#todo | Anand S - Things I Learned

Mon, Nov 10, 2025. HTML + JS apps will last longer than server-side apps and it makes sense to write more of those. For essential back-end services, keep them generic. Specific services layers I see are: #cloud #future #prompt-engineering #server #todo
- Auth (e.g. Google Auth, Auth0, Supabase, ...)
- Storage (e.g. Supabase, Firebase)
- LLMs (e.g. OpenAI, Claude, OpenRouter)
- Communications (e.g. EmailJS)
- ... Extend with LLMs

Mon, Nov 10, 2025. Core concepts of game design #todo

Tue, Feb 18, 2025. I subscribed to ChatGPT Pro mainly for DeepResearch. Here are the first 50 reports I generated: #best-practices #code-agents #todo
1. uv Package Manager Overview
2. DuckDB Analytics Comparison
3. Rust vs Python / JavaScript
4. Modern Data Engineering Course
5. LLM Code Migration Practices
6. Cloud Cost Optimization Strategies
7. LLM Coding Interview Tools Report (compare with Perplexity)
8. Text To Speech Engines
9. Customer Service in Indian Public Sector Banks
10. LLMs in Software Development
  - Old version 1: Gen AI in Software Development
  - Old version 2: Gen AI in Software Development
11. Leadership Training Content
12. Open-Source HTTP Servers. Caddy wins.
13. Deep Research Use Cases
14. Nagpur No-Parking Violations
15. Data Science in Food Services
16. Deep Research Disruption to Research Firms
17. LLMs in Design Thinking
18. EU Taxonomy Report Clarification
19. Shell Valuation Analysis Inquiry
20. LLMs in DSLs Research
21. Public API-Based Data Storage Options. Supabase wins.
22. Front-End JS Frameworks Analysis
23. Database Evaluation Guide
24. CSS Frameworks Evaluation Guide
25. CI/CD Tooling Ecosystem Report
26. Color Names Count
27. S Anand Biography. Meh, I know more about me, and it gets a few things wrong.
28. Cosmere Secrets Encyclopedia. This is the best. Deep Research is great if it's stuff I actually want to read, rather than just learn about.
29. DBT course
30. Future of Coding AI
31. Claude Artifacts Use Cases. This is the only one that managed to get artifacts links correct. I used this for an article for The Hindu.
32. MCP Servers and Clients Research. Learnings:
  - Practically any "tool" can be an MCP server: file systems, APIs, codebases, browsers, collaboration platforms, memory, etc.
  - Most platforms have (or are) integrating MCP.
  - Clients: code editors, chat, and automation tools support MCP. GenAIScript is a good starting point.
  - Tester MCP Client is a browser-based test environment.
  - mcp-cli-client is a CLI-based client
  - mcp-chatbot is a chatbot client
33. Data Moats by Industry
34. Attorney Profile Research
35. Social Media Data APIs
36. Adobe Software Alternatives
37. LLM Hallucination Visualization Techniques
38. API vs Self-hosting Cost Analysis: Always use APIs, avoid self-hosting models.
39. AGI Preparation
  - AGI will emerge step by step. Knowing which step is next will help
  - AI native organisations will emerge in each of these areas. AI design agencies and AI creative Agencies being one example
  - Networking, empathy, leadership have more value now. So will human AI bridging roles (e.g. AI managers, AI consultants, ethics auditors)
  - What's the value of a human when technology can do everything better? How did this play out in drama (decay) or sports (centralization) or music (globalization)?
40. Modern digital note taking
  - Voice note taking is the game changer
  - Automatically popping of notes based on context such as people places or conversations will be a thing
41. Local LLM Search Tools
42. Blog Post to research paper on copying - suggestions
43. Linux Dev Migration Guide
44. Raspberry Pi SIM options
45. Linux Dev migration guide
46. HTML to JATS conversion
47. LLM context splitting strategies
48. Strategy for AI services in Publishing
49. Gemini multi model editing use cases by industry
50. Pharma Conference Participation Guide

