The hiring playbook is broken (and PE need to act fast)

Eighty percent of the hiring conversations I've had over the past quarter follow the same timeline. A portfolio company or mid-market operator reaches out, says they need to "build out the team," and hands me a job spec that could have been written in 2019.

That's the problem.

The roles they're hiring for - and the way they're hiring - haven't caught up with how work actually gets done today. Meanwhile, the companies moving fastest in our network have half the headcount and twice the output. Not because they found cheaper labor. Because they rethought what a team needs to look like when AI handles 40-60% of execution-layer work.

We push back hard on this, because DevriX provides the mid-market execution arm in the first 6-12 months, moving to a strategic unit working side-by-side with the new hires across different teams after. And since we hire and train the same roles, the playbook here had to change 2 years ago.

I’ve been very local about this for a while now:

• My agency recruiting article for Entrepreneur (Sep 2021)

• Integrating AI for business operations for Forbes (Apr 2024)

• Unshakable mental strength for effective leadership for Inc (Jul 2017)

• Hiring for senior leadership roles - roundup for Recruiter (Feb 2020)

• Soft skills for hiring top talent for AllBusiness (Jun 2019)

And hundreds of socials + blog posts in the process.

Here's what we're seeing on the ground, across PE portfolio companies and mid-market B2B operators scaling between $5M and $100M in revenue.

1. Velocity is the new headcount

The old model was simple: more revenue targets → more hires → more capacity. That math no longer holds.

We work with companies that compressed their sales cycle by 30% not by adding three more SDRs, but by deploying AI-driven lead scoring, automated outreach sequences, and a single senior AE who actually closes. The cost delta is massive. The speed delta is even bigger.

In a PE context, where hold periods are tightening, and operating partners are under pressure to show EBITDA improvement within 12-18 months, the question isn't "how fast can we hire" - it's "how fast can we execute with fewer, better people."

Every open req should come with a justification: why can't AI or automation handle 70% of this role? If you can't answer that clearly, you probably don't need a full-time hire. You need a workflow.

2. T-shaped operators beat deep specialists and generalists alike

There's a reason the best hires we've placed in the past year don't fit neatly into traditional JDs. And former entrepreneurs/consultants/freelancers have a special advantage in an “intrapreneurial” seat within a larger organization.

The talent that drives disproportionate value right now is T-shaped: deep in one domain (RevOps, product, engineering, GTM strategy) but broad enough to orchestrate AI tools, manage cross-functional dependencies, and move without waiting for three other departments to unblock them.

➡️ This is especially true in mid-market environments where you don't have the luxury of 15-person functional teams. You need a Head of Marketing who can also configure the HubSpot automation, prompt an AI agent for content drafts, analyze attribution data, and present a board-ready growth plan - all in the same week.

We've stopped recommending pure specialists for most mid-market roles under the VP level. The ROI isn't there. What works instead: a senior operator with a spike skill and the AI fluency to multiply their own output by 3-5x.

3. AI-first is not a perk - it's a filter

I've been saying this on LinkedIn for months: if a candidate can't show me how they use AI in their current workflow, they're already behind.

Internalizing AI as infrastructure is more important than ChatGPT parlor tricks.

1. Can they build a GPT-assisted research pipeline?

2. Can they use Cursor or Copilot and know when not to trust it?

3. Can they architect a workflow where AI handles the 80% and they focus on the 20% that actually requires judgment?

We now screen for this explicitly. The question isn't "do you use AI tools" - it's "show me your last three workflows where AI was embedded, and tell me where you deliberately overrode it."

The companies in our network that have made this a hard hiring filter are shipping faster, producing higher-quality output, and burning less cash on bodies that add process without adding velocity.

And knowing how efficient our own team has become, hiring is even more important now - with a difference in velocity being 10x to 50x to 100x at extreme cases (imagine an individual delivering a solid report/deck in an hour for what takes an old-school enterprise corporate worker 2 full weeks).

4. These roles are no longer relevant (and the replacements look different)

Here's where it gets uncomfortable for traditional org charts.

