DEV Community: Matias Palermo

The ATS Black Hole: How to Use AI to Write a Resume That Actually Gets Read

Matias Palermo — Mon, 29 Jun 2026 10:00:43 +0000

You've spent hours perfecting your resume. You've tailored every bullet point, aligned your experience with the job description, and clicked "Submit" with confidence. Then — silence. No email, no call, nothing. What happened?

Chances are, your resume never reached a human. It got swallowed by an Applicant Tracking System (ATS) — software that scans, scores, and filters resumes before any recruiter lays eyes on them. Studies suggest that up to 75% of resumes are rejected by ATS before a human ever sees them. That's not a hiring process; that's a gauntlet.

The good news: AI tools can help you fight back — not by gaming the system dishonestly, but by writing smarter, more strategic resumes that communicate your value clearly and in the language these systems understand. Here's exactly how to do it.

What ATS Actually Looks For (And Why Most Resumes Fail)

Before you can beat the system, you need to understand it. ATS software parses your resume into structured data — name, contact info, work history, skills, education — and then scores it based on keyword relevance to the job posting.

The most common reasons resumes fail ATS screening:

Missing keywords from the job description (the system doesn't infer synonyms well)
Complex formatting — tables, columns, headers in text boxes, and graphics confuse parsers
Non-standard section titles — writing "Where I've Worked" instead of "Work Experience" throws off categorization
PDF formatting issues — some ATS systems still struggle with certain PDF exports

The fix isn't to stuff your resume with keywords. It's to align your language with the employer's language while maintaining authenticity. That's where AI becomes a genuine advantage.

Step 1: Use AI to Decode the Job Description

Most job seekers read a job posting once and start writing. Instead, treat the job description as a data source and use AI to extract what matters.

Try this prompt in ChatGPT or Claude:

"Here is a job description: [paste full JD]. Extract the top 10 hard skills, top 5 soft skills, and the 3 most repeated phrases or requirements. Format as a bullet list."

From a real Software Engineer posting, this might return:

Hard skills: Python, AWS Lambda, CI/CD pipelines, REST APIs, PostgreSQL
Soft skills: cross-functional collaboration, ownership mentality, clear communicator
Repeated phrases: "scalable systems," "fast-paced environment," "own end-to-end"

Now you have a keyword map. Your resume needs to reflect this language — not copied verbatim, but woven naturally into your actual experience.

Step 2: Rewrite Your Bullet Points With AI Assistance

Generic bullet points are ATS killers. "Responsible for managing a team" tells a parser nothing useful. AI can help you transform vague descriptions into achievement-focused, keyword-rich statements.

Use this prompt:

"Rewrite this resume bullet point to be more achievement-focused and include the keywords [list from Step 1]. Keep it under 20 words. Original: 'Managed backend development for e-commerce platform.'"

Before: Managed backend development for e-commerce platform.

After: Architected scalable REST APIs on AWS Lambda, reducing checkout latency by 40% across a PostgreSQL-backed e-commerce platform.

Notice what changed: specific technology keywords, a measurable outcome, and active language. That bullet now scores well for a Software Engineer role — and it's still entirely honest.

Do this for every bullet point. It's tedious manually, but with AI it takes minutes per role.

Step 3: Build an ATS-Optimized Skills Section

Many candidates bury their skills or list them inconsistently. ATS systems specifically scan for a skills section with clean, parseable entries.

Prompt to use:

"Based on this job description [paste JD] and my background in [your field], suggest a skills section for my resume organized into: Technical Skills, Tools & Platforms, and Core Competencies."

For a Marketing Manager role, the output might look like:

Technical Skills: SEO/SEM, Google Analytics 4, A/B Testing, Conversion Rate Optimization

Tools & Platforms: HubSpot, Salesforce, Semrush, Meta Ads Manager

Core Competencies: Cross-channel Campaign Strategy, Budget Management, Team Leadership

Why does this work? Because the exact terms "Google Analytics 4" and "HubSpot" appear in job postings — not "analytics software" or "CRM tools." Specificity is everything.

Step 4: Let AI Check Your Resume Against the Job Posting

Before you submit anything, run a compatibility check. This is one of the most underused AI applications in job searching.

Use this prompt:

"Here is my resume: [paste resume text]. Here is the job description: [paste JD]. Score my resume's keyword match from 1–10, list missing keywords that appear in the JD but not my resume, and suggest 3 specific edits to improve my ATS score."

This gives you a targeted gap analysis in under 30 seconds. You might discover you've been writing "data visualization" when every job posting in your field says "Tableau dashboards" — a small difference that costs you interviews.

