Building Your AI Toolbox: A Practical Guide to Using Claude, ChatGPT, and Copilot Together

Earlier this month I made the case that comparing AI platforms head-to-head misses the point. The question I keep seeing — "which AI is better?" — isn't really the question that matters. What matters is which tool fits the job in front of you.

That post seemed to resonate with people, so I want to go one step further. Because knowing that you should have an AI toolbox doesn't help much if you don't actually know how to use one. Owning a toolbox and knowing your workflow are two different things.

So here's what my workflow actually looks like, tool by tool, and the thinking behind it.

The problem with picking a "favorite"

Most of the AI discourse I see online is framed as a competition. Someone posts a benchmark, someone else posts a counter-example, and the comments turn into a debate about which platform "wins." I understand the impulse — we like rankings, they're easy to argue about, and picking a favorite feels like it saves you the work of thinking further.

But the ranking impulse breaks down the moment you actually try to use these tools for real work. A tool that's excellent at one stage of a task can be mediocre at another stage of the same task. If you judge it only on the stage where it's weak, you conclude "this AI isn't very good," when really you just used a screwdriver to turn a bolt.

The fix isn't finding the one tool that's good at everything. It's noticing that your work itself has stages, and matching the tool to the stage.

The three stages of a piece of work

When I look back at how I actually get things done, three distinct modes show up over and over:

1. Shaping the problem. This is the messy, early part — before you know exactly what you're building, sometimes before you're even sure the idea is a good one. You need something to push back on you, ask the annoying follow-up question, and help you find the holes in your own thinking.

2. Doing the real work. Once the idea is solid enough to act on, the job changes completely. Now you need depth and continuity — something that can hold the whole shape of a project, a codebase, or a document, not just one clever exchange.

3. Executing in the flow. This is the moment-to-moment part — writing the actual code, making the actual edit — where you don't want a conversation at all. You want something quietly keeping pace with you.

Three different jobs. Three different tools, for me.

How I actually use each one

ChatGPT, for shaping the problem. Before I write a line of code or open a document, I want to know I'm solving the right problem in the first place. I'll bring ChatGPT a half-formed idea — a technical approach, a leadership challenge, a strategy question — and use the back-and-forth to stress-test it. It's less "give me the answer" and more "help me find out where I'm wrong." That adversarial, sparring-partner quality is what makes it useful here. I'm not looking for agreement; I'm looking for friction.

Claude, for the real work. Once an idea turns into actual work — a project, a codebase, a document that needs real structure — that's when Claude takes over for me. It holds context across a whole piece of work rather than a single exchange, and that matters enormously once you've moved past brainstorming and into building something that has to hang together. Give it a technical problem or a messy codebase and it can work through it methodically rather than needing to be re-oriented every few minutes.

GitHub Copilot, for the flow. Copilot doesn't get a dedicated "session" the way the other two do. It's just there, inline, while I'm actually writing code — finishing a line, suggesting the next one, staying out of the way otherwise. It's less a tool I deliberately reach for and more a tool that's already in my hand when I need it.

The skill isn't prompting — it's routing

Here's the pattern underneath all of this: the tool changes as the work changes. Early-stage thinking, deep project work, and in-the-moment execution are three different modes, and trying to force one AI to do all three is where people get frustrated and conclude "AI isn't that useful for X."

It's not that the AI failed. It's that it was doing a job it wasn't built for.

I think this is where a lot of the "prompt engineering" conversation misses the bigger picture. Getting better at prompting one tool only gets you so far if you're using the wrong tool for the stage of work you're in. The more valuable skill — the one that's actually going to compound over time — is routing: recognizing what stage of work you're in and knowing which tool matches it, before you even open the app.

A rough framework, if you want one

If it helps to have something concrete, here's roughly how I decide:

• Am I not sure what I'm building yet? → Start with a sparring partner. Push on the idea until it either survives or falls apart.
• Do I know what I'm building, and does it require holding a lot of context across a real project? → Move to a tool built for depth and continuity.
• Am I already doing the work, and just need help keeping pace? → Use whatever lives inline, in the flow, with the least friction.

It's not a rigid rule, and there's plenty of overlap — any of these tools can do a decent job outside its "home" stage. But defaulting to this kind of routing has made my own work noticeably less frustrating, because I'm no longer expecting one tool to be everything at once.

The real competitive advantage

The future of AI probably isn't about picking one AI platform and becoming an expert in it. It's about building a toolbox and learning, almost instinctively, which tool to reach for depending on the job in front of you.

The real competitive advantage may not be having access to AI — at this point, most people do. It may be knowing which AI to use, when to use it, and how to move between them without losing momentum.

That's the part I'm still refining. But it's already changed how I work.

#ArtificialIntelligence #ChatGPT #ClaudeAI #GitHubCopilot #Leadership #SoftwareDevelopment #Technology

Thanks,

 

Michael Cronin

Website: https://www.michaelcronin.info

LinkedIn: https://www.linkedin.com/in/michaeltcronin/details/experience/

 

 

Building Your AI Toolbox: Why I Use Claude, ChatGPT, and GitHub Copilot Differently

There seems to be a constant debate happening around artificial intelligence: Which AI platform is the best?

Is it ChatGPT? Claude? GitHub Copilot? Something else?

I think we may be asking the wrong question.

I have spent most of my career working with technology, and one thing technology teaches you very quickly is that there is rarely one tool that is best at everything.

Think about the toolbox you have at home. You probably have screwdrivers, wrenches, sockets, pliers, hammers, drills, and dozens of other tools. Nobody opens that toolbox and asks, "Which one of these is the best tool?"

The answer would be obvious: It depends on what you're trying to accomplish.

I believe we should start thinking about AI the same way.

