This week, I learned:

  • Wrong answers are useful if you discover why they said that. Conversation is a game where you CO-CONSTRUCT common ground. Mike Caulfield
  • BMTC hourly data from Bangalore Metro is available via RTI. Vivek
  • “Find evidence for and against” improves LLM responses far more than “Are you sure?” Mike Caulfield
  • SSH3 is an emerging SSH alternative that’s written on top of HTTP/3. It supports OAuth2, OpenID Connect, and HTTPS for certificates.
  • Cholesterol has become a victim of its own success. We give statins to those with high LDL. So most people who have heart attacks have lower-than-natural cholesterol. Inflammation (HS-CRP) is now the strongest predictor of heart attack (American College of Cardiology). The usual stuff reduces HS-CRP: no sugar/carbs, veggies, nuts, green tea, turmeric/black pepper, weight loss, exercise, sleep, meditation.
  • ⭐ The beginner mindset: scrub your instincts and don’t let life experience cloud you. This takes effort. Hold on to naivette and escape cynicism. The Knowledge Project: Barry Diller
  • Forecasts give comfort. They may not be good but they feel safer than instinct. The Knowledge Project: Barry Diller
  • My laptop’s mic is much better than my phone’s mic, surprisingly. When recording conversations, it’s better to leave my laptop open and record than use the phone’s recording app.
  • ⭐ Here are the major not-immediately-obvious LLM megatrends/superpowers I see.
    • Swarms. Ask for dozens of solutions in parallel. Merge, rank, auto-debate, converge.
    • Personalize at Scale. Create feedback, designs, excerpts/summaries, … tailored to EACH person at scale.
    • Computer use. Agents operate UIs like a human (browser, apps).
    • LLM-as-a-judge. Use AI to validate ever-increasing AI generated output.
    • Synthetic data. Create realistic data for prototypes, testing edge cases, market research simulation, training data, …
    • Code on demand. Ask for outcomes directly. Agents code on the fly to get there, in data science, research, management, …
    • Style transfer. Copy a master’s style of drawing, coding, writing, … creating an army of their apprentices.
    • Multi-modality. Native voice/video/screensharing and long-context perception
    • Citizen experts. Non-expertise is not a barrier. Amateurs can create expert-level films, music, software, reports, …
    • Long-context LLMs. Growing context size lets us process entire repos, legal libraries, personal lifelogs, …
    • Memory. Assistants learn per-person / per-team. Cuts prompt, builds knowledge.
    • Agent-to-Agent. Agents consuming content (e.g. llms.txt), agents calling agents (sub-agents, A2A protocol, …)
    • Real-world tools. Write reports, send emails, shop online, use computer, control devices, …
    • Jagged frontier. AI is great at certain things but terrible at others. This frontier is unknown and shifting rapidly.
    • Lethal trifecta. You can only have 2 out of these 3: private data, untrusted content, and external communication.
    • Edge/Private AI. Small models on private cloud compute.
    • Authenticity. What content is authentic? What’s slop? What’s fraud? Are AI twins liable?
    • AI Governance. Strict liability, transparency mandates, state control, …
    • Not sure about or haven’t seen enough of these:
      • Data / workflow as the moat
      • AI native business models
      • AI digital-divide
  • ⭐ What I’d like to do next, maybe, is build a boutique “AI Studio”. Small group of good people coding delightful AI problems. Something that doesn’t scale.
  • GLM models can be used with Claude Code. At $3/month and a quality close to Claude 4 Sonnet, this is a good deal. But the effort of adding a new subscription is too high for me. I’d rather use it via OpenRouter which is doesn’t support an Anthropic API end point at the moment.
  • typst is a good LaTeX alternative. Markdown-like syntax with fast rendering. Mostly useful for researchers using LaTeX. But publishers / journals don’t accept typst often.
  • libSQL is an SQLite compatible fork with remote access, replication, ALTER TABLE to modify columns, random ROWID, etc. It supports the same externsions. The maintainers are working on turso - a SQLite compatible improvement with async, vectors, change data capture, etc. (still in alpha). But because of this, I’m a bit uncertain about the future of libSQL.
  • ⭐ LLM benchmarks show a correlation of ~0.5, hinting at a common theme of intelligence. Correlations in coding & science are particularly high. Ethan Mollick. Reminds me of student marks correlations. Strong correlation clusters (physics, chemistry, biology, mathematics, computer science) with the weaker correlations going down to ~0.5. What does it indicate? LLMs learn like people? Knowledge areas cluster? Humans write benchmarks like exams?
  • Dayflow records your screen at 1 fps and uses Gemini to summarise your activity every 15 min. Has low CPU usage.
  • ⭐ Code Mode is a smart way to use MCPs and a very likely future direction. Using LLMs to write code to call MCPs rather than directly.
  • Cloudflare supports an AI Index which will eliminate the need for a lot of custom RAG engineering.