The Curious Engineer

All blogs / AI / ML

Anup Jadhav

anup.io

I build AI agent systems that hold up in production. My focus is the agent harness: orchestration, durable workflows and observability.

AI / MLSoftware / engineering practice

’19’20’21’22’23’24’25’26
Posts
112 from 13 Jul 2019 to 6 Nov 2026
Posting
weekly (51 in the last year)
Kind
personal blog
Feed
https://www.anup.io/rss/

2026 43

  1. TIL: Claude Shannon's six ways to get unstuck
  2. TIL: Six ways to cut LLM costs
  3. Claudialect
  4. The Next Wave of AI Engineering Is About Everything Around the Model
  5. What is Jev? A Simple Primer on AI That Makes Decisions
  6. TIL: The AI Wall
  7. Defining an AI Agent
  8. TIL: What’s actually different about GGUF and ONNX?
  9. How I code with Claude Code
  10. One agent or many?
  11. From Prompt Engineering to Loop Engineering
  12. Who Still Understands the Code?
  13. Designing teams for an agentic world
  14. The Frontier of Agent Memory: From Recall to Experience
  15. Speculative Decoding
  16. Query, Key, Values
  17. How Modern Agent Memory Architectures Work
  18. Why Context Is Not Enough
  19. On Durable Objects, Orleans, and prior art for the agentic web
  20. TIL: Ads in AI chatbots are not just a UX problem
  21. Welcome to Middle Loop Engineering
  22. How fast does it serve? Throughput, latency, and picking the right GPU
  23. Fitting LLMs on Self-Hosted GPUs
  24. The Harness Is the Product
  25. How "Thinking" Models Actually Work
  26. Harness Engineering by Anup Jadhav
  27. We’re Being Too Loose With the Term “World Model”
  28. TIL: Quantisation
  29. Write Skills Like Workstations, Not Prompts
  30. How the Claude Code team designs agent tools
  31. Make Claude Code Review Its Own Plans
  32. Ship Prompts Like Software: Regression Testing for LLMs
  33. Four Ways to Grade an LLM (Without Going Broke)
  34. Your Golden Dataset Is Worth More Than Your Prompts
  35. Build LLM Evals You Can Trust
  36. Stripe's coding agents: the walls matter more than the model
  37. Deep Blue
  38. TIL: The real bottleneck in AI coding isn't speed
  39. TIL: Markov Language
  40. Become an AI Value Creator
  41. Claude Code Tips From the Guy Who Built It
  42. TIL: Learning New Tech With AI Assistance Might Backfire
  43. Temporal + LangGraph: A Two-Layer Architecture for Multi-Agent Coordination

2025 61

  1. AI's Naughty and Nice List
  2. Why AI Coding Advice Contradicts Itself
  3. The Context Advantage
  4. Engineering teams evolve from coders to orchestrators
  5. What It Takes To Serve 10,000 Queries A Day | Anup Jadhav
  6. Understanding Generative UI
  7. LLMs develop distinct trading personalities when given real money
  8. Senior Developers Are Better at Using AI Agents |Anup Jadhav
  9. pgvector doesn't scale
  10. TIL: How Transformers work
  11. Fine-Tuning makes a comeback
  12. How to read research papers
  13. Eliza Redux: A Real-Time Voice AI Crisis Support Agent
  14. Atlas Unshrugged
  15. Choosing an LLM Is Choosing a World-View
  16. Reasoning LLMs are wanderers rather than systematic explorers
  17. Stop Planning Your AI Strategy and Start Running Experiments
  18. Introducing AI Engineering Premium
  19. Horizon Length - Moore's law for AI Agents
  20. The boring secret to building better AI agents
  21. Representation Engineering with Control Vectors
  22. Rethinking RAG: Meta’s REFRAG
  23. Nobody Knows How to Charge for AI
  24. Pace Layering Framework
  25. MCP + A2A: The Protocols Making AI Agents Actually Work Together
  26. AI Agents Are Finally Fixing Real-World Code Security Problems
  27. Data in CSV Format Isn’t Always the Best for LLMs
  28. Prompt Engineering vs Context Engineering
  29. Why LLMs Confidently Hallucinate a Seahorse Emoji That Never Existed
  30. Goodbye Manual Prompts, Hello DSPy
  31. Nemawashi (根回し)
  32. AI agents are starting to do real work
  33. Cargo Cult Vibe Coding
  34. The Rubber Duck That Talks Back
  35. Why Your AI Agents Keep Breaking (And How Systems Thinking Can Fix Them)
  36. From CI/CD to CAI (Continuous AI)
  37. The Agentic Protocols That Will Define the Next Decade of Software
  38. When Regulators Embrace AI
  39. AI Agents Are Getting Twice as Capable Every 7 Months
  40. Guardrails for Agentic AI
  41. The End of Thinking (Again)
  42. Five Hypothesis On The Future of AI
  43. Vibe Coding, Revisited: From Weekend Chaos to Repeatable Craft
  44. Protocols for the Agentic Era
  45. Why AI Safety Is Harder Than It Sounds: Lessons from DeepMind’s AGI Strategy
  46. Architecting the Internet of Agents
  47. 10 Ways to Vibe Code
  48. Streamlining AI-to-API Communication: A Practical Guide to Model Context Protocol
  49. From Coding to Spec-Writing - Navigating AI's impact on Devs
  50. Choosing Between RAG, Fine-Tuning, or Hybrid Approaches for LLMs
  51. RAGEntic AI: A framework for AI Agents
  52. LLM Security 101: Defending Against Prompt Hacks
  53. The Art of Sampling: Controlling Randomness in LLMs
  54. Deep Dive into LLMs like ChatGPT by Andrej Karpathy - TL;DW version
  55. Thinking Smarter, Not Harder: How LLMs Can Learn on the Fly
  56. How to think about LLM Model Size
  57. Building, Breaking, and Rebuilding: My Journey to a Smarter RAG Application
  58. From ML to AI Engineering: Transforming How We Build AI Applications
  59. Building a Matrix-themed Chat Interface with Heroku's New Managed Inference API
  60. AI Agent Use Case Evaluation: From Risk Assessment to Implementation
  61. LLM Transformer Overview

2024 2

  1. What is an AI Agent?
  2. LLMCompiler - Towards parallel function calling

2022 1

  1. Anybody can learn to code

2021 2

  1. How I learned to stop worrying and love SecOps
  2. Invert, always, invert

2020 1

  1. Tracking Productivity

2019 2

  1. Documentation - your secret weapon
  2. From monolith to microservices - a journey