Content Machine
I built a content system that connects search research, company knowledge, writing, editorial review and publishing operations.
10× publishing output · +300% AI visibility
AI builder · Business thinker
I’m a hands-on AI builder with a
background as a founder and B2B marketer.
I find expensive GTM problems and
build AI systems that generate pipeline.

Building the system is the easy part. The job is integrating it into the business.
I look at how the work gets done, talk to the team and check the data. Then I weigh the business value against the effort needed to make a solution work.
That can mean scaling content or paid campaigns, making prospect, competitor and market research practical, or putting company knowledge to work.
My work
Why I built them, and what changed in costs and pipeline.
15 projects shown
I built a content system that connects search research, company knowledge, writing, editorial review and publishing operations.
10× publishing output · +300% AI visibility
I built a system that turns LinkedIn engagement into qualified prospect worklists, with CRM context and follow-up measurement.
Six-figure ARR pipeline
I built a job-search product that discovers roles, explains mutual fit and prepares a coordinated application package.
1,000+ roles assessed weekly
I built a source-grounded working memory for projects, decisions, agreements and the questions still worth answering.
Project context that can be traced to its sources
Paid campaigns need a reason to reach a particular audience with a particular message.
Audiences and messaging used in paid win-back campaigns
Paid campaigns need a reason to reach a particular audience with a particular message. I built an AI workflow that combines CRM loss history with buyer conversations to define win-back audiences and campaign hypotheses. It turns those findings into message recommendations and campaign plans, with audience exports ready for the marketing team. The team used the system in paid-channel campaigns that brought prospects back into the pipeline.
Useful market conversations are easy to miss in a large stream of Reddit posts.
Relevant discussions with a prepared response brief
Useful market conversations are easy to miss in a large stream of Reddit posts. I built a research and response desk that selects relevant discussions and explains where an expert could contribute. It produces short briefings with an angle, context and boundaries, then brings selected opportunities into Slack. The delivered work included the research, participation plan and working desk; sustained posting had not started.
Email metrics can reveal a problem without explaining its cause or the next useful action.
From an email anomaly to a testable explanation
Email metrics can reveal a problem without explaining its cause or the next useful action. I began a diagnostic workflow that turns an issue into an evidence-backed case and a proposed test. The early build investigated one audience-related issue and shaped the next version around decisions rather than another metrics dashboard. It remained a prototype, with broader investigation and action tracking still to develop.
A journalist’s request is useful only when the audience fits and someone can answer it credibly.
Relevant media requests, ready for expert review
A journalist’s request is useful only when the audience fits and someone can answer it credibly. I built a workflow that collects requests, checks those conditions and presents the relevant opportunities with deadlines and source context. I calibrated the selection through manual review and added Slack updates for new matches. The tool prepared opportunities for an expert to review and answer.
Supplier calls leave teams comparing proposals, notes and impressions from different conversations.
Comparable offers, with the detail behind the recommendation
Supplier calls leave teams comparing proposals, notes and impressions from different conversations. I built an AI-assisted workflow that brings transcripts and proposals together with the team’s requirements. It organizes scores, strengths, weaknesses and price considerations in a comparison dashboard. The result helps people inspect the tradeoffs and explain a recommendation to management.
Early sales contacts needed a reason to stay engaged between conversations.
A repeatable content channel for early sales relationships
Early sales contacts needed a reason to stay engaged between conversations. I helped build a Telegram content bot with the marketing team, using sports news and AI-assisted content for a news group. Sales invited cold contacts into that group during their first interactions. It became a repeatable way to keep relevant content in front of those prospects.
Colleagues needed to see how AI could fit the work already on their desks.
Two practical sessions across LSports’ go-to-market teams
Colleagues needed to see how AI could fit the work already on their desks. I designed and delivered two practical training sessions for go-to-market teams across LSports. We worked through recurring-task assistants, AI-assisted research and prototypes that people could discuss with design and web teams. The sessions gave colleagues methods they could adapt to their own workflows.
The next useful webinar speaker may already be somewhere in the CRM.
A speaker shortlist grounded in existing relationships
The next useful webinar speaker may already be somewhere in the CRM. I built a tool that combines those relationships with public profile information and available account context. It creates an evidence-backed shortlist that people can inspect by fit, expertise and location. The delivered result was a speaker library prepared for event planning.
A recorded webinar holds expert material that is difficult to reuse from a video alone.
Attributable expert material prepared for editorial use
A recorded webinar holds expert material that is difficult to reuse from a video alone. I built a workflow that identifies speakers, preserves attributable quotes and connects the content with CRM context. It organizes the material into a reusable library and prepares article drafts for human review. I manually checked reliability and worked through the field mapping needed to connect the sources.
I built a tool to make product videos easier to produce and revise, and turn long recordings into short promotional clips.
Product explainers, 30-second promos and 10-second teasers.
I built a tool to make product videos easier to produce and revise, and turn long recordings into short promotional clips. Producing a few product videos had taken the team more than a week, with even small edits adding work. I built a workflow that renders scenes from code, so I could control the output and make precise changes. It also cuts webinar and summit recordings into short promos, with a person choosing from five versions.
An expert speaks differently in an article, a LinkedIn post and a live talk.
An expert’s voice across posts, articles and scripts
An expert speaks differently in an article, a LinkedIn post and a live talk. I built format-specific writing guides and an AI workflow from an expert’s own material. The process separates product knowledge from voice and checks whether the output follows the right format. Reviewers rated the writing highly in testing, giving me feedback to refine the guides and the evaluation.
About me

I’m Evgeny Rodionov. I work across business, go-to-market and AI, and I build the systems myself. Running my own company taught me to look beyond acquisition: more demand only helps if the business can turn it into profitable work. That perspective still guides which problems I choose to solve.
I build systems that help teams scale what works and take on work they couldn’t do before. That can mean expanding content production, finding new sales opportunities or making company knowledge available when someone needs it. I work directly with the people doing the job, from understanding the problem through building, rollout and improvement.
My approach
Talk to the process owner. Understand the result they need and where time, revenue or useful information is being lost.
Follow the workflow and inspect the data. Map decisions, exceptions and handoffs before choosing what to automate.
Define the output and how to check it. Build the workflow with clear places for human review and decisions.
Try it with the people who will use it. Support rollout, observe the result and refine the system around real feedback.
Where the experience comes from
Founder & CEO
I founded and ran a custom wood-products business, reaching $700,000 in peak annual revenue with a 20-person team. I connected digital acquisition with pricing, CRM, production and delivery.
Co-Founder & Growth Lead
I co-founded the AI assistant platform and led its growth from 0 to 10K users in five months through guerrilla marketing, with no paid advertising.
Web Growth & AI Automation Manager
I expanded web acquisition through a niche-site network that generated 23% of the company’s inbound leads in 2025. I connected lead capture to the CRM and built AI workflows while teaching practical GenAI methods across go-to-market teams.
AI Marketing Lead
I built and rolled out 10 AI GTM systems with the teams using them. My content engine scaled SEO/GEO publishing 10× and increased AI visibility by 300%; a LinkedIn prospecting channel contributed to a six-figure ARR pipeline.