Blind Dev article
How I work with AI agents: why it is more than ChatGPT
The difference between chat, agents, and skill-based workflows in real Blind Dev scenarios.
Based on Blind Dev personal experience and source posts; verify current details before applying.
In short
The difference between chat, agents, and skill-based workflows in real Blind Dev scenarios. This article explains how I use AI as a working layer, not as a novelty: task framing, decomposition, execution, verification, and rollback when the result does not survive review.
The scenario
Most AI automation starts with the same pain: repeated work, too many manual steps, and the temptation to ask a model to “make it nice.” In real work that is not enough. You need context, boundaries, acceptance criteria, and a way to verify the result without trusting the model blindly.
What matters
- Describe the workflow before choosing the tool.
- Split the task into small verifiable steps.
- Keep sources, decisions, and limitations close to the output.
- Do not delegate final judgement where the cost of error is high.
How I use it
I use assistants and skills for code, writing, documents, analysis, planning, and routine operations. The key layer is not generation; it is control: gather context, draft, verify, improve, and only then publish or ship.
Risks
The biggest risk is confusing speed with quality. AI can create a strong feeling of completion while facts, logic, or usability are still broken. A good workflow always includes manual checks and clear stop rules.
Practical takeaway
AI is useful when it reduces friction while keeping the human in control. If automation makes a process faster but less verifiable, it should be simplified or redesigned.
Related Blind Dev work
AI workflow consulting, internal tools, Telegram bots, and quality checks before launch.