Dima Bilous
Founder @ Anfloy • Built 100+ AI Agents for GTM, content and internal ops • Sharing the workflows that scale revenue
Dima Bilous teaches B2B founders and sales ops professionals how to build AI agents that replace manual sales work, using contrarian claims and problem-solution frameworks that generate 75.9% comment engagement. His most distinctive move is opening with a role or workflow shift (not a product feature), then showing the old vs. new model with concrete numbers before revealing the AI solution.
3.3/wk
0 posts in 30d
582
avg per post
75.9%
comments / total
0.6%
reposts / total
problem-solution
Wed · 11 PM CET
Voice & tone
Direct, pattern-breaking, and technically credible without jargon. Dima writes like someone who just shipped something and is reporting back. Phrases like 'It's not an SDR. It's not an AE.' and 'You're not interrupting. You're responding.' show he leads with negation and reframing rather than selling. The tone is confident but not arrogant—he cites real examples (SaaStr, Trigify) and speaks to multiple personas in a single post.
Signature phrases
- “There's a new role taking over B2B sales.”
- “You're not interrupting. You're responding.”
- “The old model: → [list]. The new model: → [list].”
- “It's part sales, part ops, part technical.”
- “No templates. No guessing. Real context → real conversations.”
- “And companies can't hire them fast enough.”
Top 3 posts, dissected
Their highest-engagement posts, broken down line by line. Steal the structure.
There's a new role taking over B2B sales. It's not an SDR. It's not an AE. It's not even in most job boards yet. It's called a GTM Engineer. Here's why it matters: The old model: → 10 SDRs doing manual outreach → Each one handles 50-100 leads per day → Burnout in 6 months → High turnover, high cost The new model: → 1-2 GTM Engineers → Managing 20+ AI agents → Each agent handles a specific job (cold outbound, nurture, re-engagement, inbound) → Output of a 10-person team SaaStr tested this exact setup. 1.2 humans + 20 AI agents replaced 10 SDRs. $1M+ in pipeline in 90 days. The GTM Engineer is the person who: → Builds the AI workflows → Writes the prompts → Cleans the data → Monitors performance → Optimizes what's working It's part sales, part ops, part technical. And companies can't hire them fast enough. Why this matters for you: If you're a founder: This is how you scale outbound without hiring 10 SDRs. If you're in sales: This is the skill set that makes you irreplaceable. If you're in RevOps: This is your career path for the next 5 years. I put together a list of 20 AI agents you can build for your GTM strategy. The exact ones top teams are using for cold outbound, lead enrichment, follow-ups, and more. Same results. No 10-person team required. Want the list? Like this post Comment "ENGINEER" and I'll send it over. (Due to the response on this post, I can’t keep up with all the comments. If you want the list of the 20 AI agents mentioned, connect with me and send “engineer,” and I’ll share it - thanks!) ♻️ Repost if your network needs to see this. Anfloy
There's a new role taking over B2B sales.' stops scroll because it's a macro claim (not a feature), uses present tense urgency, and immediately creates a knowledge gap. Readers want to know what role and why it matters to them.
Negation hook → role reveal → old vs. new model (side-by-side bullets) → proof point with numbers → role definition (what GTM Engineer does) → persona-specific CTA (3 branches: founder, sales, RevOps). Long-form (180-350 words) allows full narrative arc.
- Negation pattern (It's not X, not Y, it's Z) creates anticipation
- Arrow bullets (→) for speed and visual rhythm in model comparison
- Specific number proof (1.2 humans + 20 AI agents, $1M+ pipeline in 90 days) anchors credibility
- Role definition broken into three parts (builds, writes, cleans, monitors, optimizes) shows depth without overwhelming
- Three-persona close (founder, sales, RevOps) multiplies relevance and comment hooks
Ends with 'I put together a list of 20 AI agents you can build for your GTM strategy.' This is a soft CTA that promises a resource, driving comments from people asking for the list or debating the premise. No hard sell—just a next step.
Open with a macro shift (role, workflow, market trend), not a feature; use side-by-side old/new models to make the contrast visceral; close with a resource promise that invites follow-up questions.
I stopped cold outreach. Now I only use 2 AI agents to find people who WANT to hear from me. Cold outreach means messaging strangers and hoping they care. Signal-based outreach means finding people already talking about your topic, engaging with competitors, or asking for solut…
'I stopped cold outreach. Now I only use 2 AI agents to find people who WANT to hear from me.' works because it's a personal behavior change (credible) + a reframe of the problem (signal vs. cold). The word 'WANT' in caps signals emotional resonance, not just efficiency.
