Claude Can Now Build Visuals Mid-Conversation. Here’s Why That Matters for Your Next Board Deck.

Anthropic shipped a feature this week that sounds incremental but isn’t: Claude can now generate interactive visualizations directly inside the chat window. If you’ve been using Claude for analysis or strategy work, you’ve probably hit the wall where a text-heavy answer needed to become a chart for a stakeholder meeting. That used to mean copying data into Excel or Power BI. Now you can go from question to polished visual in the same conversation.

Let’s look at a simple prompt, and the difference between its prior state explanations and its interactive visualizations. This is triggered by asking Claude to "show you" rather than just to "explain to you" an idea.

• Prompt: Explain to me compound interest.

• Model: Opus 4.6.

• Prompt: Show me compound interest.

• Model: Opus 4.6.

You can already see how powerful the visualization of the data is compared to the explanation. However, the demo example is compound interest; this is fine for a tutorial, but not revolutionary for senior business leaders.

However, imagine if you were to use this instead of Power BI, Tableau, or other data visualization tools for the following use cases:

• Competitive pricing analysis: Ask Claude to compare your pricing tiers against three competitors, then visualize the output as an interactive comparison your sales team can understand.

• Consumption vs. seat-based modeling: If you sell an enterprise product with multiple pricing structures, you can now illustrate the crossover points visually, inside the same thread where you’re building the model.

• Earnings prep and audit committee decks: Generate variance waterfalls or trend charts on the fly during prep, in your brand colors, without a BI team.

These visuals are shareable artifacts. You can embed them in presentations, hand them to a colleague, or iterate on the design with follow-up prompts. As you can see, the barrier between “analysis” and “communication-ready output” just got a lot thinner.

Let's see an example below regarding comparisons on pricing models (consumption vs. seat based vs. all-you-can-consume).

• Prompt: Show me revenue model that is comparing consumption based pricing to seat based pricing to enterprise all you can consume based pricing.

• Model: Opus 4.6.

WORTH NOTING

Senator Bernie Sanders Interviewed Claude About AI Risk

Senator Sanders published a conversation with Claude this week covering concerns around artificial intelligence regarding privacy, data manipulation, customer profiling, and the pace of AI deployment. Claude agreed with Senator Sanders that a moratorium should be placed on datacenter development due to these risks It’s a notable watch; however, it is worth flagging, that large language models tend to agree with their interviewer (which is part of what is known as AI sycophancy). Claude’s responses here reflect the dynamics of the conversation, not necessarily Anthropos’s corporate positions. However, the underlying questions about data privacy and algorithmic influence are real and worth tracking.

 https://www.youtube.com/watch?v=h3AtWdeu_G0

TOOL STACK - What I’m Using This Week

Primary Platforms

Claude (Cowork + Code) & Opus 4.6: The strongest model right now for both technical and business use cases. I’m using it for financial modeling, deck creation, Excel automation, and data visualization. Quickly becoming the default for enterprise-grade work.

Gemini NotebookLM: Google keeps updating this and adoption is outpacing Gemini itself. Best current use: upload presentations, lectures, or research, and get structured summaries, visuals, and Q&A against your own materials via its RAG model.

Agentic & Coding Tools 

Antigravity (AG): Google's release for agentic coding in plain language. It's main advantage is you can use Opus 4.6 through the platform. However, if Google pulls this or puts strong limits the platform will be less useful. From my personal experience, Gemini Pro 3.1 dramatically underperforms most enterprise use cases when compared to Opus 4.6.

OpenAI Codex: ChatGPT’s latest release for agentic coding in plain language. Performs well for Microsoft-native formats: Word docs, PowerPoint, etc.. Less competitive for full application builds or website deployment compared to Claude.

Teams Building Advanced AI Solutions

If your organization is past the experimentation phase and needs domain-specific implementation, these are teams I’d recommend talking to:

Numeric: Advisory team includes a former Big 4 partner. Focused on close and reporting automation - building products that meet real accounting specifications.

Tabot: Founded by a former Google AI engineer. Specializes in technical accounting and deal intelligence use cases.

Angela (Gaapsavvy) or I for Training: One of the best ways to get your organization upleveled in AI is to If you or your team needs hands-on AI training tailored to your actual workflows and use cases, send me a message. Happy to talk through what makes sense for your organization.

That’s it for this week. If this was useful, drop a comment or share it with someone on your team who’s evaluating these tools.

See you next Friday. — Devon