Blind Dev article
Where AI automation breaks: Google Docs, Calendar, limits, and reality
An honest look at automation boundaries: auth, limits, formats, and expectations.
Based on Blind Dev personal experience and source posts; verify current details before applying.
In short
An honest look at automation boundaries: auth, limits, formats, and expectations. 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.
If you need this kind of system
If you have a repeated workflow, internal documents, requests, content, support, or analysis process, I can help review the workflow and set up an AI agent for a concrete task. A useful first step is a short process review: where AI can help, which risks should stay under human control, and what result can be validated quickly. Then you can open the services page or contact me with a short description of the workflow.