Personal behavior hook → problem redefinition (cold outreach vs. signal-based) → reframe statement (You're not interrupting) → two agents with bold headers → agent 1 breakdown (tool, capability, prompt example) → agent 2 breakdown (output, example contrast) → tool mention (Trigify) → soft CTA. Long-form (180-350 words) allows two full agent explanations.
- Personal 'I stopped' opening creates authority and relatability
- Reframe statement ('You're not interrupting. You're responding.') is a mindset shift, not a tactic
- Bold headers (𝗔𝗴𝗲𝗻𝘁 𝟭: 𝗧𝗵𝗲 𝗦𝗶𝗴𝗻𝗮𝗹 𝗛𝘂𝗻𝘁𝗲𝗿) use formatting for visual hierarchy
- Contrast example (Not: 'I saw you work at...' But: 'Your comment about CRM data...') shows the quality difference without preaching
- Tool mention (Trigify.io) feels like a discovery, not a sponsor plug
Ends with 'If you're a founder, sales...' (truncated in data, but follows the three-persona pattern). The CTA is implicit: try this method. Comments spike because readers ask 'How do I set this up?' and 'What's the cost?'
Reframe the problem before selling the solution; use contrasting examples (not/but) to show quality gaps; mention tools as discoveries, not endorsements; let the mechanism speak louder than the outcome.
I stopped cold outreach. Now I only use 2 AI agents to find people who WANT to hear from me. Cold outreach means messaging strangers and hoping they care. Signal-based outreach means finding people already talking about your topic, engaging with competitors, or asking for solut…
'I built a 4-agent AI sales team using Opus 4.6 Agent Teams.' is a bold statement hook that works because it's specific (4 agents, named tool), concrete (built, not theoretical), and immediately shows a system, not a feature. Readers want to reverse-engineer it.
Bold statement hook → capability summary (four agents, parallel operation) → context shift (before vs. after AI) → agent team explanation (how they coordinate) → four-agent breakdown (Researcher, Analyst, Writer, Coordinator with specific outputs) → implied CTA (build this). How-to guide format (14% of posts, avg 861 eng) with step-by-step agent roles.
- Bullet summary (→ One researches, → One analyzes, → One writes, → One coordinates) creates visual momentum
- Before/after framing (Before: one conversation at a time, Wait. Ask. Wait. After: Agent Teams flipped that) shows the leap
- Plain English instruction ('You describe the team you want in plain English') lowers the barrier to entry
- Agent role breakdown with specific outputs (Researcher builds intel brief, Analyst scores on ICP fit, Writer crafts custom outreach, Coordinator prioritizes and sequences) shows depth and coordination
- Coordinator role as the 'runs the show' agent adds a meta layer of sophistication
Truncated in data, but the structure implies 'Here's how to build this.' Comments spike because readers ask 'Can you share the exact prompt?' and 'How long does this take to set up?'
Lead with a specific build (tool + number of components); show how the system coordinates (not just what each part does); use before/after to highlight the leap; let the mechanism be the story.
What drives their engagement
Dima's posts generate 75.9% of engagement as comments (not likes) because he leaves gaps. He shows the system but not the full prompt. He mentions the tool but not the setup cost. Readers comment to ask 'How do I do this?' and 'What's the next step?' This is intentional—the post is the hook, the comments are the conversation.
Repost rate is only 0.6%, which is low. This suggests Dima optimizes for reach and comment depth, not viral spread. Posts that get reposted tend to be the role-shift posts (GTM Engineer) because they're macro-level insights that feel shareable as 'this is happening in my industry.' Contrarian claims about job market shifts outperform tactical how-tos on reposts.
Low savability signal. Dima's posts are designed for immediate engagement and conversation, not reference. Readers don't save 'Here's how to build a 4-agent team' because they want to comment and debate it now, not revisit it later. The posts are current-moment insights, not evergreen guides.
Content pillars
AI Agent Workflows for Sales
35%How to build multi-agent systems that handle cold outreach, nurture, re-engagement, and prospect research without hiring more SDRs.
Role Evolution in GTM
25%Emerging job titles and skill sets (GTM Engineer, AI ops roles) that are replacing traditional sales structures and why founders should care.
Signal-Based vs. Cold Outreach
20%Tactical shift from spray-and-pray messaging to finding warm prospects already talking about your solution on social platforms.
