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AI agents are unlocking new and BIGGER budget pools. A CEO I just interviewed for the Get Paid podcast told me that for every $1 a company spends on software, they will spend $9-12 on the labor arou…

LinkedIn post image: AI agents are unlocking new and BIGGER budget pools.

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Sales9 months ago

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Your Best SaaS Sellers Are Leaving 80% of the Deal on the Table. Not because they're bad. Because they're too good at what they've always done. Hear me out. Here is a classic example: 🔥 Seller dem…

LinkedIn post image: Your Best SaaS Sellers Are Leaving 80% of the Deal on the Table.

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Sales9 months ago

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“You don't buy enterprise software, you inject it into your corporate veins.” Quote of the week courtesy of Dave Kellogg on the latest episode of Get Paid. In markets with high switching costs, like…

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Product Strategy9 months ago

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I'm hosting a roundtable on Thursday. We'll be talking about how sales changes for AI companies vs traditional SaaS, and what tactics your peers are using to win more deals and get back to growth. W…

LinkedIn post image: I'm hosting a roundtable on Thursday. We'll be talking about how sales changes for AI companies vs traditional SaaS, and

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Sales9 months ago

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We are here to get all AI agent builders to grow - whether you are Saas company looking to re-ignite growth or a startup or solopreneur just building your AI Agent Paid will help you grow. Fast!

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AI9 months ago

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it's the Friday after Thanksgiving possibly the least productive non-holiday day in the year enjoy

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Work Culture9 months ago

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Topics & Content Focus

Primary Topics

Commercialization of AI agents in B2B SaaS (how to grow, package and sell AI agent products)Enterprise value capture from data and AI (headcount vs tools budgets, ACV expansion, ROI framing)Building AI execution teams inside established companies (A-team design, startup-speed inside enterprise)Modern B2B pricing and revenue models (outcome-based pricing, aligning fees to customer results)

Secondary Themes

Founder and CEO decision-making around AI adoptionData engineering and analytics backlogs as opportunities for AI agentsGo-to-market support for AI agent builders (from solopreneurs to SaaS scale-ups)Curating and amplifying insights from respected operators and investors

Industry Focus

B2B SaaS, especially data and analytics platformsEnterprise data engineering and analytics teamsAI agent builders and AI-native startupsRevenue leadership and GTM teams in venture-backed software companies

Content Categories

Case-study style breakdowns of real AI + data deals and budgetsMeta-strategy for AI adoption inside enterprises (org design, team structure)Sales and pricing strategy for AI and data productsProduct and platform evangelism for AI agents and related servicesCurated expert takes with added commercial and GTM context

Performance Insights

50%

Avg Engagement Rate

STABLE

Performance Trend

Best Performing Topics

Direct growth promises for AI agent builders and SaaS foundersOrg design to move at “startup speed” inside larger companiesOutcome-based pricing and accountability to customer results

Virality Signals

Concrete dollar and headcount numbers that dramatize the stakes (e.g., $4M budget unlocked, 20 engineers, 10x ACV)Clear transformation narrative from current state (backlog, slow shipping) to desired state (fast AI deployment, growth)Name-dropping credible operators, founders, and investors and framing their moves as playbooksSpeaking directly to a tightly-defined persona (AI agent builders, SaaS founders, CEOs) with promises of speed and growthSimple, outcome-focused messages rather than technical deep dives

Structure & Quality

100

Avg Length (Words)

MEDIUM

Depth Level

ADVANCED

Expertise Level

7/10

Uniqueness Score

Common Hooks

Direct questions that mirror CEO or founder concerns (e.g. how to set up an AI team, how to move faster)Bold or flattering statements about another expert’s insight (“drops a masterclass”, “Gold from…”)High-drama budget or outcome reveals (e.g. number of hires, size of budget, 10x ACV)Mission-driven declarations aimed at a specific persona (“We are here to get all AI agent builders to grow…”)

Common Endings

Aspirational framing that this success is repeatable (“this can be you!”)Excitement and endorsement of people or teams (“Super excited for the team…”)Implicit CTA to adopt the highlighted strategy or tool without a hard sellOpen-ended, letting the core idea or number sit as the takeaway (“let that sink in”)

Value Delivery Methods

Translating abstract AI hype into concrete budget and headcount strategiesHighlighting specific commercial levers (pricing models, ACV expansion, budget reframing)Offering lightweight, memorable frameworks (A-team / Series A team, headcount vs tools budget)Curating high-signal insights from respected practitioners and reframing them for AI and data foundersPositioning AI agents not just as tech, but as vehicles for revenue growth and efficiency

