Member-only story
Agent Harness — A complete guide
There isn’t much more to understanding Agent Harness than what's in here!
When we started interacting with LLMs back in 2023, life was simple. We simply asked a question and got an answer back. A typical example of a question from a programmer like me would be, “Write a function in Python to sort an array of numbers”. We get the answer in near real-time without the model going into thinking mode! Because the models were bare-bones LLMs without all the bells and whistles of today’s agentic systems.
Non-members can read for free here!
By bells and whistles, I am referring to tools, memory, skills, and many more that have become inevitable in 2026. All these add-ons are what make a simple LLM an AI agent.
The Agentic race on the one side
Back in 2023 and 2024, the race was about the models. OpenAI had one of the best general-purpose models, and Anthropic had one of the best coding models. Competitors constantly built models to beat other models in standard benchmarks like MMLU, SWE-bench, etc.
The model race started to saturate, and things like reasoning and context started…
