The side door: How to skip applications and get hired using AI as your research assistant

I read most cold emails I get. Both from people looking to get hired and those trying to sell something.

I do it to see if anyone’s actually trying. 99% aren’t.

They send templates. Glorified resumes. Generic “I saw you’re hiring, I’m interested” messages that do nothing but waste everyone’s time.

If you’ve been sending applications into the void for months, there’s a better way. And AI can help, if you use it right.

The traditional approach Is broken

First, let’s be clear about what doesn’t work:

• Sending the same resume to 200+ companies
• Using generic cover letters with the company name swapped out
• Spamming hiring managers with “just checking in” messages
• Having AI write more of these generic messages, just faster

The fundamental problem? These approaches center around you in an environment that cares about them.

A better approach: Solve problems no one asked you to solve

After coaching hundreds of designers and watching what actually works, I’ve developed a framework that consistently gets responses, even in this brutal market.

The key insight: People hire problem-solvers, not resume-submitters.

Here’s the exact process I teach:

Step 1: Deep research

Take the company you want to reach and gather EVERYTHING:

• Recent funding rounds or financial news
• Current growth stage (pre-seed, Series A, public, etc.)
• Product reviews and social media mentions
• Their job descriptions
• Recent product launches or changes
• Competitor moves in their space

The goal isn’t just to find basic facts. You’re looking for context that reveals underlying challenges.

Step 2: Leverage AI for insight generation

Feed all this information into GPT (or Claude, or Deepseek) and clearly explain:

• Who you are
• Your relevant skills and background
• What you’re trying to accomplish

Then ask it to identify potential problems the company is likely facing that AREN’T explicitly mentioned in job descriptions.

Prompt it to focus on:

• Stage-specific challenges (e.g., a Series A company faces different problems than a public company)
• Non-obvious pain points that align with your skillset
• Competitive pressures or market shifts they might be responding to

Step 3: Using AI to read between the lines

This is where AI becomes your secret weapon. After gathering all that company information, explicitly ask the AI to:

“Based on this data, what are 3–5 challenges this company is likely facing right now that AREN’T mentioned in their job descriptions?”

For example, AI can help you spot:

• If they announced Series A funding “to scale into new markets” — their product needs to evolve for those markets (= design opportunity)
• If they hired a VP of Sales but no product marketers — they need sales materials (= content opportunity)
• If their blog suddenly focuses on enterprise — they’re facing new UX challenges (= research opportunity)

This is the exact value of AI in this process because it connects dots from public information to reveal unstated problems you can solve. These hidden challenges are your way in.

Step 4: Craft a message that gets responses

Next have AI help you draft a message using this specific formula:

1. Acknowledge a recent milestone: “Saw you just raised $10M Series A, congrats.”
2. Name a stage-specific challenge: “At this stage, pressure shifts from proving demand to scaling without leaks.”
3. Point out a specific product observation: “Noticed your pricing page makes users book a demo, while competitors let them self-serve.”
4. Hint at relevant experience: “I’ve helped teams solve this before by streamlining signups while keeping sales happy.”
5. Add a soft call-to-action: “If you’re building your design team, I’d love to chat.”

Step 5: Edit for authenticity

The final step, which most AI users skip, is to edit the message to sound like you.

• Cut jargon and marketing speak
• Add your personal voice
• Keep it concise (under 150 words)
• Make sure you actually understand everything in it

If you followed the steps correctly up to this point, the message should already be pretty good and need minimal editing.

Why this works when applications don’t

This approach succeeds because:

1. It diagnoses a real pain point (“Series A = must scale efficiently”)
2. It shows you’ve done your homework (specific product observations)
3. It hints at experience solving the problem (without overselling)
4. It makes it about THEM, not you (but includes a soft CTA)
5. It stands out in a sea of generic requests

Real world results

People who’ve used this framework have gotten responses from companies that never replied to their formal applications.

A designer I worked with applied to a company three times over six months. Nothing. Then she sent one message using this approach to their Head of Product. Interview within 48 hours.

Another used it to land conversations with four startups in a week after months of silence.

I’ve used it myself every single time I’ve had to look for something new.

Common mistakes to avoid

Even with this framework, people still make these errors:

1. Being too generic: “All startups struggle with scaling” is not an insight.
2. Making it about you: Lead with their problem, not your skills.
3. Sounding desperate: No “I really need a job” energy.
4. Going too broad: Target specific people with relevant problems, not entire departments.
5. Over-automating: Using AI to send 100 slightly-tweaked messages still feels mass-produced.

The ethics question

Some people ask if this approach is manipulative. It’s not. It’s actually more honest than traditional applications.

You’re leading with actual value and genuine insights rather than inflated resumes and exaggerated cover letters.

You’re showing what working with you would be like, not just claiming you’d be great to work with.

The AI warning

A final note: Don’t use AI to scale up bad outreach.

I see people using AI to send more generic messages, faster. That’s worse than doing nothing.

AI should help with research and insight generation, the hard parts most people skip , not with mass-producing mediocrity.

What’s next?

If this approach resonates with you, there are two paths forward:

1. Do it yourself: The framework is here. It takes work, but it works.
2. Get guidance: In Backchannel, I walk through this exact process step-by-step, with templates, examples, and direct feedback on your outreach in the community forum.

Either way, stop sending applications into the void. Start solving problems people care about.

The job market is brutal right now. But the path I’ve outlined above works regardless of economic conditions — because it’s built on a timeless truth:

People hire problem-solvers, not resume-submitters.

If you don’t know me — I’ve spent the last 10 years helping designers navigate layoffs, land roles, and get unstuck when nothing seems to work.

I’ve now built Backchannel: a simple but powerful system to help you stand out and actually get hired.

It’s $49 for access. That’s it. You’ll get the exact process I use to help people find jobs faster, with none of the BS.

→ Check it out here