Supercharge your research with AI
A new trend is sweeping LinkedIn: users aren't just "#OpenToWork" anymore—now they're also using the "#Desperate" banner on their profiles. While more than 200 million people have the #OpenToWork option enabled publicly or privately, the new #Desperate trend is for users who want to up the ante further.
But here's the thing about desperation: it rarely works. Over my years of helping friends and former colleagues with job searches, I've learned that thorough research is what separates successful candidates from the rest. Earlier it used to mean spending weeks digging through company blogs, industry reports etc. Now, with AI as a research co-pilot, you can be just as thorough in a fraction of the time—transforming what was once a weeks-long process into something you can do in days.
Let me show you what I mean.
Imagine you're applying for a job at Asana, Notion, or another project management company. The old way would be to read their website, maybe check out a few Reddit threads, and call it a day. But AI lets you do something different: it lets you build a comprehensive understanding of the industry that would previously have taken weeks to develop.
Think of it like you having a team of AI research assistants. Each assistant has different strengths— Perplexity for factual research, Claude( Anthropic ) for analysis, ChatGPT ( OpenAI ) for brainstorming. Together, they help you build a complete picture of your target industry.
In this specific example, here's how I'd break down the research process::
This last part, strategy map, is crucial: Companies don't just want people who understand where the industry is—they want people who can see where it's going. It's about showing you can take disparate pieces of information—market trends, user behaviors, technological capabilities—and weave them into a compelling narrative about the future. When you can do that, you transform from just another candidate into someone who looks like they could help shape that future.
Let's explore each of these sections further, starting with the landscape analysis.
Understanding the Landscape
Fire up Perplexity (if you need citations; highly recommended) and craft a precise query. I like to start with something like this:
I want to understand how the project management space is evolving with Generative AI. First, give me the top 3 established project management tools and what makes each unique.
The beauty of this approach is that it gives you a snapshot of the current market leaders along with their unique strengths.
Actual thread: link
Now that you have understood major players, you would want to change gears and start developing an understanding of actual users these tools. This is important because successful products aren't built around features—they're built around people and their problems.
Finding the Personas
Let's dig deeper with another focused query. I like to ask Perplexity something like this:
For Monday.com and Asana, break down their primary user personas. Include specific job titles, day-to-day responsibilities, and most importantly—their core pain points. Then highlight where these personas overlap or diverge.
This kind of research often reveals fascinating patterns. You might find that while both tools serve project managers, they attract different types of PMs with different needs. Or that one tool has found unexpected traction with a particular industry vertical.
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The AI Acceleration
Now we want to see how Monday.com and Asana are using AI to reshape the experience for their specific personas and whether they are able to deliver upon this promise or not. Let's craft two strategic queries to understand both the promise and the reality:
For Monday.com, detail how they're using AI to transform work for their core personas. Specifically: How are AI features helping Project Managers and Operations Managers do their jobs differently? Include specific features, use cases, and any reported productivity gains.
Then, we'll check the ground truth:
What are users actually saying about these AI features? Share specific feedback or complaints from Project Managers and Operations Managers using Monday.com's AI capabilities.
This two-pronged approach gives us both sides of the story: how companies are try to increase value prop for its users and the ground truth - whether they are able to deliver on their promise or not.
The gap that we see above between promise and reality isn't a failure—it's an opportunity. It tells us that while AI features are becoming table stakes in project management tools, the real challenge isn't just adding AI. It's making it reliable, intuitive, and truly integrated into daily workflows. And that brings us to our final section: Your Strategy Map
Your Strategy Map
Now, let's transform our research into insight. Let's craft one final series of queries to help build our point of view. First:
Based on current challenges in AI-powered project management tools (reliability issues, integration problems), what are the key opportunities for improvement? Frame these as specific user problems that need solving.
Then, let's go deeper:
Looking at emerging trends in AI capabilities (especially large language models and autonomous agents), how might project management tools evolve in the next 2-3 years to address these challenges? Include examples of potential features or capabilities.
Finally, let's zoom out:
What broader shifts in how teams work might these AI developments enable? How might the role of a Project Manager or Operations Manager change as these tools become more sophisticated?
Notice what we're doing here: We're building a three-layer prediction—immediate opportunities, technical possibilities, and broader implications. This gives our strategy map both depth and credibility. When you weave these elements together into a coherent narrative about the future, you transform from a candidate who knows the industry into someone who could help shape it.
Some of the insights that we get include:
Closing Thoughts: From #Desperate to #Deliberate
What I've shared above isn't just a theoretical framework—it's the actual process I used to build this analysis in just a few hours. Yes, there's room for improvement, but that's exactly the point: being deliberate isn't about perfection, it's about structured progress.
The process we've walked through demonstrates something powerful: With AI as your research partner, you can compress weeks of research into hours. But—and this is crucial—AI isn't doing the thinking for you. It's helping you think better, faster, and deeper.
Instead of showing up to interviews feeling #Desperate, you arrive as someone who has been #Deliberate in their approach.
And here's the real magic: These skills compound. Once you learn to do this kind of strategic research for one industry, you can apply it to any domain. Each analysis makes you better at pattern recognition, helps you ask sharper questions, and builds your confidence in navigating complex spaces.
Remember: In a world where everyone has access to the same AI tools, the difference isn't in having them—it's in how deliberately you use them.
All the very best in your search. May your next interview be less about desperation and more about demonstration.