Fri, Feb 14, 2025. Notes from a fireside chat with Prashanth Chandrasekar, CEO, StackOverflow, and the StackOverflow team #learning #todo
- There's a signal that software demand is growing in 2024. Many more students took the StackOverflow survey in 2024. So more students (or other professionals) are shifting into / starting to learn software development.
- The AI Index is a good resource for AI trends.
- Experts are better able to use AI for writing code. Less experienced developers are more likely to use AI for code reviews, project planning, etc.
- There's a 5% decline in favorability for AI tools compared to 2023, maybe due to disappointing results.
- Pilot groups working on AI are 25-30% more productive. They're the most enthusiastic. For the rest of the company, it drops off to 5-10%
  - Benefit comes from NEW people becoming programmers, not existing ones getting more effective?
- StackOverflow wants to be where the developer is.
  - The programmer workflow was: Google -> StackOverflow -> GitHub.
  - Now it's changing to ChatGPT / Cursor -> GitHub.
  - StackOverflow has a partnership with OpenAI and working on a plugin. Same with Google's Duet AI, GitHub Copilot, many others. They'll link to StackOverflow.
- StackOverflow is driving integration actively through an enterprise Overflow API
- Q: What tech have you seen blaze through the ranks?
  - Prashanth: Abstraction wins. Stuff that abstracts away things well and more wins. This includes Gen AI.
  - Erin Yepis: Rust (from 3% to 12%). AWS has steady growth.
  - Erin Yapis: I have a time series spreadsheet that I'll publish.
- Q: What technologies are unusually tightly coupled?
  - Prashanth: AWS & Google Cloud are tightly coupled.
- Q: We have an engagement problem. Might be India-specific. What are low-effort high-return mechanisms to increase engagement.
  - Eric Woodring: Rather than a static web page, integrate it using the API.
  - Ben Marconi: Use LLMs to write post mortems and push to StackOverflow.
  - Eric Woodring: "Hydrating" the community helps.
    - We take repeat questions on Teams / Slack and seed them using LLMs.
    - We integrate with the API to auto-add Q&A.
    - Transform documentation into Q&A. Potentially UPDATE existing Q&A if it's wrong.
- Q: What unexpected lessons about developer behavior have you learned while running StackOverflow?
  - Prashanth: We didn't expect developers moving away from Google. Now it moved to the IDE.
- Q: What are you learning about developer learning behavior?
  - Ben Marconi: Generating LLM-based onboarding documents.
  - Using StackOverflow for Teams to identify who the experts are to contact for specific topics.
- Q: Are you thinking about leveraging Stack Overflow's knowledge base for personalized or interactive learning experiences? How?
  - Prashanth: Traditionally, people use StackOveflow for productivity, learning, and flexibility (i.e. to ask/answer questions asynchronously without breaking their flow). So yeah, learning is important for us. (Duh!)
- Q: Could Stack Overflow’s interactions help evaluate the accuracy and relevance of LLM-generated code? Or provide potential metrics on quality?
  - Prashanth: LLM accuracy improves by ~30%. Upvotes / downvotes are reinforcement learning (RL) in steroids, so that helps.
- Q: What are your thoughts on reliance on LLMs potentially deskill-ing developers?
  - Prashanth: A real issue for junior developers, not for senior ones.
  - They'll come across as knowledgeable.
  - Make internal evaluations and interviews more rigorous.
- Anand's requests for action:
  - Could I get a copy of Erin's spreadsheet? Vivek Narayanan will follow-up.
  - Could you help me learn more about hydration? Nick Madison will set up a meeting with customer success group.

Mon, Oct 14, 2024. How AI can improve education performance and engagement. Ref #ai-coding #future #learning #todo
- Student: Create study plan based on course and schedule
- Student: Focus on what you need to learn more
- Student: Align with your study style and pace
- Teacher: Grading MCQs
- Teacher: Writing conceptual guides
- "New collar workers" was coined by Ginny Rometty
- Embed tutor or document in video and ask for clarification! This is a new embedded interface.

