Anup Jadhav
Anup Jadhav
Agentic AI Engineering
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Anup Jadhav
Welcome, AI Engineers!

Welcome, AI Engineers!

👋🏽 I'm Anup. I'm an AI and Software Engineer building production Agentic AI and Generative AI systems. I work on RAG pipelines, multi-agent architectures, and multi-cloud deployments.

My newsletter, The AI Engineering Brief, covers practical AI engineering for people shipping real systems. X/Twitter/Bluesky: @anup.

The AI Engineering Brief Newsletter

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What is Jev? A Simple Primer on AI That Makes Decisions
jev

What is Jev? A Simple Primer on AI That Makes Decisions

Jev is a new kind of AI model designed for fast, structured judgments rather than open-ended responses. This nontechnical primer explains how Jev turns fuzzy decisions into probability-backed outputs that software can use.
Defining an AI Agent
AI Agents

Defining an AI Agent

An attempt to nail down the definition of the constantly evolving term: AI Agents
How I code with Claude Code
Claude Code

How I code with Claude Code

I have been coding with Claude Code for over a year now, and somewhere along the way I have developed
One agent or many?

One agent or many?

A practical guide for AI engineers choosing between single-agent and multi-agent systems, based on task structure, context and coordination costs.
From Prompt Engineering to Loop Engineering
Loop Engineering

From Prompt Engineering to Loop Engineering

If you spend any time watching this space, you have watched this vocabulary turn over three times in about a
Who Still Understands the Code?
Claude Code

Who Still Understands the Code?

AI coding agents make you dramatically faster. The cost they carry is quieter: a slow erosion of how well you understand the software you are shipping. Here is how I have come to think about that trade, and how I try to stay on the right side of it.
AI Engineering

Designing teams for an agentic world

AI coding agents are changing the economics of software development and the shape of engineering organisations. Here is how leaders should rethink build-versus-buy decisions, talent, team structure, platform strategy, and AI governance.

Recommended Resources and Tools

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Zed

Zed

My new favourite code editor.
Claude Code

Claude Code

My pair programmer in the terminal.
Obsidian

Obsidian

Where my second brain lives. Daily notes go in, post outlines come out.
Wispr Flow

Wispr Flow

How I dictate notes and posts when typing would slow me down.

Recommended Podcasts

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AI for Humans

AI for Humans

Educational, light-hearted discussions breaking down AI concepts
Google DeepMind: The Podcast

Google DeepMind: The Podcast

Research-focused, neuroscience-inspired models, safe and ethical AI
Latent Space

Latent Space

Technical updates, real-world engineering, foundational models
NVIDIA AI Podcast

NVIDIA AI Podcast

In-depth interviews on AI transforming industries

Shipped

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LLM VRAM Calculator
VRAM Calculator: 2026 LLM Tool

LLM VRAM Calculator

A free VRAM calculator for self-hosted LLMs that picks the smallest fitting GPU instance (H100, B200, A100 ) across FP16, FP8, FP4.
Eliza Redux: A Voice AI crisis support Agent

Eliza Redux: A Voice AI crisis support Agent

Voice AI crisis support chatbot that responds in under a second. Built and deployed in 90 minutes for a hackathon win. Handles natural conversation, breathing exercises, safety checks, and can locate nearby emergency services.

Side Projects

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Vision Transformer (ViT) Paper PyTorch Implementation
ViT: 2024 - Paper Replication

Vision Transformer (ViT) Paper PyTorch Implementation

PyTorch replication of the Vision Transformer paper. Applied transformer architecture to image classification to deepen my understanding of attention over patches.
EfficientNetB2 Computer Vision Model
EfficientNetB2: 2024 - Paper Replication

EfficientNetB2 Computer Vision Model

An EfficientNetB2 feature extractor computer vision model to classify images of food as pizza, steak or sushi. The model performs at 95%+ accuracy, and can classify an image at 0.03 seconds inference time per image.