Mohit Grover

Hurray🥳🥳

I initially thought Vyper was just an another Smart Contract Language! But man, it’s safety-first approach makes sense now, they make unsafe code much harder to write by default! Vyper not having modifiers, multiple inheritance, inline assembly, function overloading makes sense It improves auditability, because it Storage layout is way more predicable. Vyper is a security-critical infrastructure which is amazing for core contracts but not ideal for Defi Protocols with many layers!

Zkvms built for GPUs, this provides complete FPGA Acceleration Backend! @cysic_xyz @cysic/open-sourcing-venus-a-new-foundation-for-high-performance-zkvms-b08fbb270ab7" target="_blank" rel="nofollow noopener">medium.com/@cysic/open-so…

My biggest takeaways from @simonw: 1. November 2025 was an inflection point for AI coding. GPT 5.1 and Claude Opus 4.5 crossed a threshold where coding agents went from “mostly works” to “almost always does what you want it to do.” Software engineers who tinkered over the holidays realized the technology had become genuinely reliable. 2. Mid-career engineers are the most vulnerable—not juniors, not seniors. AI amplifies experienced engineers by letting them leverage decades of pattern recognition. It also dramatically helps new engineers onboard. Cloudflare and Shopify each hired a thousand interns because AI cut ramp-up time from a month to a week. But mid-career engineers who haven’t accumulated deep expertise and have already captured the beginner boost are in the most precarious position. 3. AI exhaustion is real and underestimated. Simon runs four coding agents in parallel and is mentally wiped out by 11 a.m. He’s getting more time back, but his brain is exhausted from the intensity of directing multiple autonomous workers. Some engineers are losing sleep to keep agents running. This may just be a novelty issue, but the underlying dynamic—that managing AI amplifies cognitive load even as it reduces labor—is a real tension. Good companies will manage expectations rather than expecting 5x output indefinitely. 4. Code is cheap now. This simple idea has profound implications. The thing that used to take most of the time—writing code—now takes the least. The bottleneck has shifted to everything else: deciding what to build, proving ideas work, getting user feedback. Since prototyping is nearly free, Simon often builds three versions of every feature when he’s getting started. 5. The “dark factory” is the most radical experiment in AI-assisted development happening right now. A company called StrongDM established a policy: nobody writes code, nobody reads code. Instead, they run a swarm of AI-simulated end users 24/7—thousands of fake employees making requests like “give me access to Jira”—at $10,000 a day in token costs. They even had coding agents build simulated versions of Slack, Jira, and Okta from API documentation so they could test without rate limits. 6. "Red/green TDD" is the single highest-leverage agentic engineering pattern. Having coding agents write tests first, watch them fail, then write the implementation, then watch them pass produces materially better results. The five-word prompt “use red/green TDD” encodes this entire workflow because the agents recognize the jargon. 7. “Hoarding things you know how to do” is one of Simon's other favorite agentic engineering patterns. Simon maintains a GitHub repo of 193 small HTML/JavaScript tools and a separate research repo of coding-agent experiments. Each one captures a technique, a proof of concept, or a library he’s tested. When a new problem arrives, he can point Claude Code at past projects and say “combine these two approaches.” 8. The "lethal trifecta" makes AI agent security fundamentally unsolved. Whenever an AI agent has access to private data, exposure to untrusted content (like incoming emails), and the ability to send data externally (like replying to email), you have a lethal trifecta. Prompt injection—where malicious instructions in untrusted text override the agent’s intended behavior—cannot be reliably prevented. Simon has predicted a “Challenger disaster” for AI security every six months for three years. It hasn’t happened yet, but he’s pretty sure it will. 9. Start every project from a thin template, not a long instructions file. Coding agents are phenomenally good at matching existing patterns. A single test file with your preferred indentation and style is more effective than paragraphs of written instructions. Simon starts every project with a template containing one test (literally testing that 1 + 1 = 2) laid out in his preferred style. The agent picks it up and follows the convention across the entire codebase. This is cheaper and more reliable than maintaining elaborate prompt files. 10. The pelican-on-a-bicycle benchmark accidentally became a real AI benchmark. Simon created it as a joke to mock numeric benchmarks—get each LLM to generate an SVG of a pelican riding a bicycle, and compare the drawings. Unexpectedly, there’s a strong correlation between how good the drawing is and how good the model is at everything else. Nobody can explain why. It’s become a meme: Gemini 3.1’s launch video featured a pelican riding a bicycle. The AI labs are aware of it and quietly competing on it. Don't miss our full conversation: youtube.com/watch?v=wc8FBh…

A quantum computer won't kill crypto -- a centralized key management will.

Timeline of Different Mediums of Transactions : Barter to Gold ~ 600 B.C. Gold to Paper Money ~ 700 A.D. ( matured by 19th century) Gold Backed to Fiat Paper: 1971 Ethereum was launched in 2015! How long do you think it’s gonna take to Ethereum to go mainstream? 2030? 2040? 2050? #ethereum #crypto

Competition is largely an illusion. 95% of people don't even try to do great things. 0.1% of the people are loud, so you overestimate how many people there are. The rest get stuck worrying about competition and quitting after 2 weeks.

You can assign a private key to every atom in the visible universe

@_KxrMa_G Bro was in hibernation

When did RAM get this expensive? Wtf I need to pay 45k to get 32gb. Wasn’t this how much a entry level RTX used to cost 😭

Every node runs the same code to reach consensus, but it’s a waste of resources. EIP 8025: Optional Execution Proofs solves this! Validators can verify blocks using Zk proofs instead of re-executing every transaction. Specialised Validators known as zkAttesters verify Blocks via Zk proofs without storing full state!

It inlines small internal functions thus eliminating the overhead of JUMP and JUMPDEST opcodes. It also simplies complex expressions into equivalents, removes dead code , reuses code segments and Streamlines the usage of Redundant or inefficient variable usage!

I was today year’s old when I realised registering a contract means creating a transaction whose “to” field is EMPTY! The data field contains the bytecode of compiled contract. It has a size limit of 24KB . This can be reduced by using compiler’s optimiser. What does it do? ⬇️

This could break the logic of games that rely solely on address(this).balance This is called Ether Injection Attacks!

Could you send Ether to a contract address if no payable function is there? No receive() or fallback() defined? Use the SELFDESTRUCT opcode, it sends funds directly to an address at EVM level, bypassing all Solidity Code.

@AnIdiotJimJam Got it, gotta stick to this!

@GroverInnovate If you have two choices. Assign each to a side of a coin and flip it. You will know the right choice (trust me) when the coin is still in the air. Just don't deviate from it.

How do you actually find your niche , when everything seems interesting?

How will crypto look in 10 years?

@0xpanicError @AbhiMan1601 🔥🔥

The SoK on Speedy Secure Finality has been accepted in IEEE ICBC 🥳 Really happy to have my first paper accepted in a prestigious conference like this and special thanks to my co author @AbhiMan1601 for all his contributions.

Absolutely Loved this! ZK vs TEEs I am on the zk side; @ethmumbai

A few things surprised me: A single elliptic curve point addition = 2,000× costlier than a float32 fma → ICICLE-SNARK is 3× faster than RapidSnark on iPhone → Amdahl's Law caps total speedup at ~5×, and we're already at 3×. This Blog covers everything. Also, share your reviews.

I wanted to understand how mobile GPUs can accelerate ZKP proving. So, I read the papers, studied ICICLE-SNARK and Mopro’s Metal Implementations and wrote a Technical Blog covering GPUs, MSM, NTT, current scope and constraints. Check this out ⬇️ hackmd.io/KmoAyo8qRwaTfN…