AI Tools and Integrations
15%Specific tools (Claude, Opus, Trigify MCP servers) and how to wire them together into functional sales systems.
Case Studies and Proof Points
5%Real numbers from companies (SaaStr: 1.2 humans + 20 AI agents replaced 10 SDRs, $1M+ pipeline in 90 days) that validate the shift.
Hook patterns
Role Negation + Reveal
It's not [old role]. It's not [old role]. It's [new role].
“It's not an SDR. It's not an AE. It's not even in most job boards yet. It's called a GTM Engineer.”
→ Breaks pattern by denying what readers expect, creating curiosity about what replaces it.
Behavior Flip + Outcome
I stopped [old behavior]. Now I only use [new method] to [desired outcome].
“I stopped cold outreach. Now I only use 2 AI agents to find people who WANT to hear from me.”
→ Personal credibility + immediate contrast makes readers want to know the mechanism.
System Build + Capability Stack
I built a [number]-agent [system] using [tool]. → [Agent 1]. → [Agent 2]. → [Agent 3].
“I built a 4-agent AI sales team using Opus 4.6 Agent Teams. → One researches prospects. → One analyzes fit and timing. → One writes personalized outreach. → One coordinates the entire operation.”
→ Concrete deliverable + visual breakdown signals actionable depth.
Contrarian Claim + Proof
[Contrarian statement]. [Proof point with numbers]. Why this matters for you: [3 persona-specific reasons].
“There's a new role taking over B2B sales... SaaStr tested this exact setup. 1.2 humans + 20 AI agents replaced 10 SDRs. $1M+ in pipeline in 90 days.”
→ Claim alone generates debate; numbers prevent dismissal and anchor credibility.
Problem Reframe + Mechanism
Cold outreach means [old definition]. [New method] means [redefined approach]. You're not [old outcome]. You're [new outcome].
“Cold outreach means messaging strangers and hoping they care. Signal-based outreach means finding people already talking about your topic... You're not interrupting. You're responding.”
→ Reframing the problem itself (not just the solution) makes readers feel smarter for adopting the new frame.
Before/After Workflow
Before this, [old process]. [New tool/method] flipped that. Here's my setup: [breakdown].
“Before this, AI was one conversation at a time... Agent Teams flipped that. You describe the team you want in plain English.”
→ Acknowledges the old way (no dismissal) then shows the leap, making adoption feel inevitable.
Top-performing hooks
“There's a new role taking over B2B sales.”
→ The post combines a trend-jacking hook around an emerging role (GTM Engineer) with a compelling old-vs-new framework and specific proof point ($1M pipeline in 90 days), then segments the audience by p
“I stopped cold outreach. Now I only use 2 AI agents to find people who WANT to hear from me.”
→ The post reframes cold outreach as outdated and positions AI-powered signal-based outreach as the superior alternative, creating a clear before/after contrast that resonates with sales professionals.
“I built a 4-agent AI sales team using Opus 4.6 Agent Teams.”
→ The post combines a compelling technical walkthrough with a concrete result (20 prospects researched for ~$100/month), making the value tangible, while the comment-gated lead magnet ('Comment HIRED')
“I get 50-100K impressions weekly on LinkedIn.”
→ The post combines a compelling results-driven hook (50-100K impressions) with a highly structured, easy-to-scan numbered list of 7 AI agents that creates curiosity and perceived value, then funnels th
“Just wanted to introduce my new hire.”
→ The post opens with a curiosity-driven hook ('my new hire' being an AI agent) that compels readers to keep scrolling, then builds credibility through a specific walkthrough and a compelling anecdote s
“I collected 300 AI agents over the past year.”
→ The post uses a high-value free resource (300 AI agents list) as a lead magnet with a frictionless CTA (comment 'LIST'), while the categorized breakdown across business functions ensures broad relevan
“I built 7 AI agents that replace $300K+ in hires for my company.”
→ The post combines a jaw-dropping financial claim ($300K+ in savings) with a highly structured, skimmable list of 7 specific AI agents that each solve a recognizable business pain point, making the val
“Apollo just dropped an MCP server for Claude.”
→ The post leverages a timely product announcement to deliver three highly specific, actionable agent blueprints that make the reader feel they're getting insider knowledge, while the comment-gated lead
“I went from 200 impressions to 300K in 30 days.”
→ The dramatic before/after transformation (200 to 300K impressions) creates immediate curiosity, the numbered rules deliver tangible value that builds trust, and the lead magnet CTA ('Comment 30DAYS')
“Just wanted to introduce my AI team.”
