Rajan Verma (Aarvy)

@deepestbrew @mufasaYC It is actually good at there too.

@mufasaYC Good use of AI: writing code Bad use of AI: building PowerPoint diagrams that don’t suck

What used to take me 30 minutes now takes me 2 hours with AI. Also, what used to take me 2 hours now takes me 30 minutes with AI.

Ready to level up your Agent game? Stop building fragile AI wrappers and start engineering real systems. Follow aarvy.ml for deep dives into the engineering behind the AI boom.

Why Monty wins: Microsecond startup, strict isolation with no network or filesystem access by default, memory safety via Rust, and snapshot support. It is the missing piece for reliable AI infrastructure.

Stop giving LLMs direct access to your OS. Executing AI-generated code blindly is a security disaster. Meet Monty: the Rust-powered sandbox designed to make agentic code execution safe and lightning fast.

**Build Faster AI.** Ready to stop wasting compute cycles and start shipping production-grade inference? Follow for more deep dives into the world of production ML engineering. Your latency will thank you.

**The Gist of Speculation.** Tiny models guess sequences, large models verify them in parallel. Accept correct guesses, discard the rest, and enjoy zero loss in output quality with massive speed gains.

**Why is your LLM so slow?** Waiting for one token at a time is the biggest bottleneck in modern AI engineering. Let's fix that with Speculative Decoding. Stop letting your H100s idle while waiting for sequential outputs.

**Build to Sell or Build to Last?** The era of easy money is over, but the era of real exits has begun. Focus on moats and scale to survive the transition. Tag a founder who needs to see this 2026 roadmap!

**The 2026 Reality Check.** Valuations are shifting from "Hype" to "Unit Economics." High-revenue firms head to IPO, while others consolidate via acquisition. If your margins aren't healthy, your exit won't be either.

**The 2026 Payday is coming.** The VC liquidity drought is finally ending for AI startups. But for those building AI wrappers, your exit strategy is now more important than your code. Are you ready for the rebound?

**Stop being just a Prompt Engineer.** Real value lies in understanding the infrastructure that actually powers AI. Follow for deep dives into ML engineering and optimized deployments. 🚀

**The Engineer's Cheat Sheet.** Quantization reduces VRAM by 75%, enables LLMs on consumer hardware, and has minimal impact on reasoning. It is the secret sauce for production deployment at scale.

**Your GPU is dying for no reason.** Running LLMs in FP32 is like driving a truck to buy a loaf of bread. You're wasting massive VRAM and money for precision you don't actually need. Let's talk about Quantization. 🧵