Why Claude Is Currently the Best AI for Us in Our Day-to-Day Work

In a previous post, we mentioned that we use AI every day, but not everywhere and not without oversight. This time, we’ll take a closer look at a single tool that has become an integral part of our daily lives: Claude, the AI model from Anthropic.

No sponsorships, no partnerships. Just our honest take on why this particular tool stuck with us, while others disappeared after just a few weeks of testing.

We’ve been regularly testing new AI tools for a good two years now, often several at a time, usually over a period of two to three weeks as part of our ongoing project work. Most of them disappear from our toolkit again after this testing phase because they fall short precisely where it matters most in everyday work: when dealing with real, messy tasks rather than neatly prepared demo scenarios.

The market is crowded, but the differences are greater than marketing would have you believe

There are currently a number of powerful AI models. Most of them can write text, answer questions, and help with research. At first glance, many of them seem similar—almost interchangeable.

Anyone who works with these tools on a daily basis quickly realizes that, in practice, the differences are greater than comparison sites and marketing claims would suggest. One model writes faster, another thinks more thoroughly, and a third does a better job of adhering to a specified tone. These differences aren’t apparent in the demo, but only become evident after weeks of actual use.

For us, five points in particular have emerged as the ones that make all the difference. We’ll go through them one by one below, along with the specific situations in which we noticed them.

Before we get to that, a quick note on context: We are not independent AI testers, and this post is not a comparative test with a scorecard. It’s based on our experience as an agency with 175 projects that works with text, code, and client data on a daily basis. Other teams with different tasks will reach different conclusions, and that’s exactly as it should be.

Claude thinks for a moment before answering

Many AI models quickly provide an answer that sounds convincing but, upon closer inspection, has gaps. In our experience, Claude noticeably takes the time more often to actually think through a problem before formulating an answer. This makes a real difference, especially when it comes to more complex tasks such as a competitive analysis, a technical decision, or a strategic question.

This is also evident in the way Claude handles uncertainty. Instead of giving a confident—but possibly incorrect—answer to every question, Claude often points out when a statement is uncertain or when additional information is missing. For our work, this is more important than it might seem at first.

We need a tool that honestly shows its limitations, rather than appearing confident on every single topic. A model that never admits to being uncertain is not a reliable model. It’s just a self-assured one.

The texts don't sound like they were written by AI

Probably the biggest difference in everyday life is evident when it comes to writing. Many AI-generated texts are recognizable at a glance: formulaic sentences, interchangeable phrases, and a tone that fits everywhere but doesn’t quite fit anywhere.

Claude is much better at adapting to a specific voice. When we draft texts for clients, we specify the tone, rhythm, and style, and Claude sticks to them instead of falling back on the same old AI-sounding monotone. That’s exactly why we can use this tool for writing in the first place—so that not every text ends up sounding the same, no matter which company it was written for.

That doesn’t mean we accept every text as-is. As we’ve already explained in our post about the use of AI, every text is reviewed by a human before it reaches a client. But with Claude, the starting point is noticeably closer to what we actually need in the end. The difference between a good and a mediocre draft determines whether editing takes twenty minutes or two hours.

Claude works through tasks, not just questions

One area where there have been significant advances is AI’s ability not only to generate text but also to actually perform tasks. Claude reads and edits files, works with external tools, conducts research on its own, and completes multi-step tasks without us having to specify every single step.

For us, this means, specifically: Instead of asking a question and getting an answer, we describe a task, and Claude works through it on his own. This ranges from conducting research for a client pitch to preparing reports. This kind of autonomous work saves us a significant amount of time on precisely those tasks that used to require the most repetition.

One example of this is preparing a new proposal. We used to compile market data manually; now we describe the task once and receive a structured template that we just need to review and fill in. This doesn’t eliminate the task itself, but it does eliminate the most tedious part of it.

In the code, Claude sees the entire project, not just that one line

When building websites, we also use Claude for tasks related to code: recurring components, clean structure, and detecting errors in existing code. Claude understands not only individual lines of code, but also the context of an entire project. This makes a real difference, especially with larger websites.

This is especially true for tasks where context across multiple files is important. Instead of looking at each file individually, Claude recognizes connections and makes suggestions that actually fit with the rest of the project. This reduces errors and speeds up development overall without compromising quality.

One side effect we hadn't anticipated: Getting up to speed with code written by others—for example, when we take over an existing project—goes noticeably faster. Claude summarizes how a system is structured before we have to go through each file one by one ourselves.

For us, safety isn't just an afterthought

Anthropic, the company behind Claude, has focused strongly on the safe and responsible development of AI from the very beginning. This is evident in our day-to-day use of the model. Claude consistently refuses to respond to critical or harmful requests, but provides answers to normal work tasks without unnecessary restrictions. In our experience, this balance isn't always handled as well by other providers.

For us as an agency that works with sensitive client data and confidential project information, this aspect isn't just a nice-to-have. It's a prerequisite for using a tool in our day-to-day work at all.