→ The post uses a relatable 'meet my team' framing to make abstract AI tooling feel tangible and aspirational, while the numbered agent breakdown delivers immediate perceived value. The comment-gating C
What works
- Contrarian claim hooks (9 posts, avg 866 eng) outperform bold statements (19 posts, avg 574 eng) by 51%. 'There's a new role taking over B2B sales' and 'I stopped cold outreach' work because they flip expectations, not because they're shocking.
- Problem-solution format (49% of posts, avg 658 eng) is the backbone. The formula is: old model (with numbers) → new model (with numbers) → why it matters to you (three personas). This structure drives both reach and comments.
- Side-by-side old vs. new comparisons (→ bullets) create visual contrast that makes the shift feel inevitable. 'The old model: 10 SDRs doing manual outreach... The new model: 1-2 GTM Engineers managing 20+ AI agents' is more persuasive than 'AI replaces SDRs.'
- Proof points with specific numbers (1.2 humans + 20 AI agents, $1M+ pipeline in 90 days, SaaStr case study) anchor credibility and prevent dismissal. Vague claims get ignored; numbered claims get debated in comments.
- Three-persona closes ('If you're a founder... If you're in sales... If you're in RevOps...') multiply relevance and create three separate comment hooks. Each reader sees themselves in the post.
- Tool mentions as discoveries, not endorsements (Trigify.io, Claude, Opus 4.6) feel like reporting, not sponsorship. This builds trust and drives comments asking 'Is this free?' and 'How much does it cost?'
Steal this for your own LinkedIn
- Start your next post with a role or workflow shift, not a feature. Instead of 'Here's a new AI tool,' try 'There's a new role replacing X.' This frames your insight as macro, not micro.
- Build a side-by-side old vs. new model with arrows (→) and specific numbers in both columns. Readers process contrast faster than narrative. Show the output difference (10 SDRs vs. 1-2 GTM Engineers) before explaining why.
- End with a three-persona close: 'If you're a [persona], this means [specific outcome]. If you're a [persona], this means [specific outcome].' This multiplies relevance and comment hooks.
- Use contrasting examples with 'Not: X. But: Y.' format to show quality gaps without preaching. 'Not: I saw you work at [Company]... But: Your comment about CRM data being a mess hit home...' is more persuasive than 'Personalization matters.'
- Mention tools and integrations as discoveries ('Trigify.io just launched their MCP server') rather than endorsements. This feels like reporting, not selling, and drives curious comments.
- Leave a gap in your post. Show the system but not the full prompt. Mention the outcome but not the exact setup cost. This invites comments asking 'How do I do this?' and turns readers into active participants.
Compare Dima with…
vs Mark A. Pfister - 'The Board Architect'
Dima Bilous vs Mark A. Pfister: Viral hooks versus graduate spotlights
vs Timi Merivirta
Dima Bilous vs Timi Merivirta: AI workflows or lead-gen systems
vs Oskar Moen
Dima Bilous vs Oskar Moen: Automation teacher or metrics hustler?
vs Bray Jaks
Bray Jaks vs Dima Bilous: Personal brand vs systems authority
vs Kris J. Curran
Dima Bilous vs Kris J. Curran: AI automation or content consistency
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Posting patterns
Dima posts 3.3 times per week on average, but has posted 0 times in the last 30 days (data is stale or he's shifted strategy). When active, he maintains consistent cadence without burnout patterns.
Wednesday at 22:00 UTC (10 PM) performs best. This is evening in US Eastern time, likely when professionals are catching up on LinkedIn before bed or during evening work sessions. Timing suggests a US-focused audience.
180-350 words (long-form) is the sweet spot, averaging 805 engagement. This length allows for hook + problem reframe + mechanism + proof + persona-specific close without overwhelming. Shorter posts (30-80 words) average only 40 engagement, suggesting his audience wants depth and narrative, not quick tips.
Engagement by day
Content mix
avg 658 engagements per post
avg 602 engagements per post
avg 861 engagements per post
avg 186 engagements per post
Dima's 49% problem-solution + 14% how-to guide + 14% numbered list mix works because his audience is builders (founders, sales ops, RevOps) who want both macro context (why this shift is happening) and micro tactics (how to build it). The problem-solution posts establish the trend and credibility; the how-to posts deliver the mechanism. This mix keeps readers engaged at both the strategic and tactical level, preventing the content from feeling either too high-level or too granular.
