Towards AI

Built My Own MCP Server in 80 Lines of Python. Now Claude Knows My Sales Pipeline.

A year ago I wrote about building a tiny AI agent that uses MCP tools. It’s still the most-read thing I’ve published.

Your Knowledge Graph Is Measuring Your Pipeline, Not Your Subject: A Replication Attempt

I left a comment on a Medium piece a few weeks ago about agentic graph engineering across 82.8 million edges, the one about catching hidden vulnerabilities by walking task graphs, capability graphs, and run graphs instead of asking an LLM to reason over the whole mess.

Eight GPUs, Three Models, One Server: A Production Playbook for Self-Hosting LLMs on NVIDIA H20

Somebody on the team gets a local model running in an afternoon. One Docker command, one model name, and ten minutes later there’s a…Continue reading on Towards AI »

Meet Jev: The AI Model That Doesn’t Write, and Why Data Engineers Should Care

A plain-English guide to “System One” models, with patterns, code, and honest caveats

AI Agents Need More Than an LLM. Here’s the Full Stack

Learn the full AI agent stack: LLM, context, tools, memory, orchestration, runtime, guardrails, and observability. A clear guide to…Continue reading on Towards AI »

Understanding Similarity Measures / Metrics in Data Science

I’m writing this blog to give you a quick glimpse of the Similarity Metrics that we use in industry covering about why we need them, when do we use, what’s the intuition behind each metric and ending with some bonus tip to easily remember them.

ChatGPT Pro $200 Cut to 10x: is a Mac Studio Worth it for Local LLMs now?

I priced 50 days of my own $200 AI plan at API rates first. The number a Mac Studio has to beat is a lot smaller than $200.Continue reading on Towards AI »

RNNs Explained: How Neural Networks Understand Sequential Data

In the last article, CNNs showed us how a network can understand where things are in an image. But some data isn’t about space at all. It’s about order. Read this sentence backwards and it stops making sense. Shuffle a week of stock prices and the trend disappears.

Your Agent’s Guardrails Probably Fail Open. Microsoft Just Published a Contract to Fix That

Microsoft published Agent Hooks on August 27, 2026.Continue reading on Towards AI »

THIRSTDAY #7: WHERE CAN I ORDER THE EXPERIMENT MY AI JUST PROPOSED?

AI is becoming increasingly good at finding questions worth testing, but once the answer depends on samples, instruments and laboratory time, the work leaves the comfortable world of software and collides with the physical economy of science.

I Installed 40 Claude Skills. Three Survived.

superpowers has 291K stars — and it actively slows me down on half my work.Continue reading on Towards AI »

Redis for AI Agents: Memory, Queues, Checkpoints

Your framework is the brain. Redis is the hands. Here’s when the hands are overkill.Continue reading on Towards AI »

How to Write an Agent Eval Rubric: Why Your LLM Judge Averages 4.8 on Useless Replies

AI Models Are Starting to Communicate Without Words

Cache-to-Cache lets one LLM pass internal representations directly into another. What looks like an inference optimization may become…Continue reading on Towards AI »

How Jev Picks an Answer Without Writing One

Scoring instead of generating: what open Qwen2.5 experiments show about speed, accuracy and calibration, and how to build it on AzureContinue reading on Towards AI »

GPT-6 Astra vs Gemini 4 Argon vs Claude Fable 5.1: The Benchmark Winner Is the One You Can't Buy

Gemini 4 Argon beats GPT-6 Astra and Claude Fable 5.1 on most of the benchmark table Google published on September 30, and almost nobody…Continue reading on Towards AI »

The Desk Toy That Explains Pascal’s Triangle In Thirty Seconds

Pascal’s Triangle, Explained From ScratchContinue reading on Towards AI »

Making Intent Routing Explainable

Making Intent Routing Explainable: Calibrated Probabilities, Decision Records and a Four-Tier Cascade