AI Is Becoming a Toolbox

Over time, I have found myself using Claude, ChatGPT, and GitHub Copilot differently.

There is certainly overlap between them. All three continue to evolve, and each can perform tasks that might traditionally be associated with another platform. But that doesn't mean they feel the same when you're actually working with them.

Each has developed strengths that make me reach for it in different situations.

Claude: When I Want to Build

Claude has become particularly interesting to me when it comes to software development.

When I have a coding project, existing codebase, technical problem, or something that needs to be built and iterated upon, Claude can be an extremely capable development partner.

What I find valuable isn't simply its ability to generate code. Writing code is only one part of software development.

Understanding an existing application, following dependencies, recognizing patterns, making changes without unnecessarily disturbing other parts of the system, troubleshooting problems, and iterating on a solution are often much more important.

That makes Claude interesting as more than a code generator. It can become part of the development environment itself.

For someone who understands technology but may not necessarily spend every day writing code, tools like this can also dramatically reduce the distance between having an idea and actually building something.

GitHub Copilot: AI Where Developers Already Work

GitHub Copilot approaches the problem from another direction. Instead of asking developers to leave their normal workflow and go somewhere else to interact with AI, Copilot brings AI directly into the development process.

That is an important distinction.

Developers already spend their days inside editors, repositories, pull requests, and development tools. Having AI available inside that environment makes it a natural companion.

It can assist with writing code, understanding unfamiliar code, generating tests, explaining functions, suggesting improvements, and handling some of the repetitive work developers deal with every day.

The value isn't necessarily replacing the developer. It's reducing friction.

A good power tool doesn't replace the carpenter. It allows the carpenter to accomplish more with the skills and experience they already have.

I see Copilot in much the same way.

ChatGPT: My Sparring Partner

My relationship with ChatGPT is somewhat different.

I certainly use ChatGPT for technical questions and coding. It is more than capable of helping in those areas. But where I personally find it particularly valuable is as a sparring partner for ideas.

Sometimes I don't need someone to give me an answer. I need something that helps me think.

I may start with a business problem, a technical strategy, a leadership challenge, an architecture decision, a product idea, or simply a half-formed thought. Then I start asking questions:

What am I missing? What assumptions am I making? What happens if we approach this differently? What are the risks? How would I explain this to an executive? How would I explain the same thing to an engineer? What would someone who disagrees with me say?

Those conversations can be incredibly valuable.

For me, ChatGPT becomes less of an answer engine and more of a thinking environment.

The AI doesn't have to make the decision. I still make the decision. But having something available that can challenge an idea, organize my thoughts, explore alternatives, and help turn a rough concept into something actionable can dramatically accelerate the thinking process.

The Tools Are Starting to Overlap

There is an important caveat to all of this: These categories are not permanent.

Claude can absolutely help with strategy and writing. ChatGPT can absolutely build and troubleshoot software. GitHub Copilot continues expanding beyond simple code completion.

The boundaries between these platforms will continue to move. Six months from now, I may use them differently than I do today.

And that's actually part of the point.

We shouldn't become so attached to a particular AI platform that we stop evaluating the tools available to us.

Technology changes. Our toolbox should change with it.

The Bigger Skill Is Knowing Which Tool to Use

For years, organizations have focused on teaching people individual technologies: learn this programming language, learn this database, learn this project management platform, learn this cloud environment.

Those skills still matter. But AI introduces another skill that I think will become increasingly important:

Tool selection.

The most effective AI users may not be the people who know the most prompts or subscribe to the most AI platforms. They may simply be the people who understand their problem well enough to choose the right tool for it.

Sometimes that might mean Claude. Sometimes GitHub Copilot. Sometimes ChatGPT.

And sometimes the best answer might be using all three during different stages of the same project.

Imagine starting with ChatGPT to challenge an idea and develop the requirements. Then moving into Claude to explore the implementation and work through the codebase. Then using GitHub Copilot alongside the development team as the solution is written, tested, reviewed, and maintained.

That isn't three competing AI platforms. That's a toolchain.

AI Doesn't Replace Experience. It Amplifies It.

There is another part of this conversation that I think sometimes gets lost.

AI can generate an impressive amount of information very quickly. But speed isn't the same thing as judgment.

Someone still has to recognize when an answer doesn't make sense. Someone still has to understand the business. Someone still has to recognize technical risk. Someone still has to understand customers, employees, budgets, deadlines, security, and all the other constraints that exist in the real world.

Experience provides that context.

AI can dramatically accelerate what an experienced person is capable of doing, but the person still needs to know where they're going.

A power tool in experienced hands can accomplish remarkable things. The same tool in inexperienced hands can create a remarkable mess.

AI isn't much different.

Stop Looking for the Winner

I don't believe there needs to be a winner between Claude, ChatGPT, GitHub Copilot, or whatever platform comes next.

Competition between these companies will continue, and that's a good thing. It will make the tools better. But as users, we don't have to participate in the rivalry.

We can simply use the best tool available for the job in front of us.

The screwdriver doesn't need to defeat the hammer. The socket wrench doesn't need to replace the drill. They simply need to be there when we need them.

That is how I increasingly think about artificial intelligence.

Build your AI toolbox. Learn what each tool does well. Understand where each one struggles. Experiment with how they work together.

And most importantly, don't become so focused on finding the "best AI" that you miss the larger opportunity.

The advantage isn't necessarily having access to artificial intelligence anymore. More and more people already have that.

The advantage will be knowing which tool to reach for, when to reach for it, and having the experience and judgment to know what to do with the result.

Thanks,

 

Michael Cronin

Website: https://www.michaelcronin.info

LinkedIn: https://www.linkedin.com/in/michaeltcronin/details/experience/