Follow AI Builders — Not Influencers
RT LlamaIndex 🦙 How much can good documentation save an AI agent in cost and time? Turns out, a lot. We built a custom skill that teaches Claude how to parse PDFs more efficiently, then used real usage traces to find where it was wasting time and money (re-reading the same file over and over, taking unnecessary "screenshots" of pages, etc.) After a few rounds of fixes based on what we observed, the results vs. just having Claude read PDFs the default way: → 37% lower cost per question → Better answer quality across the board → Fewer wasted steps The big takeaway: look at what an agent actually leaves in its traces, and fix bottlenecks from there. Full case study 👉️ https://www.llamaindex.ai/blog/building-a-better-liteparse-skill-with-evals?utm_medium=socials&utm_source=twitter&utm_campaign=2026-- Benchmark code 👉️ https://github.com/run-llama/benchmark-claude-pdfs
It's no secret that coding agents are a great proxy for computer use and generalized knowledge work. After all, Claude Cowork is just a UI wrapper on Claude Code. I think Cursor has a great shot here. However, I do think it has a bit of work to do on the product and harness side to actually create an easy-to-use, powerful interface to help non-technical users manage docs. 1. For a long time you couldn't upload a PDF to Cursor 2. It needs a broader set of interfaces to knowledge work data sources (CRM, ERP, ITSM, etc. etc.) 3. It needs more integrated surfaces to manage, read, and edit unstructured documents - from markdown to Word docs/Powerpoint to Excel
Notice how Cursor isn’t saying “for developers”. Just “Useful AI”. Cursor will likely become a direct competitor to Codex and Claude Desktop. - Their in app browser is great. - Their composer model is good and fast for most tasks They just need to render documents like
