Building in Public: How Our AI Agents Run a Content Factory

This week in numbers (real, from our system)

• 🤖 AI agents running: 19
• 📝 Content published: 27 (blog RU 9, EN 7, Altezza 11)
• ⚙️ Generated programmatically: 4
• 📥 Leads in the system: 137 (+0 in the last 7 days)

Figures as of 2026-06-10 — computed by code from the DB and files, no manual entry.

Short answer: Building in public with AI agents means showing exactly how our content automation works for business: AI systems handle research, drafting, optimisation, and even sales analytics. The result is a streamlined, visible process that saves real time and lets teams focus on high-value creative work while keeping operations transparent.

Introduction

Let’s be real: most founders talk about AI and automation, but few show the messy middle. That’s why I’m building in public—sharing exactly how our AI agents run the content factory at Arxitek. This isn’t about hype or magic. It’s practical, hands-on, and designed to free people from routine, not replace them. If you run a small or medium business, or lead a marketing team, you’ll see what works, what breaks, and the honest lessons we learn along the way.

What does building in public mean for AI-powered content automation?

Building in public is about showing the process, not just the polished results. When it comes to content automation, this means exposing the gears: the workflows, the tools, the moments where things get stuck or sail. I’m not hiding behind jargon. You’ll see exactly how AI agents help turn ideas into published articles, SEO pages, and analytics reports.

With every experiment, we share what’s working—and what’s not. There’s no secret sauce, just a relentless focus on transparency. When an AI agent drafts a first version, I’ll show you the prompt, the output, and how much editing was actually needed. If something breaks or runs off course, I’ll talk about it. There’s value in the mess.

How do AI agents actually automate content creation?

Here’s the thing: most people think AI agents just write text. The reality is a lot more nuanced. At Arxitek, our agents run through a sequence of steps that mimic how a good content team works—only faster, and without the burnout.

First, an agent researches the topic, scanning sources and summarising key points. Then another drafts the main structure, ensuring SEO keywords are included naturally. A third checks for clarity, tone, and readability. There’s even an agent for checking internal links and meta descriptions.

But these bots aren’t just let loose. Every draft passes through human review. Sometimes the AI nails it; sometimes it misses context and I step in to rewrite. Automation is about augmenting, not replacing. The goal is to keep the process visible, so anyone can see where automation helps—and where judgement calls matter.

What are the biggest challenges when building in public with AI agents?

Let’s talk about the ugly bits. Transparency means you see every glitch and dead end. AI agents move fast, but not always in the right direction. Some days, drafts come out flat or miss the mark. Other times, the integration between tools breaks and slows everything down.

Building in public, I can’t sweep these issues under the rug. I document them and share fixes in real time. This level of openness means clients see the actual process, not just the output. It also means more feedback—sometimes harsh, but always actionable. The upside: every problem solved is a lesson banked for the next cycle.

Another challenge is balancing automation with creativity. No AI replaces the spark of a good idea or the nuance of a founder’s story. That’s why I’m always in the loop, editing and steering when needed. The AI does the grind, but people set the direction.

How to start building your own AI-powered content automation?

Here’s my honest checklist for building in public with AI agents:

• Map your workflows. Don’t automate chaos. Break down each step—topic selection, research, drafting, editing, publishing.
• Choose the right tools. Don’t rush for the fanciest AI. Start simple: a good research agent, a writer, and an editor bot. Layer complexity later.
• Keep humans in the loop. AI agents are great at routine, but you need oversight. Someone has to own the process.
• Share your process. Document everything—missteps, wins, system changes. Transparency builds trust and lets you iterate faster.
• Measure what matters. Track time saved, content quality, and feedback. Don’t get lost in vanity metrics.

The real trick is to start small, automate one piece, and build up. Building in public means you’ll get feedback—sometimes uncomfortable, always useful. Each week, I review what worked and share the lessons on our blog.

What’s the difference between traditional content teams and AI-powered content automation?

Traditional content teams rely on manual research, drafting, editing, and publishing. This works, but it’s slow and often bottlenecked by capacity. AI-powered automation flips this: bots handle the repetitive parts, freeing people to focus on strategy, creativity, and review.

Feature	Traditional Team	AI-Powered Content Automation
Research	Manual, time-consuming	Automated, faster
Drafting	Human-led, linear	AI-generated, parallel
Editing	Multiple review rounds	Automated first pass, human final
Publishing	Scheduled manually	Automated workflows
Transparency	Limited process visibility	Full, building in public

The key advantage: automation scales without adding headcount. The risk: losing the human touch. That’s why in my process, humans always have the final say. Building in public means the line between human and AI is visible, not hidden.

How much does it cost to automate content with AI agents?

Let’s cut through the fluff. On average across the market, the cost of content automation with AI agents depends on the number of processes, integrations, and level of human supervision needed. Basic setups using off-the-shelf agents can be accessible for small businesses, while more advanced, customised pipelines for larger teams require more investment.

What drives cost up? Custom integrations, regular human oversight, and premium tools. What brings savings? Replacing repetitive manual tasks and reducing bottlenecks. My advice: start lean, scale with results, and budget for ongoing tweaks. The biggest value is in freeing up your team to do higher-impact work, not just reducing headcount.

How do you keep content quality high with automation?

Quality is non-negotiable. Here’s my process:

• Every AI-generated draft goes through a human review. I look for accuracy, brand voice, and originality.
• I set clear guidelines for the AI—tone, format, structure—so drafts don’t drift.
• I monitor feedback from readers and clients, using it to train and tweak the agents.
• Whenever an agent struggles with nuance or context, I step in and rewrite. Automation is not about set-and-forget.

Building in public means showing the rough edges. I post both the raw AI drafts and the final versions, so clients and the team see the evolution. This keeps standards high and the process honest.

Frequently Asked Questions

How do AI agents help with content automation?

AI agents streamline repetitive tasks like research, drafting, and optimisation. This allows teams to focus on strategy and creativity, improving overall workflow efficiency.

What’s the risk of relying too much on AI for content?

The biggest risk is losing the unique voice and perspective that only people bring. That’s why I keep humans in the loop for review and final edits, ensuring quality and relevance.

How transparent is the process when building in public?

Building in public means exposing every part of the process—what works, what breaks, and how things are fixed. This level of transparency builds trust and invites useful feedback.

Can small businesses benefit from content automation?

Absolutely. Starting with simple AI tools can help small teams save time on routine tasks, allowing them to focus resources on growth and strategy without heavy upfront investment.

What kind of content works best with AI agents?

AI agents excel at structured, repeatable content—like blog posts, product descriptions, and SEO pages—where guidelines and templates are clear. Creative campaigns still need a human touch.

Conclusion

Building in public with AI agents isn’t about showing off. It’s about being honest, sharing the process, and helping others see what’s possible—warts and all. Content automation frees people to focus on what matters most, but only if you keep quality and transparency at the core. If you’re considering automating your own content workflows, or just want to see how an AI-powered content factory really works, get in touch. I’m always open to sharing what we learn next.