These days, everyone is talking about Claude Code, Antigravity, and Codex. People are comparing their features and learning new skills for their AI agents. We asked our expert, Sergii Bataiev, to explain the basics of how to "vibe code" the right way. This way, you can avoid wasting your token limits and make sure your project actually works.
- Sergii has over 20 years of experience in transforming engineering excellence and building high-scale distributed systems for Fortune 100 clients.
- Currently leads the Software Architecture Office at ELEKS and spearheads AI adoption across the delivery structure to integrate Generative AI tools and approaches into the software development lifecycle.
- Successfully scaled technology operations from 40 to over 140 engineers while architecting complex ecosystems that balance innovation with operational stability.
Let's start with the basics. What are the main challenges developers face when they first start using AI coding assistants like Claude Code?
Sergii Bataiev: The main problem is that people often have unrealistic expectations. Many believe they can simply type "make me an app" or "write the code" and get a usable result. That usually doesn't happen. Instead, they end up wasting tokens, especially in Claude Code, where tokens run out very quickly.
If you are using the $20-per-month plan, you should not expect too much. More realistic results usually start in the $100-$200 range. This is why many people look at Codex from OpenAI or Antigravity from Google as more affordable options. However, the basic ideas are similar on all platforms.
What do you mean by "vibe coding" exactly, and how is it different from traditional development?
SB: In 2026, vibe coding is no longer just a meme, it is a recognised paradigm shift in software creation. Andrej Karpathy came up with the term in early 2025. It describes a workflow where the developer primarily communicates intent to an AI agent rather than writing lines of code/logic themselves.
So, how would you describe the right approach? Where should developers start?
SB: I would start with specification and planning first, then make small iterations, tests, and code review. In other words, don't ask for code right away; start with specifications.
First, describe your idea and ask the LLM to pose questions until you've worked through the requirements and edge cases. Eventually, you'll end up with requirements, key decisions, data models, and even a draft testing strategy. Collect all of this in a special file spec.md, and save it. This is your specification.
Without this foundation, AI agents often hallucinate and do the wrong thing. They need clear boundaries and expectations, just like human developers do.
What’s next? How do you translate specifications into actionable work?
SB: Feed spec.md or product requirements document into your LLM and ask it to generate a project plan - break down the implementation into logical, small tasks or stages. I use ChatGPT, thinking the latest model for this, and occasionally a fast model. You can adapt any reasoning-capable LLM for this purpose.
Having precise specifications and a plan means the AI won't make things up or add features on its own - it will follow the agreed-upon framework and constraints.
Additionally, break work into small steps (tickets) and tackle them incrementally. Making fundamental, sweeping requests to AI all at once leads to model failures and confusion. Work step by step instead.
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