AI & Development 10 min read

Agentic AI Development: 7 Days with an AI Orchestrator in Production

Seven days of real-world development where an AI agent plans, codes and tests autonomously. Not a demo, not a sandbox — live production, real money, real mistakes.

Vibe-coding lost its appeal for me around the third iteration. Watching AI write code that it immediately rewrites isn't productive. I started thinking differently: what if instead of giving AI tasks one by one, I gave it context, a goal, and let it find its own path?

That's how the experiment was born: seven days of agentic AI development on a real project. No simulations, no toys. The agent got access to the codebase, tools, and was able to work largely autonomously — with my oversight on key decisions.

What is agentic AI and why it's different from a chatbot

Generative AI can write code on demand. Agentic AI goes further — it plans steps, calls tools, processes results and iterates without you pushing it after every step. The difference is fundamental.

At the core is an orchestrator: a layer that takes a high-level goal and breaks it down into concrete steps. For that it needs access to tools — git, terminal, filesystem, databases. Model Context Protocol (MCP) standardized this communication and turned it into a production-ready interface.

What I discovered in seven days

  • Agentic AI is production-ready — not just for prototypes, but for real features
  • The speed gains are real — things that would take two days, the agent completed in a few hours
  • The cost will surprise you — $1 per minute of active agent work sounds steep, but in context it makes sense
  • Guardrails are a necessity, not an optional extra — without them the agent goes off the rails
  • Code quality is mid-level — a solid foundation, but without senior review it's not enough for production
Who this series is for: Technical leads, CTOs and developers deciding how to integrate AI into their development process. No theory — concrete experiences, numbers and conclusions.

How the series works

Each episode covers one day of the experiment: what happened, what worked, what didn't and what conclusions follow. The episodes are short and deliberately concrete — no generic talk about the "AI revolution".

At the end of the series you'll find two bonus articles: one on guardrails and protecting against an uncontrolled agent, the other on a knowledge base as the key building block for AI in an enterprise environment.

If you want to know where agentic AI development begins and where vibe-coding ends, start from day one.

Want to see how business processes can be automated? Book a consultation — we start where vibe-coding ends.

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