AI Hints
Home›Agentic AI Tutorial›Agents That Build
Agentic AI · Lesson 65 of 100

Working with Coding Agents

How professionals do it.

⏱ 2 min read▶ Video at 1:55:59🎓 Free
Watch this lesson in the Agentic AI courseWatch on YouTube ↗Full Agentic AI course

Two developers use the same coding agent. One gets broken code, and gives up. The other ships a week of work in a day. The difference isn't the tool. It's how they work with it.

Working with Coding Agents
From the video: Working with Coding Agents
  • Two developers, same agent
  • One gives up
  • One ships a week's work in a day

Habits that work

Here's what the best people do. They explore first, asking the agent to read the code, and to explain it, before changing anything. They ask for a plan, and they review it. They give it a way to check its own work, such as tests. They keep tasks small. And they read every line that's going to production.

Explore firstno code yet
Plan and reviewcatch mistakes early
Give it a checktests or a script
Small tasksone thing at a time
Read the diffyou're responsible

A weak request and a strong one

The way that you ask matters enormously. A weak request says, fix the login bug. A strong one gives the symptom, where to look, and how to prove that it's fixed. The agent can then check its own work, and you can walk away.

Weak

  • Fix the login bug
  • No context
  • No way to check

Strong

  • Login fails after a timeout
  • Look at auth/session.py
  • Add a failing test, then fix it

Manage the context

Context is the scarcest thing that you've got. As a session fills up, quality falls. So clear it between unrelated tasks. Use sub agents for wide searches, as they only report back a summary. And keep your project's instructions file short and useful. Everything we learned about tokens applies directly.

Clear between tasksfresh start
Sub-agents for searchsummaries come back
Short project fileit's always loaded
Watch the qualityit drops as context fills

Summary

Explore, plan, check, and review. Coding is one form of action. Next, an agent that writes code to answer questions about data.

Key takeaways
  • Explore before editing
  • Give it a way to check
  • Context is the scarce resource
Next up: Code as a Tool — the analyst agent