# @the.datascience.gal on Instagram

- **Type:** Image
- **Original URL:** https://www.instagram.com/p/DdDhoFnEcfB
- **Gondola URL:** https://gondola.cc/posts/70134732-thedatasciencegal-instagram
- **Thumbnail:** https://img.gondola.cc/tr:w-,h-,fo-auto/postThumbnails/04c5f3f9ef.jpg
- **Posted:** 2026-09-09T05:36:41.000+00:00
- **Account Owner:** Aishwarya Srinivasan | Data & AI | LinkedIn Top Voice (@the.datascience.gal) — https://gondola.cc/the.datascience.gal

## Caption

Your AI Agent Doesn’t Need a Better Model

The problem might not be the model. It might be the harness.

A harness is the system around the model that helps it actually complete useful work.

Think of it as the layer that provides:

Context — what information the agent can access
Tools — what actions it can take
Checks — how it verifies its work
Stop rules — when it should stop or hand control back

And there’s an important difference between three concepts:

Prompt engineering: What you ask the model.
Context engineering: What information the model sees.
Harness engineering: How the entire workflow runs, checks itself, recovers, and improves.

A reliable AI agent should be able to:

Read the right files
Make an edit
Run checks
Read the failures
Fix the issue
Check again
Hand control back when it can’t safely continue

The goal isn’t to make the agent run forever.

The goal is to make “done” verifiable.

If your AI agent keeps breaking things, stop asking only, “Which model should I use?”

Start asking:

“What does my harness need to do differently?”

Comment AI to get the full video on Harness Engineering.

#AI #AIAgents #AgenticAI #HarnessEngineering #PromptEngineering

## Stats

- **Views:** 0
- **Likes:** 59
- **Shares:** 0
- **Comments:** 9

## Tags

agenticai, aiagents, promptengineering, harnessengineering, ai

---
Copyright (c) Gondola