kubernetes, Terraform > Cloud: AWS / GCP / Azure + Serverless (Vercel, Cloudflare) > MLOps: MLflow, Kubeflow, Vertex AI > Security: Zero Trust, API Security > AI Productivity: GitHub Copilot, Cursor AI Learn in this order. Ship along the way.

@arpit_bhayani Hmm wow Doesn't orm ? Helps in writing query in type safe way? Like if I change my table it reflects in the query ? In drizzle orm and Ts it does.. ? Idk how is it done with raw sql writing

ORMs are an anti-pattern once you start operating at scale. At scale, most move away from them as the abstraction that bridges the database and programming language never fully holds. At scale, by using ORM, you almost always end up missing native database optimizations. And if you are already writing raw queries to work around ORM limitations, you are actually better off using prepared statements directly. The ORM abstraction hides query complexity, yes, but it does make it easy to ship inefficient N+1 queries without realizing it. Debugging becomes painful at the worst possible time - during production incidents. ORMs tend to lag behind database features. Indexing strategies, query hints, and newer capabilities are either inconvenient to use (just look at prefetch in Django ORM) or simply unavailable. This makes you opt for the lowest common capability (as offered by ORM) instead of leveraging the database properly. At scale, explicit queries are always simpler, faster, and easier to optimize; the cognitive overhead of mapping objects to tables is often not worth it. To be fair, ORMs make sense for prototypes and for getting to market quickly. Use them when you are starting out or in the early phases, but have a plan to migrate away from them :) Easier said than done, though; been there!