This week, I learned:
- I know that fact-checking 2000 page PDFs is error-prone, so’d do it manually for a few pages, then refine. Agents would know this if they’ve tried and failed and added it to their memory systems. So I intervene when agents don’t remember well (increasingly rare) or I think they haven’t seen it before (again, increasingly rare). My prompts guard against these - but I shouldn’t habitualize these - they’ll be needed less in future.
- rofi - a Linux menu app I use for all kinds of things - makes it hard to take screenshots because it takes over focus and I can’t send the
PrtScor other keys to the screenshot apps. So I useflameshot full --delay 3000 --path ~/Downloads/screenshot.pngto take a screenshot (of the last region it used) 3 seconds later, and quickly activaterofiin-between. (The docs sayflameshot fullcaptures the full screen. For me, it captured my last region.) - ChatGPT can now connect to multiple GMail accounts in paid plans. X
- AWS to acquire DuckDB. DuckDB is one of my favorite tools today and is improving at a rapid pace. I guess that will continue in the short run - hope it lasts long enough for a worthy successor.
- I use GoatCounter to track my website traffic. It doesn’t capture domains (only paths), so I just use a code snippet to log
https://sanand0.github.io/SITE/...as/@SITE/...- the@makes it easy for me to see that it’s from a GitHub page. - I switched from anydoc to docling as my default PDF to Markdown converter. Docling is even better than AnyDoc #ForNow.
- Based on my Codex usage, ChatGPT recommended that I not create custom subagents (my setup already used subagents a fair bit last month), but rather, just use
default_subagent_model = "gpt-5.6-luna"(which is a remarkably good model for its price #ForNow). - Artificial Analysis hosts several useful task-based evaluations. Here are some the fronter leaders #ForNow:
- GDPVal is good for realistic tasks. Again, GPT 5.6 Luna models have captured most of the low-cost fronter.
- EnterpriseOps Gym is good for office tasks like emails, calendars, Teams/Drive, support tasks, etc. Interestingly, none of the OpenAI models are on the frontier. Claude Fable 5 and Gemini 3.5 Flash are at the high-end, but Kimi K3 (Max), Qwen3.7 (Max), GLM-5.2 (Max) lead the mid-end and DeepSeek V4 Pro / Flash lead the low-end frontier.
- TerminalBench 2.1 is good for coding tasks. The OpenAI models completely rule this frontier.
- Analyst Agent is good for spreadsheet tasks (using Python). Gemini 3.7 Flash seems to be a strong outlier on this frontier.
- Tau3 is good for navigating unstructured data. GPT 5.6 Luna wins the bottom, DeepSeek V4 the middle, and Qwen 3.8 / GLM 5.3 take the top. Anthropic and Google are not even in the race.
- Briefcase is good for building useful things from diverse messy data. Grok completely wins the mid-end with Anthropic dominating the high-cost frontier.
- APEX Agents is good for deeper knowledge work. GPT 5.6 Luna (Max) is a strong frontier outlier here.
- Task-based benchmarks seem more practical than token-based benchmarks.
- For example, rather than the LM Arena ELO vs Cost, I would use Terminal Bench 3.0 which clearly tells me to use Codex with GPT-5.6 Sol over Claude Code with Opus 5 / Fable 5; that GLM 5.3 with Claude Code might be excellent value for money as well when using APIs. #ForNow
- I also did a rough calculation to see if the $18 GLM subscription offers more than $20 ChatGPT Plus. Short answer: No, for my usage, Codex offers ~1.8x more value #ForNow. ChatGPT
- Anthropic’s Skill Creator Skill now includes evals and A/B testing #ForNow to check if a skill actually does better. I’ve been doing this the hard way, e.g. with impact of simple writing on thinking, optimizing my ideation prompt, optimizing my summarization prompt, etc.
- I switched from markitdown to anydoc as my default PDF to Markdown converter. AnyDoc handles tables and other kinds of structures in PDF much better #ForNow.