Vision Ias

“Claude deleted my project.” After seeing multiple posts like this, including recent one where someone lost 717 GB of data, I realized something important: AI coding agents are becoming incredibly good at reasoning, but they’re still dangerously confident around irreversible actions. So while building GrapeRoot Pro ( https://graperoot.dev ), I started working on a defensive layer for Claude Code. I built an “Undo Shield” that watches session attention, which files Claude keeps editing, debugging, and revisiting and even warns before destructive operations like mass deletes or overwrites. But the more interesting part came while building the retrieval layer behind it. In the demo below, Claude audits a 80k file repository(effectively 10k) while using only ~32k tokens for the entire session. No embeddings pipeline. No vector database. No extra API calls. No additional LLMs. Everything runs locally using your existing Claude session + repository + a dual-graph retrieval system that narrows exploration before context gets wasted. So instead of blindly traversing thousands of files, Claude spends more of its context budget reasoning about the code that actually matters. Even during the audit, it was still identifying: • circular dependencies • dead exports • missing error handling • copy-paste logic • orphan TODOs • DB calls inside routes I genuinely think the next layer of AI coding tools won’t just be about better generation. It’ll be about memory, retrieval, reliability, and safety around long-running engineering workflows. Install : https://lnkd.in/g7gsuAwn And share how much score your repository got! If you are an enterprise, look at https://lnkd.in/g6C3UgXc

"Burnt 210 billion tokens in a week using claude code. That's the flex? Here's the reality check" Tokenmaxxing is the new Silicon Valley status game. I mean $150K/month on Claude Code. Jensen Huang saying tokens might become the "fourth pillar of compensation." If you own the GPUs, flex away. But here's the problem nobody's actually talking about: Claude Code reloads your entire codebase context from scratch. Every. Single. Session. It doesn't remember what it already mapped. Every prompt re-ingests the same files, the same service graph, the same cross-repo structure, because the tooling isn't built to remember. So we ran a benchmark. 110 engineering queries across a 34-service, 12-language production-grade workspace. Stock Claude Code: $0.755/query - 19 wrong answers out of 110 Ripgrep-augmented Claude: $0.729/query - 24 wrong answers out of 110 GrapeRoot( https://graperoot.dev ): $0.567/query - zero wrong answers 25% cheaper over 110 different Hard scenarios and 2× more consistent. (Honest numbers, no hack) And on the queries that actually kill engineers : blast-radius analysis, cross-service impact, Kafka topology and the quality gap widens to +10–15 points per query. At 50 queries/day per engineer, that's ~$5K/year saved per active user. On the other side, Users from open source free version collectively saved 1 billion tokens in the last 3 days. "Not burned. Saved!" This was when we hit the reality of this real pain. We wore t-shirts at YC Startup School that said "Cut your AI bills by up to 80%." The people burning the most came straight to us. Two became our first enterprise clients after seeing their own pilot numbers. Large companies can absorb the waste. A 10-person team where Claude Code is your primary dev tool? That bill catches up with you. We're not anti-AI. We're anti-stupid-spend. Free tool: graperoot.dev For teams: graperoot.dev/enterprise Source Image: [ https://lnkd.in/gviefkEi ]

This was the second consecutive pitch after exhaustive day at YC but people were really connected with the idea of product because it was solving their real problem. The line “Cut your anthropic/openai bill by 80%” on our tees was sufficient to pull interested people. Thanks for the opportunity at Entrepreneurs First , it was real fun to talk people with different ideas.