Are you getting the most out of Agentic Coding Tools?

Software engineering is changing fast.

Agentic coding tools became widely available last year, and if you’re not using them today, you’re already behind. But many still struggle to move beyond the “fancy chat” experience.

Just like any tool in our engineering tool belts, knowing how to use it effectively matters.

🤖 Agents Are More Than A Better Chat

Last year, most were using tab-complete with a useful chat interface where you could ask questions, get suggestions, and maybe copy/paste into your code.

But agents can do much more than make suggestions — they can understand your codebase and act.

Instead of asking an agent:

“Can you suggest additional tests?”

Tell your agent:

“Create additional test cases, then run make tests and validate they pass.”

An agent can create tests, run them, inspect failures, adjust the implementation, and re-run the suite until it passes.

This isn’t about suggestions anymore; agents have more autonomy.

I think of coding agents as assistants working toward a shared goal. They do some work, you do some, and you iterate together.

🏆 Moving from Direction to Outcomes

A big mental shift is moving away from simple directions to defining an outcome with guidance & guardrails.

Agents don’t just perform a single task; they can execute multiple steps (and even parallelize them). You don’t need to spoon-feed each directive one by one.

Instead, define the outcome you want, along with guidance and guardrails.

The clearer you are on the outcomes, constraints, and context around what you are trying to do, the better the agent will perform.

📋 Examples: Real-world tasks I’ve asked Agents to handle

“Using the existing DB Driver X as a reference, create a set of table tests for driver Y. The tests should be structured similarly to the existing driver, surface any logic issues, concurrency issues, and act as a clear insurance against the defined interface.”

“Update CI workflows to Go 1.26.0, find and update any references to 1.25.6, then run tests to ensure everything still builds and passes”

I also use agents for mundane work like git commits and opening pull requests. They consistently produce better commit messages and PR descriptions than I would.

Agents don’t always get it exactly right, but with a bit of feedback and occasional adjustment, you can get a lot done quickly.

Avoid going down the rabbit hole of endless refinement, sometimes it’s better to reset with a clearer prompt.

👨‍🏫 Context is Key

If you want the best results from agents, you need to give them context.

Before I do serious work on a project, I have the agent:

• Read the Docs 📚
• Review the Architecture 🏙️
• Understand the Project Structure 📐
• Understand how to build, test, and run the application locally 👩‍🔧

The same steps that a human would take. Agents are no different.

(I’ll dive deeper into Agent files, skills, and effective ways to provide more context in a future post)

🧠 Final Thoughts

Engineers are doing amazing things with agents, and new capabilities are being added daily. But you don’t need to be at the bleeding edge to get more out of them (I certainly am not).

Don’t worry about the hype. Understand what these tools can do, making small adjustments in how you use them can drastically change what you get back.