Repeat this process for every job application. A resume that scores 9/10 for one role might score 5/10 for another. Tailoring isn't optional; it's the whole game.

Step 5: Format for Machines, Polish for Humans

AI can help you write strong content, but formatting mistakes will still sink you. Here's the checklist:

Use a single-column layout. Two-column resumes break most ATS parsers.
Stick to standard fonts — Calibri, Arial, or Georgia at 10–12pt.
Name your sections conventionally: Work Experience, Education, Skills, Certifications.
Save as .docx first. Even if you submit PDF, test your resume by pasting it into a plain text editor — if it looks scrambled, an ATS will read it the same way.

Ask AI to review your section titles:

"Are these resume section headers ATS-friendly? [list your headers]. Suggest standard alternatives for any that might confuse a parser."

Conclusion: AI Won't Get You the Job — But It'll Get You the Interview

The hiring process is imperfect, and ATS systems are blunt instruments. But understanding how they work — and using AI to align your resume with what they're scanning for — dramatically improves your odds of reaching an actual human.

The workflow is simple: decode the job description with AI, rewrite your bullets to match its language, build a targeted skills section, run a gap analysis, and format for clean parsing. Done consistently, this approach turns a generic resume into a targeted tool.

Start with your current resume and one job posting you genuinely want. Run through all five steps. You'll likely find 10–15 changes worth making — and that's exactly the kind of specificity that moves you from the rejection pile to the interview list.

Want ready-made AI prompt packs and guides? Check out my Ko-fi shop: https://ko-fi.com/agente10k

The 5 Emails Every Business Needs (And How to Write Them Faster With AI)

Matias Palermo — Mon, 15 Jun 2026 10:00:42 +0000

Most businesses send a lot of emails. Very few send the right emails.

There's a gap between companies that use email as a genuine revenue driver and those that treat it as an afterthought — a channel for announcements nobody asked for and newsletters that go straight to the promotions tab. The difference usually isn't budget or team size. It's knowing which emails actually move the needle and having a repeatable system to write them well.

That's where AI comes in. Not as a replacement for your voice or strategy, but as a force multiplier. With the right prompts and a clear framework, you can produce high-converting, on-brand emails in a fraction of the time. Here are the five types every business needs — and exactly how to write them with AI.

1. The Welcome Email

Why it matters: Your welcome email gets opened at roughly 4x the rate of a standard marketing email. It's the highest-attention moment you'll ever have with a new subscriber, and most businesses waste it with a generic "Thanks for signing up!" that does nothing.

What it should do: Set expectations, deliver immediate value, and give the reader a reason to keep opening your emails.

How to write it with AI: Give your AI assistant context about your brand, your audience, and what you promised in exchange for their email. A strong prompt looks like this:

"Write a welcome email for a SaaS company that sells project management software to small marketing agencies. The subscriber just downloaded a free 'Client Onboarding Checklist.' Tone: warm, professional, slightly witty. The email should: thank them for downloading, deliver the checklist link, tell them what kind of emails they'll receive from us, and end with a soft CTA to book a free demo."

The AI will draft a structured email in seconds. Your job is to inject your real brand voice, add a specific detail or two that only your company would know, and review the CTA for clarity.

2. The Nurture Sequence Email

Why it matters: Most leads aren't ready to buy the first time they hear about you. Nurture sequences build trust over time by educating, entertaining, or solving small problems — so that when the prospect is ready, you're the obvious choice.

What it should do: Provide genuine value without pushing a hard sell. Each email in the sequence should stand alone while also moving the reader one step closer to a decision.

How to write it with AI: Nurture emails work best when they're built as a series. Ask AI to plan the full sequence before writing individual emails:

"Create a 4-email nurture sequence for a B2B HR consulting firm. The audience is HR managers at companies with 50–200 employees. The sequence should: Email 1 — share a counterintuitive insight about employee retention. Email 2 — break down a common mistake companies make during performance reviews. Email 3 — share a short case study. Email 4 — transition to a soft pitch for a free 30-minute audit."

Once you have the structure, prompt AI to write each email individually. This keeps each one focused and prevents the bloated, kitchen-sink emails that kill open rates.

3. The Promotional Email

Why it matters: Revenue doesn't happen on its own. Promotional emails — done right — drive direct sales, event signups, and product launches without coming across as pushy or desperate.

What it should do: Create desire, address the most likely objection, and make the next step completely obvious. Every word should earn its place.

How to write it with AI: The key is giving AI a real offer to work with, not a vague one. The more specific your brief, the better the output:

"Write a promotional email for a 3-day flash sale on an online photography course. Original price: $297. Sale price: $147. The sale ends Sunday at midnight. The target audience is hobbyist photographers who want to go professional. Main objection to overcome: 'I don't have time for a full course.' The email should use urgency without being aggressive, highlight one specific student result, and have a single CTA button."