Sat, Aug 10, 2024. Embedding models can be fine-tuned. Example: #embeddings #future #gpu #markdown #models #optimization #todo

Wed, Feb 21, 2024. Discussions with Sachin, AMAT #todo
- Microsoft said Indigo, Air India uses LLM based bookings
- Meta invested $70bn in GPUs. Sam Altman is investing $7tn!
- NVIDIA has a price PREMIUM not discount for bulk GPUs!
- AMD is the next company to watch for
- Numenta - Subutai Ahmad - deploys AI models on CPUs
- Read A Thousand Brains by Subutai Ahmad
- Sanjeev Sharma
  - Swaayatt Robots: Autonomous driving in India
  - Deepeigen: Education
- Rohan Shravan, Bangalore.
  - Likes sharing knowledge. Amazing teacher. IIT KGP 2008. Interested in exploring quantum computing
  - Tresa Motors, Inkers App, The School of AI
- AMAT is working on
  - photon-based computing.
  - science research models. AI for science. Like Google: Deepmind Genome, Microsoft: Metagen
  - quantum: AMAT is actively in into this. Nagapati Banda is driving this
- John Kelly is predicting a ChatGPT moment in quantum in a few years

Sat, Feb 17, 2024. Discussion with Vinu Yamunan #dev #database #llm-ops #todo
- Databuck by FirstEigen. Autolysis plus monitoring
- Quality council has the data steward (maintainer of each dataset) coming together with the uses on a weekly basis to understand what quality problems to users are facing. Data owners jaundice at a lower frequency to get an understanding
- Automate rules for data quality in our projects and intranet
- Convert a config rule into business language. Explain SQL. These are good use cases for llm's
- Graph DBs are powerful for flexible data structures, but query generation needs AI or expertise. Check the Neo4J language cypher
- Explore storing SAME data in relational DBs AND in graph DBs / document DBs for different use cases
- Dallas rocketry challenge. Build a rocket that can take an egg to 800 feet exactly and land without breaking it

Sat, Feb 17, 2024. Discussion with Karthik A #ai-coding #prompt-engineering #todo #ans
- Ask IIT students to do internship tasks. Use advent of code is a qualifying criterion
- Tata motors unionized DB admins for longevity. No one can take their jobs. Hires people who LIKE their jobs
- Rust gives me typing. It's very efficient. Pola.rs is interesting but Pandas as good enough.
- Explore alerts from CCTV feeds. Karthik sends email alerts with pictures for:
  - "Is the machine on or off"? for productivity
  - "Are people not wearing helmets?" for safety at Cummins
- Integrate with WhatsApp. Use LLMs with function calling for responses
- Use expiring links (to pictures or content). It increases engagement
- Check Deno licensing. Is there a commercial clause? No - it's MIT license
- Centre or excellence for zero emission tech at IIT. Karthik is part of it
- Explore auth0. 7000 users are free
- toml is part of the Python 3.11 standard library!
- If copilot writes code we don't understand we are screwed. Hence expertise matters

Sat, Feb 17, 2024. Discussion with Vikas Kedia #todo
- Plan an AMA
- The mind becomes lazy with financial success. Vikas is treating his podcast as a startup
- Hire a professional videographer for your content
- Financial RoI in financial markets is the highest. Programming is high too but FS is even better
- "Performative power" -- when you're forced to perform, you get better ideas

Sun, Jan 14, 2024. AI by API is the norm today and will grow #automation #future #todo
- Just having AI is no longer a differentiator
- AI is part of life, not just work
- Explore quickdrop from Stability for Maruti
- Explore Codium VS Code plugin and Continue.dev
- Hybrid systems that combine stats, ML, DL and AI models will grow
- AGI and AutoGPT resurgence
- RAG will continue to be a focus
- GPT4 will be beaten by open source models. Special purpose models beat it already
- Self hosted and cloud hosted models will grow for security
- Small language models will grow
- Productivity will be enhanced rather than replaced
- Multi modal models will grow
- Cost efficiency will grow in focus