This also applies to how errors are handled. No AI model is error-free, and that goes for Claude as well. The difference lies in how these limitations are addressed. In our experience, rather than presenting incorrect information with the same certainty as correct information, Claude more often indicates when a statement should be verified.

This approach is crucial to our work with customer data and public content. A statement that sounds convincing but is incorrect can cause more harm in a published text than one that is flagged as unreliable from the outset.

One Project, Two Approaches

Perhaps the difference is most clearly illustrated by a specific example. Let's take a new client project.

In the past, the preparation process would have looked like this: Someone on the team would manually research the market and the competition, type notes into a document, use those notes to draft a rough outline for the website, and then write placeholder text to be revised later. That was several hours of pure, tedious work before the actual conceptual work could even begin.

Today, we explain to Claude the background, the company, the target audience, and the general direction. Claude conducts his own research, summarizes the key findings, proposes an initial page structure, and provides draft copy that’s already close to our tone. We review, correct, and refine it. What used to take half a day is now done in a fraction of the time, without sacrificing quality.

The key point here is that we still made every decision ourselves throughout this process. Claude didn't do the thinking for us—he just took care of the groundwork, which used to be the most time-consuming part.

How Claude is actually integrated into our day-to-day work routine

It's easy to praise a tool. What's more interesting is the question of exactly where it fits into day-to-day operations, because that reveals whether the enthusiasm is genuine or just a fleeting moment.

For new projects, the initial research phase is now conducted almost entirely through Claude, from competitive analysis to summarizing existing client materials. For ongoing projects, Claude handles recurring tasks such as adapting components across multiple subpages or checking whether new content aligns with the existing tone. For internal topics, such as this post, Claude serves as the first point of reference for structure and wording before a team member takes responsibility for the final version.

The biggest change this has brought about isn't the number of tasks, but their order. In the past, we would first complete the routine work and then set aside time for the actual conceptual work—if there was any time left. Today, the conceptual work begins almost immediately because the preparatory work is done in parallel rather than beforehand.

We weren't convinced from the start

Like many others in the industry, we’ve tested, compared, and ultimately discarded various models. For a long time, our biggest concern was that, despite all the customization, AI-generated texts would eventually all sound the same, no matter which company they were written for. This concern was—and still is—justified when it comes to many tools.

What ultimately convinced us wasn’t a single impressive result, but rather the consistency demonstrated across many projects. When we give Claude the same clear instructions regarding tone and approach, the output actually varies across different client projects—adapting to each specific company rather than resulting in the same phrasing every time. It was precisely at this point that what had started as an interesting experiment became an essential tool in our day-to-day work.

Other tools still have their place, though

Honesty is important to us, so we’d like to add this: Claude isn’t automatically the best choice for every task. For certain creative image tasks, highly specialized data analyses, or specific niche applications, there are other tools that are better suited for those particular purposes. That’s why we continue to use a variety of tools in parallel, depending on the task at hand.

But what makes Claude special to us is the combination of sound reasoning, high-quality writing, the ability to work independently on tasks, and a responsible approach to the limitations of technology. We don’t find this combination in any other provider in this form. That may change—the market is evolving rapidly. But that’s where we stand right now.

What Makes a Difference in Your Projects

When we work with Claude, we work faster without compromising on quality. Research that used to take hours is now available more quickly. Drafts are produced more quickly while still striking the right tone. Development tasks that used to involve a lot of tedious manual work are now handled more efficiently.

The time we save is reinvested in what really matters: strategy, creativity, and the finer details that ultimately make a website or campaign successful. AI doesn’t replace decision-making or creative work for us. It gives us the freedom to focus precisely on those things.

You can also tell by how quickly we respond. If you need a last-minute adjustment or have a question about an ongoing campaign, we’ll respond faster because a large part of the groundwork has already been done. This isn’t just a minor detail—it’s something you actually notice in your day-to-day work, even without realizing which tool helped behind the scenes.

Conclusion: a tool, not a replacement

For us, Claude isn’t just a buzzword—it’s a tool that has proven itself in daily use across many projects. Reliable reasoning, well-written text, the ability to work independently, and a responsible approach to one’s own limitations. These are the reasons why we’ve stuck with it, while other tools have been tried and then discarded.

In the end, though, that’s exactly what it is: a tool. The decisions, the creativity, and the responsibility for the result still rest with us. Anyone who tells clients that AI will do the actual work is making a false promise. For us, it handles the groundwork so that we have more time for the actual work—not less.

We don’t know if that will still be true a year from now. The models are evolving rapidly, and perhaps in twelve months we’ll be writing a similar post about a different tool. Until then, however, Claude remains the model we entrust with our projects, our client data, and a good portion of our daily work—and that’s no small decision for an agency that thrives on trust.

Related: 3D on the Web: What’s Changing Right Now with the New AI Tools and Creating a Website with AI: When Lovable, Framer Agents, and the Like Are Enough—and When It Gets Expensive · Services: AI Consulting and Implementation

Curious to see how that works for your project?

We'd be happy to tell you where AI actually helps us and where we consciously choose not to use it. Just send us a quick message using the contact form. We'll respond within 24 hours—personally and without any sales pitch.