Formatting Style

Short paragraphs with heavy use of line breaks for rhythm and emphasisOccasional capitalization for emphasis (e.g. A Team, Series A Team, ACV up 10x)Sparse use of emojis and no heavy formatting gimmicksConversational punctuation (ellipses, exclamation marks) to keep energy highNumber-driven callouts (20 engineers, $4M budget, 10x ACV) set on their own lines

Audience & Tone

YES

Question Usage

0.6%

Response Rate

Detected Tone

Smart-casual operator who lives in the SaaS and data trenchesGrowth-obsessed AI commercialization evangelistRelatable expert who mixes boardroom topics with conversational languageOutcome-first strategist focused on dollars, headcount, and ACV, not just technologysemi-formalfirst-person

Interaction Style

Peer-to-peer tone that assumes the audience are operators, founders, or senior leadersAspirational and energizing, pushing readers to act like high-performing SaaS and AI companiesSupportive and collaborative, often celebrating others’ wins and approachesDirective when it comes to strategy (“Set up an A Team”, “Try outcome based pricing”)

Community Building Signals

Frequently spotlighting named individuals and companies as examples to learn fromUsing “we” language to create a sense of shared mission with AI agent builders and SaaS leadersPositioning the audience as part of a movement to capture the AI opportunity before smaller startups doReinforcing norms around accountability to customer outcomes and disciplined execution

Writing Style Patterns

Content Strategy

Hook: Direct questions that mirror CEO or founder concerns (e.g. hTone: semi-formalCTA: Soft, aspirational CTAs (“this can be you”, “Use t

Writing style breakdown

Core characteristics

Overall tone: conversational, high-energy, sales-savvy, and persuasive with a teaching/evangelizing bent.

- Feels like a hybrid of

SaaS/GTMSales operator giving tactical advice

Hype/evangelist for AI agents and new go-to-market motions

Thought partner/peer talking to founders, CROs, CEOs, and sellers

Style is direct and punchy, but not aggressive. Confident, opinionated, and very clear.

Emotional energy is high: lots of exclamation, urgency, and excitement, especially around opportunity and growth.

The style is not formal. It’s professional but relaxed, with occasional slang, lowercase starts, and broken rules used intentionally.

The voice is authoritative but friendly – more “smart peer who’s figured some stuff out” than “distant guru.”

- High energy, particularly in

Opportunity moments: “Paid will help you grow. Fast!” / “Split the $4M budget!”

Revelation or insight moments: “AI agents don't replace software. They replace work.”

- Moves between

Excited and hype-driving

Educational and explanatory

Lightly humorous and playful (e.g., “20!!!! data engineers.”, “Then think about what you will do with all that extra commission? 😄”)

Not melodramatic – it’s grounded in numbers, budgets, and practical GTM realities.

- Frequent use of

Rhetorical questions: “Why are you always hiring people?”, “Want to join?”

Imperative / directive sentences: “Stop asking: ‘What’s your software spend?’ Start asking: ‘What’s your fully-loaded cost per employee?’”

Contrast and re-framing: “AI agents don't replace software. They replace work.”

Emphasis lines: “let that sink in”, “This playbook works. That's why it's killing you.”

- Heavy use of concrete numbers and specifics

20 data engineers”, “at $200K a piece”, “$4M budget”, “2-5x higher ACV”.

Uses simple, accessible language even for complex ideas.

- Occasionally uses slogans / quotable lines

Use the headcount you already have. Give them all access to Maia. Clear the backlog.

The difference will break your addiction to the tools budget.

- Primarily second person (“you”) when advising or calling to action

If you’re a SaaS sales team selling in AI, you need to start fishing in the labor pool…

Run your next discovery twice.

- First person “I” used when

Sharing personal anecdotes or opinions: “I get this question from a lot of CEOs…”, “Even I caught myself doing this recently.”

Hosting or inviting to events: “I'm hosting a roundtable…”

- Occasionally third person to tell stories / case studies

A CEO I just interviewed…”, “His buyer shares that next year they will be hiring 20 data engineers…

- Direct commands are common

Stop asking… Start asking…”, “Use the headcount you already have.

- Suggestions show up but are still fairly direct, not hedged

Try outcome based pricing for at least a portion of your arr.

Manny Medina

Warm Analysis

Performance Overview

Top Posts by Engagement

Posting Patterns & Frequency

Best Performing Days

Best Performing Times To Post