Sun, Jan 7, 2024. Tangi #todo #ask #think
- Domain-specific models being beaten by general purpose models is a phase. It will reverse towards domain.
  - AI will potentially help build and understand domain-specific models
- Models are evolving so rapidly that humans cannot interpret models. We need a process to interpret models!
- xAI, Responsible AI, Physics-guided or Knowledge-guided models (called grey box models) are therefore a trend
- CS papers
  - Don't review other papers, certainly not other fields.
  - Disregard measurement errors.
- When CS papers get applied to climate, manufacturing or biology, we'll worry about
  - Interpretability
  - Domain-specific mechanics. (Introduce that into the training as a constraint.)
    - Many domain experts are using AI to UNDERSTAND their process. Need to explore
  - Uncertainty
- IB adds context to make learning applicable. But that distracts from the core learning, and if there's a gap it widens
- Most data science courses teach "Python science", not data science. They teach a bunch of models. They don't teach how even one kind of model e.g. LSTM works.
- Most coaching programs today teach FAMILIARITY with problems, not critical thinking
- Most of current education will become redundant thanks to LLMs. For students AND teachers
  - Coding will become irrelevant
  - Cognitive thinking, reasoning, human relations, systems thinking will become more relevant
  - Troubleshooting will become more important. AI is not self-diagnosing. I would hire someone who can figure out something is going wrong, diagnose what's going wrong, and fix it
  - Hire for troubleshooting ability. Give a Q, an A, and ask them to figure out if it's wrong, why, and fix it
- All my exams and quizzes are open book, open ChatGPT. Onus is on me to give a problem that forces you to think.
  - Write a question paper that is ChatGPT proof.
- Exploring AI could be a ToK subject. "How to interact with an AI?"
  - We need a manual on how to use AI. Like Simon Willison says
  - Content doesn't suffice. You need pedegogy. What to serve you at what time, how, how to assess. Lots of businesses are filling this gap
  - Students get great confidence when a teacher points to online content and says, I"ll tell you WHAT to see" and COMPLEMENTS that in their class
- "The map is not the territory." Most people confuse sample mean for the actual.
- Parameter estimation -> Signal estimation -> State estimation
- Stats vs DL differ in that
  - There is no notion of a defined "truth". Hence reliability is not measurable
  - Parameters have no value. Hence interpretability is ignored.
- Read 2020 National Education Policy. It's quite modern.
- We need a manual on self-learning too
- Listening is not learning. You know only if you implement.
- Levels for students:
  - I can solve it.
  - I can explain why it works.
  - I can find alternatives.
  - I can apply it to a new area, reformulating (requires imagination.)
- For teachers, you also need:
  - Responsible learning (extra careful about what to teach and how to teach, to exceite them, to teach at THEIR level).
  - Show the universality and connecting to other concepts. E.g. noise reduction with FT is like using water to remove dirt. Transform to water domain, remove dirt, transform back to air domain. It's better than dusting clothes to remove clothes. Washing machine programs are just different models of removing noise in the water domain.
- Teach people who WANT to learn AND who will APPLY it long-term. That's what maximizes impact
  - Grad students are more satisfying that way.
  - Else, it is WASTED effort. (Not that it's a bad thing for the student, but the effort IS wasted for the teacher)
- Therefore, I believe students should have general engineering first, and let students pick specialization later. Some universitie are doing that.
- Students remember my philosophy more than my content. We impart character, not just knowledge.
- Astrology and horoscopes serve a different function. They provide explainability, not predictive ability. As the world becomes less explainable, the need for astrology will grow.
  - Explainability is about creating STORIES that fits data plausibly. It has nothing to do with data or truth.
  - Explainability and predictive ability and reproducibility are all different. Maybe, Science is about the latter two, less about explainability.
  - Astrology is a model. The map is not the territory. It's an explanatory, not a predictive model.
  - Therefore, my lessons are just explanations. Stats about experiments are STILL explanations. They are NOT reproducible or predictive. Hence not yet science
- The meaning of our life is the transformation we undergo in our lives
  - Read "The Journey of Souls" by Michael Newton. A hypnotherapist
- Try regression therapy / hypnosis. Record it and listen to it. Just for fun!

Sat, Dec 16, 2023. - Grab. Improving last mile delivery in maps. When did people pick up the phone, when should driver be allocated to minimize waiting time, layer on top of OSM. #future #gpu #ask #todo
- Singapore developers the Sea Lion 7b model
- Try VLLM with AWQ format. Can do batch inferencing. Needs a good GPU
- Amex prediction whether they can pay back in 1 year or 18 months. That choice is a business decision. In real time. Precompute individual score and use it as input to another model. Model must be explainable by regulation. Creates decision tree models therefore. Compliance team must agree if I can use a feature. Can't use gender. Age (in US, Canada);- high age is more risk. Can't use edu level in the US.
- Capture information from camera and use LLMs. Like traffic cameras mapping. Explore GIS from video cameras
- Grab tracks road closures and road accidents and whether a cycle can go on a road vs a bike vs a car
- All drivers have a front facing camera
- Drivers report road accidents by pressing a button
- Amex prices individual loans when selling to a collection agency
- buy a bike head camera!
- Playwright is a browser-based test framework. Supports recording.