Roles that are rapidly losing relevance in mid-market and PE-backed companies:

• Dedicated data entry and reporting analysts - replaced by AI-driven dashboards and automated ETL

• Junior content writers doing volume-based SEO - replaced by AI content generation with senior editorial oversight

• Manual QA testers running regression suites - replaced by AI-assisted testing frameworks

• SDRs doing cold outreach at scale without personalization - replaced by AI sequencing with human-in-the-loop for high-value touches

• Project managers whose primary output is status updates - replaced by AI project tracking and async coordination tools

What's replacing them isn't "fewer people" - it's different people:

• Revenue architects who own the full funnel from lead scoring to expansion

• AI workflow designers who configure and maintain the automation layer

• Strategic account leads who combine relationship depth with data-driven decision-making

• Operator-engineers who sit between product and GTM, shipping integrations that directly drive revenue

The net effect: smaller teams, higher average talent density, faster execution cycles.

A hiring checklist for PE operators and mid-market leaders

Before you open your next req, run it through this filter:

1. Automation audit - Can 50%+ of this role's tasks be handled by AI or workflow automation? If yes, redesign the role or eliminate it.

2. T-shape test - Does this person need to operate across functions? If the role is narrowly scoped, question whether it survives the next 18 months.

3. AI fluency screen - Add a practical AI workflow exercise to your interview process. Non-negotiable.

4. Velocity justification - Will this hire accelerate time-to-outcome, or are you adding headcount to feel productive?

5. Cost-per-output math - Compare the fully loaded cost of the hire against an AI-augmented alternative. Include ramp time, management overhead, and attrition risk.

6. Portfolio pattern check - Are other portcos solving the same problem differently? Cross-pollinate before you hire.

The reality is that most mid-market companies and PE portfolio operators are still hiring like it's 2021. Big teams, narrow roles, slow ramp times, and zero AI integration in the talent strategy.

📈 Meanwhile, the fastest-growing companies are small teams generating outstanding results, shipping several times a day. They're hiring fewer people, paying them more, demanding AI fluency as table stakes, and building teams around velocity - not headcount.

If you're scaling a PE-backed company or running a mid-market operation and your hiring plan still looks like a spreadsheet of open reqs by department, it's time to rethink. Not incrementally. Fundamentally.

Mario

🧩 GTM stacks are getting messier. Teams keep adding AI tools on top of existing systems without rethinking the foundation. This creates more complexity, not speed. The better approach is simplification, not accumulation.

⚡ Headcount is no longer a growth strategy - execution speed is. We’re seeing companies compress sales cycles by 30%+ without adding a single hire - just better systems, automation, and fewer but sharper people. In PE, where time-to-value is everything, “how fast can we hire” is the wrong question. The right one: how much can we ship with the team we already have?

📊 Activity is not progress. Clean dashboards and automated flows look good, but they don’t guarantee revenue. More teams are starting to realize that motion without outcome is just noise.

🤖 The AI hiring gap is growing. Companies are still hiring for roles instead of workflows. The strongest operators today show up with systems they’ve already built and automated. If your hiring process doesn’t surface that, you’re screening for the wrong profile.

Most AI pilots don’t move the needle, validation does. While ~80% of companies experiment with generative AI, only ~40% report even modest EBIT impact; focusing on validation turns pilots into measurable value.

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Working with me

🌐 Scaling $30M - $100M+ mid-market companies with value creation through RevOps, data engineering, and WordPress. DevriX provides full RevOps consulting + delivery with GTM enablement for PE-backed portfolio companies, traditional tech, healthcare, finance, and professional service businesses pacing toward revenue growth initiatives. Our standard retainers between $10K and $60K include revenue lifecycle services for marketing and sales leaders, FP&A for financial teams, pipeline enrichment through websites and dozens of lead sources, automations and delivery integrations, CRO and ongoing testing, product delivery and platform integration solutions, and more through our consulting solutions.

🚀 1:1 Advisory retainers. At Growth Shuttle, I run two popular plans: Async Advisory ($3,500/mo) for $3M - $30M founders and executive teams and the smaller Strategic Growth Circle ($997/mo) for $100K - $500K entrepreneurs, agency founders, scale ups. My fractional executive plan is also available here.

📈 Building US LLCs from Europe. I help European and Asian founders scale faster through doola and their “Business in a Box” model. Also suitable for US citizens (given their bookkeeping solution), but in very high demand across Europe.

📊 Post-Merger Integration. We take on M&A initiatives with Flippa. Working closely on PMI retainers for PE companies and fast-growing startups integrating new companies within their portfolios, enabling data pipelines, and securing more deals through my personal network.