Using AI Agents to Create Research and Export to Productivity Suites

Every business has a hidden tax—manual research. For sales, business analysts, marketing and PR pros finding journalists, potential clients, or competitive insights still consumes hours that should go to execution. AI research agents eliminate that burden. They search, cross-reference, and export polished results across productivity suites—turning research from a bottleneck into a competitive advantage.

I looked for just the right Reddit thread, a LinkedIn or Facebook group, influencers, and manually searched for journalists who cover the relevant industry.

I spent time cross-referencing their recent articles, finding contact information, and building spreadsheets. The same tedious process whether I was prospecting for clients, researching competitors, or even planning where to eat during my summer vacation to St. Simon's Island, Georgia.

But those days are over now.

I spent some time setting everything up and now I use AI agents that can conduct this research automatically and export formatted results directly to Google Docs, OneNote, or Notion.

What used to take me hours or days now takes 30 minutes of agent setup and review. For example, last month I built a comprehensive press list for my new AI event in Charlotte, North Carolina, in 20 minutes.

The agent found 47 relevant journalists, their recent coverage, contact details, and even suggested personalized pitch angles—all exported directly to a Notion database ready for my team to use.

This isn’t about replacing humans but offloading time-consuming, menial tasks to machines.

It's about automating the research legwork so you can focus on relationship building, message crafting, and execution. When you get this workflow right, research transforms from a bottleneck into a competitive advantage.

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Turn hours of manual research into minutes of automated intelligence.

I've been testing two primary platforms for agent-based research: Manus.im and ChatGPT Agent Mode. Both can automatically export to Google Docs, OneNote, and Notion, but they have different strengths and cost structures that affect which one I choose for different projects.

Author’s Note: On October 6th ChatGPT made a number of announcements including their new AgentKit, agent builder. I’ll cover this in the future but for now we all have access to Agent Mode in the paid versions of ChatGPT. Moreover, read this great tutorial from We Love Open Source on creating AI self-portraits with Gemini, ChatGPT, and Stable Diffusion — it’s a fun example of what’s possible with multimodal AI.

Manus.im excels at complex, multi-step research with more connectors and integrations. It handles sophisticated workflows better and can complete tasks that would require multiple prompts in other systems. The downside? It's usage-based pricing, so I burn through credits quickly on large projects. There’s no monthly cap like ChatGPT, which makes it more expensive for heavy research.

ChatGPT Agent Mode offers more predictable costs with monthly limits, but fewer connectors and sometimes requires more manual guidance for complex research tasks. For straightforward research projects, it's often sufficient and more cost-effective.

Here's how I use both platforms for different types of research projects, with specific examples you can adapt for your needs.

Last month, I needed a press list for a B2B SaaS product launch targeting mid-market companies. Instead of spending hours manually researching journalists, I used Manus.im with this prompt:

The agent delivered a perfectly formatted Notion database sorted by type of outlet. I do have to use a little more work manually to verify some contact information, but what would have taken me 6 hours took 25 minutes.

The key difference: Manus.im handles the complex cross-referencing and personalization better, while ChatGPT Agent Mode works well for straightforward contact lists.

The same approach works brilliantly for sales prospecting. I recently helped a consulting firm build a prospect list for their AI implementation services. Here's the Manus.im prompt that generated 60 qualified leads:

The agent created a comprehensive spreadsheet with 73 prospects, complete with decision-maker contact info and personalized outreach strategies.

For vacation planning, I used a simpler ChatGPT Agent Mode approach for my St. Simon's Island trip:

The result was a perfectly organized dining guide that made our trip planning effortless. We hit 4 restaurants from the list and every one was excellent.

I'm always looking for opportunities to promote our All Things AI Meetup group in RTP, North Carolina. Finding relevant events, conferences, and networking opportunities used to take hours of manual research, then converting everything into a usable format was even more work.

Here's how I automated the entire process with Manus.im:

The agent found 34 relevant events and automatically organized them in a Notion database with all the contact details and partnership opportunities. What used to take me an entire afternoon now takes 20 minutes, and the database format makes it easy to track follow-ups and measure results.

Choosing the Right Platform and Quality Control

After months of testing both platforms extensively, here's when I use each one.

Use Manus.im when:

Use ChatGPT Agent Mode when:

Quality Control Checklist

Regardless of which platform you choose, always validate the results:

I always spot-check 10-15% of contacts or data points manually. For the press list example, I verified email addresses for the top 10 journalists and found 2 that were outdated—a 20% error rate that's typical and manageable.

Google Docs works best for collaborative research that needs team input. The commenting and suggestion features make it easy for multiple people to review and refine the results.

Notion is ideal for ongoing prospect management or any research that becomes a working database. The filtering and sorting capabilities make it easy to prioritize and track follow-up actions.

OneNote excels when you need to combine research with other project materials, images, or multimedia content. Great for comprehensive project planning.

For Manus.im, I've learned to be very specific in my prompts to avoid burning credits on irrelevant results. The more precise your initial prompt, the less back-and-forth refinement you'll need. Sometimes I even create a metaprompt in ChatGPT, then bring it back to Manus.im for execution.

For ChatGPT Agent Mode, take advantage of the monthly limits by batching similar research projects together. I do all my monthly prospect research in one session to maximize the value.

Common Mistakes to Avoid

Being too vague in prompts. "Find potential clients" won't work. "Find manufacturing companies with 100-500 employees that have announced digital transformation initiatives in the last 12 months" will.

Not specifying export format. Always tell the agent exactly how you want the data organized and which platform to export to.

Skipping quality control. Always spot-check a sample of results, especially contact information.

Using the wrong platform for the task. Save money by using ChatGPT Agent Mode for simple research and Manus.im for complex, multi-step projects.

Both platforms offer extensive connector ecosystems that make the research-to-productivity-suite workflow seamless:

ChatGPT Agent Mode can connect to your existing productivity tools through built-in connectors and the Model Context Protocol (MCP). As detailed in our ChatGPT Agent Mode guide, these connectors include Gmail, Google Calendar, Google Drive, SharePoint, GitHub, and more. The Model Context Protocol creates a universal standard for AI integrations, making it easier to connect ChatGPT with your business systems.

Manus.im offers a broader range of connectors and integrations (at least at the time of this writing), particularly for complex research workflows. The platform excels at connecting multiple data sources simultaneously and can export to various formats and platforms beyond the standard productivity suites.

The key advantage of both platforms is that they handle the technical integration work automatically, so you can focus on crafting effective research prompts rather than managing API connections and data formatting.

I've been using agent-based research for six months now, and it's transformed how I approach any project that requires information gathering. Whether I'm building press lists, prospecting for clients, or planning a vacation to St. Simon's Island, the workflow is the same:

The time savings are dramatic, but the real value is in the quality and comprehensiveness of the research. Agents can process more sources and cross-reference more data than I ever could manually.

Start with one small project this week. Pick something you'd normally spend 2-3 hours researching manually, and try the agent approach instead. You'll be amazed at what 30 minutes can accomplish.

I appreciate your support.