KULDEEP LUVANI

The Harness

AGENT = MODEL + HARNESS

A free field manual for the engineering around the model: the loop, the context, the tools, the guardrails and the evals that decide whether an agent ships, and how to run all of it as a program. Every chapter has a live instrument you can operate.

7parts
11live instruments
Oct 2026last updated
MODEL EVERYTHING ELSE IS HARNESS

Contents · Harness engineering

Seven parts. One system.

Hold the model fixed, change what wraps it, and scores move by 3 to 30 points. In controlled studies the harness moves the number more than the model does. The harness is that wrapping, and this book takes it apart one subsystem at a time.

Portfolio · field work

Harnesses I've built

The book is the theory. These projects are where I tested it, mostly personal tools built around coding agents. Each one is tagged with the chapter it puts into practice.

MYCELIUM · SELF-ENRICHING KNOWLEDGE ENGINE

A knowledge network that grows its own specialists

Most memory systems store what you give them and hope retrieval finds it later. Mycelium works the other way round. It reads a body of notes and code, decides what is true, and organizes itself around what it has learned. Concretely:

  1. Perceive in layers. Each source passes through a pipeline: a cheap structural parse, then a deep extraction of entities, relationships and claims.
  2. Argue before believing. A separate adversarial pass challenges every extracted claim, and a consistency check tests it against what the graph already holds. Only reconciled facts get in, each with a confidence score.
  3. Remember like a living thing. Facts carry provenance and decay over time unless new evidence reinforces them, and duplicates are merged at three levels of similarity.
  4. Grow specialists from structure. Community detection finds dense clusters in the graph, and each cluster becomes a specialist agent that knows its region deeply.
  5. Route through a cortex. A second tier of meta-agents supervises the specialists and decides which ones to consult for a question.
Ch 2 · Context & memoryCh 5 · Verification GitHub ↗

CLAIM · DEVELOPER KNOWLEDGE OS

Memory that writes itself

A single-file, self-bootstrapping memory system for coding agents. Lifecycle hooks capture decisions and discoveries as you work, structure them into an entity graph, and inject a briefing at the start of each session, so every session begins where the last one left off. It stores plain markdown you own.

Ch 2 · ContextCh 3 · HooksGitHub ↗

CLAUDEGOTCHI · DEVELOPER WELLNESS PLUGIN

A harness for the human

A Tamagotchi-style companion that lives in the agent's status line and watches session length, velocity and frustration. Its intelligence runs as deterministic shell hooks at near-zero token cost, and the model only hears about it when you actually need to stop.

Ch 3 · Deterministic hooksGitHub ↗

BRAINCAST

Podcast intelligence

Transcript analysis and AI-assisted content predictions across podcast catalogues, with a full web stack behind it.

Ch 1 · PipelinesGitHub ↗

COCOSTORY

Stories for small humans

An interactive children's story generator that creates personalized, illustrated stories with AI-generated narratives.

Operator

Kuldeep Luvani

SOFTWARE ENGINEER · AGENT HARNESSES & AI PLATFORM TOOLING

I started in machine learning, with computer vision, NLP and recommender systems, back when the model was the whole product. Now I build the scaffolding around models: memory, hooks, knowledge graphs, and the verification loops that make an agent trustworthy.

I wrote The Harness because the most useful knowledge in this field is scattered across papers, engineering posts and incident write-ups. This is my attempt to put it in one place, in order, with the receipts.

Taking an agent to production? I like comparing notes on harness design, evals and guardrails. The fastest way to reach me is email.

GitHub @kuldeepluvani ↗ LinkedIn connect ↗ Email kuldeepluvani@gmail.com