Why Your AI Writing Still Sounds Robotic (+ The Fix)

💼 In Today’s 5-min AI Brief

• Your Everyday AI Toolkit: Turn text into studio-quality music with Suno

• Prompt of the Week: Teach your ChatBot to write like a human

• AI News You Can Use: ChatGPT’s new Study Mode makes learning more interactive

• What I’m Learning: How teams are building startups with AI at the center from day one

🛠️ Your Everyday AI Toolkit

From Text Prompt to Finished Track

Suno AI makes music production as simple as typing an idea.

• Turn a short prompt (“80s pop song about staying focused”) or your own lyrics into a fully-produced track vocals, instruments, everything done for you.

• Remix a voice memo: upload audio, extend it into a full song, clone your voice, or isolate vocals and instruments.

• You can even play with settings to shape mood, energy, and musical layers like solos or interludes.

For marketers, founders, or content creators, Suno is a clear example of how GenAI shrinks the gap between an idea and a finished product.

Demo: Check out a demo from Kallaway on how you can turn a voice memo into a track in seconds.

💭 Prompt of the Week

If you’re aiming to make your AI writing sound less robotic, try using this prompt to make your chatbot sound more natural by cleaning up tone, removing em dashes, and avoiding “this, not that” phrasing.

💡 AI News You Can Use

A New Way to Study: ChatGPT as Your Learning Partner

OpenAI’s new Study Mode in ChatGPT takes a more intentional approach to using AI for learning. Instead of giving you quick answers, it slows the process down so you can work through ideas with structure and clarity.

It works like a thoughtful study partner that:

• Guides you through concepts step‑by‑step, asking questions to check your thinking

• Adjusts explanations to meet you where you are - more detail if you’re ready for it, simpler framing if you’re not

• Builds in practice through short quizzes, hints, and prompts to help you retain knowledge

• Encourages reflection so you can connect ideas and draw your own conclusions

I see this as part of a broader shift in AI design away from tools that simply “do the work” and toward tools that help you think critically. For anyone looking to build lasting skills, this is where AI can be a real partner in your growth.

Last Week in AI

• Google Opal - Google’s brand new release lets you create AI mini‑apps by describing what you want, then refining it in a visual editor before sharing. Opal turns plain‑language prompts (or “vibe‑coding”) into functional mini‑apps, and from there, you can adjust prompts, add logic, connect tools, and iterate in real time without writing any code. For anyone who’s ever had an idea but stalled at the “how do I build it?” step, Opal could be the missing link between concept and launch.

📖 What I’m Learning

If you’re interested in what I’ve been digging into… check out:

1. Claude Code: How Two Engineers Ship Like a Team of 15 - If you’re just using AI to write bits of code, you might be missing the bigger win. Two engineers at Every walked through how they used Claude Code to ship a week’s worth of updates - by setting up workflows where each AI-assisted task made the next one easier. It’s a reminder that AI gets a lot more useful when you think in systems.

2. Testing EVERY Hyped AI Tool - I Only Kept Using These - Ras Mic and Greg Isenberg tested AI tools by actually building with them - shipping features, fixing bugs, and seeing what held up in real workflows. 

   Verdict: Claude Code came out on top for serious dev workflows, with Devin and CodeRabbit close behind as powerful assistants for small teams. Automation tools like n8n showed huge potential, but mostly for technically fluent users.

Final Thoughts

I hope you learned something new or have a new tool added to your list. And I love to hear about new applications of AI, so let me know what you're building!

Thaddeus