AI will give you a solid draft. Then A/B test the subject line — that's often where promotional emails win or lose before they're even opened.

4. The Re-engagement Email

Why it matters: Inactive subscribers drag down your deliverability and skew your metrics. A re-engagement campaign either wakes them up or cleans your list — both outcomes improve your email performance.

What it should do: Acknowledge the silence without being passive-aggressive, remind the reader of the value you offer, and give them a clear choice: stay or leave.

How to write it with AI: This is one of the trickiest email types to get right in tone. AI can help you thread the needle:

"Write a re-engagement email for a meal planning app. The subscriber hasn't opened an email in 90 days. Tone: honest, slightly self-deprecating, never guilt-tripping. The email should: acknowledge we haven't heard from them, briefly mention what's new or valuable in the app, and offer two options — a link to 'Stay subscribed' and a link to 'Unsubscribe.' Subject line should be unexpected and curiosity-driven."

Subject lines like "Is this goodbye?" or "We messed up — here's what changed" consistently outperform polished corporate alternatives in this category.

5. The Transactional Email

Why it matters: Order confirmations, shipping notifications, password resets — these emails get opened almost universally because they contain information the customer actually needs. That makes them prime real estate for reinforcing trust and planting seeds for the next purchase.

What it should do: Deliver the expected information clearly and quickly, then add one small layer of brand personality or value without overwhelming the primary message.

How to write it with AI: Transactional emails are often templated and forgotten. Use AI to audit and upgrade them:

"Rewrite this order confirmation email for an e-commerce brand that sells sustainable kitchenware. Current version: [paste your existing email]. Make it warmer, add one sentence that reinforces the brand's environmental mission, and include a subtle CTA to follow us on Instagram — but only after all the order details."

Small tweaks to transactional emails — a better subject line, one genuine line about your brand, a referral nudge at the bottom — can generate meaningful lift over time because of the volume they operate at.

Putting It All Together

These five email types cover the entire customer journey: acquisition, nurturing, conversion, retention, and re-engagement. Together, they form a system — not just a collection of one-off sends.

AI makes each one faster to produce, but the strategy still needs to come from you. Know your audience, define the one thing each email should accomplish, and give your AI tool enough context to actually do the job. Vague prompts produce vague emails. Specific, well-framed prompts produce drafts you can genuinely use.

Start with whichever type your business is currently missing. Add one email, measure it, then build the next. Within a month, you'll have a working email infrastructure that runs largely on its own — and a repeatable AI-assisted process to keep improving it.

Want ready-made AI prompt packs and guides? Check out my Ko-fi shop: https://ko-fi.com/agente10k

Why AI-Generated Content Is Quietly Outranking Human Writers in Google Search

Matias Palermo — Mon, 08 Jun 2026 10:00:45 +0000

The SEO world spent years insisting that AI content was a shortcut to penalties and a one-way ticket to Google's graveyard. That narrative is crumbling fast. Across industries — from SaaS blogs to e-commerce product pages to local service businesses — AI-generated content is not just surviving in search rankings. It's winning.

This isn't a fluke, and it isn't happening because Google suddenly stopped caring about quality. It's happening because the definition of quality in SEO has always been more technical than most writers want to admit — and AI is exceptionally good at the technical parts.

If you're still treating AI as a threat to human creativity rather than as a tool that can systematically outperform on search, you're already behind. Here's why the shift is real, what's driving it, and how to use it before your competitors do.

1. AI Produces Topical Depth at a Scale Humans Can't Match

Google's Helpful Content system doesn't just reward individual articles — it rewards websites that demonstrate deep, comprehensive coverage of a topic. This is where AI has an unfair advantage.

A human writer producing one 1,500-word article per week on "email marketing" will cover the basics and maybe one subtopic. An AI-assisted workflow can generate a full topical cluster in a weekend: a pillar page on email marketing strategy, supporting articles on subject line optimization, send time testing, list segmentation, re-engagement sequences, and deliverability troubleshooting — all internally linked, all targeting long-tail keywords the human writer never thought to research.

Concrete example: A B2B SaaS company in the project management space used an AI workflow to build out a 40-article topical cluster around "remote team productivity" in under three weeks. Within four months, the cluster captured featured snippets for 11 queries and drove a 340% increase in organic traffic to that section of the site. A single human writer working on that same topic would have taken the better part of a year to produce equivalent coverage.

2. AI Consistently Nails Search Intent Alignment

One of the most common reasons well-written human content underperforms in search is intent mismatch. A writer crafting a "guide to project management" might produce a thoughtful, engaging narrative piece — when Google's top results for that query are all comparison tables and feature lists because the intent is transactional, not informational.

AI content tools trained on search data align to intent by default. When you prompt an AI with a target keyword and ask it to analyze the SERP structure first, it produces content that mirrors the format, depth, and angle that Google already knows users want for that query.

Actionable step: Before generating any article, pull the top 5 results for your target keyword and note the content format (listicle, how-to, comparison, opinion piece). Feed that context into your AI prompt. The output will structurally match what's already ranking, which is the single fastest way to reduce the gap between publication and first-page visibility.

3. Consistency and Publishing Frequency Drive Compounding Returns

SEO is a compounding game. Sites that publish consistently — not occasionally — build domain authority faster, get crawled more frequently, and accumulate backlinks at a higher rate simply because there's more content to link to.

Human writers have limits: bandwidth, creative fatigue, sick days, competing priorities. An AI-assisted content operation doesn't. A solo operator running an AI content workflow can realistically publish three to five optimized articles per week. A traditional content team of the same budget might publish one.

Real-world comparison: A travel affiliate site relying on human freelancers published an average of 6 articles per month and plateaued at 12,000 monthly organic sessions. After switching to an AI-assisted workflow with basic human editing for accuracy and tone, they scaled to 22 articles per month. Twelve months later, monthly organic sessions crossed 85,000. Same niche, same domain, dramatically different output volume.

4. AI Doesn't Have Ego — and That Makes the Optimization Better

Human writers resist editing. They push back on keyword density suggestions, ignore heading structure recommendations, and sometimes prioritize stylistic choices over SEO fundamentals. AI content has none of those friction points.

Need to restructure an article because the primary keyword is buried in paragraph four? Done instantly. Need to add an FAQ section targeting People Also Ask boxes? Appended in seconds. Need to rewrite the meta description to include an exact-match phrase? No negotiation required.

This operational flexibility means AI content can be continuously optimized in response to ranking data. When Google Search Console shows an article ranking in positions 8-12 for a valuable keyword, an AI workflow can generate a revised, expanded version targeting that gap within hours — not weeks.

Example: An HR software company noticed their article on "employee onboarding checklist" was ranking #9 for that exact phrase. Using AI, they expanded the article from 800 to 1,800 words, added a downloadable checklist structure, and inserted semantically related terms their competitors were using. The article moved to #3 within six weeks.

5. Structured Data and Technical SEO Compliance at Scale

AI content generation doesn't just produce prose — it can be prompted to output articles pre-formatted for technical SEO requirements. Schema markup suggestions, internal linking structures, image alt text recommendations, and header hierarchies can all be built into the generation workflow.

Human writers rarely think about FAQ schema while drafting. AI can be prompted to output every article with an FAQ section formatted for structured data markup, automatically increasing the chances of rich snippet placement in search results.

Practical application: If you're running a recipe site, a legal information site, or any niche where structured data drives click-through rates, prompt your AI to output content that already follows the schema.org format for your content type. Then validate it with Google's Rich Results Test before publishing. This is something most human content teams implement inconsistently if at all.

6. The Quality Gap Is Closing — and Human Review Still Matters

None of this means you fire your editor and let the AI run unsupervised. The strongest AI content workflows combine generation speed with human quality control: a human reviews for factual accuracy, adjusts the tone to match brand voice, adds proprietary data or firsthand experience, and catches the occasional hallucinated statistic.

The competitive advantage isn't AI-only content. It's the hybrid model — where AI handles structure, volume, keyword alignment, and technical formatting, and a human adds the layer of credibility and authenticity that AI still struggles to manufacture at scale.

The sites winning in search right now are the ones that figured this out 12 to 18 months ago. The sites that are still debating whether AI content is "ethical" or "authentic" are watching their rankings erode in real time.

Start Building Your AI Content Workflow Today

The evidence is no longer theoretical. AI-assisted content operations are outperforming traditional human-only approaches on coverage depth, publishing consistency, search intent alignment, and technical optimization — all at once.

If you're running a content program for a blog, an affiliate site, a SaaS company, or a local business, the question isn't whether to incorporate AI into your workflow. The question is how fast you can do it before the gap between you and your competitors becomes impossible to close.

Start with one topic cluster. Pick your highest-value keyword category, map out 10 to 15 supporting articles, and use AI to generate a first draft of each. Add your human layer of review and publish consistently for 90 days. Then check your Search Console data. The results will make the argument better than any article can.

Want ready-made AI prompt packs and guides? Check out my Ko-fi shop: https://ko-fi.com/agente10k