From Vibe Coding to Agentic: My Personal Transition
From vibe coding to agentic development: my shift from prompt demos to reliable AI agents with clear ownership, guardrails, and repeatable production shipping.
Table of Contents
First win: the prototype phase
I started like most builders in this cycle: fast prompts, fast demos, fast dopamine. A rough idea in the morning could become a working interface by that night.
That mode taught me speed and confidence. It also masked fragility because the same person who built it was still the only person touching it.
Timeline
From vibe coding to agentic development
Q4 2023
Prompt-heavy sprint mode
I was shipping quick internal tools from natural language prompts and light glue code. It was fast and honestly addictive.
Q1 2024
First real user traffic
Edge cases started showing up. Small assumptions in prompt flows turned into repeated support issues once customers used the product daily.
Q2 2024
Failure loops got expensive
A few flaky integrations and brittle prompt chains created rework. I was spending more time patching than building.
Q3 2024
Agent workflows replaced prompt chains
I introduced explicit steps, typed contracts, and retry policies. Outputs got more predictable and easier to debug.
2025 onward
Production-first agentic development
Today every serious workflow has owners, observability, and a fallback path. Speed stayed high, but chaos dropped hard.
Turning point: production pain
The turning point was not philosophical. It was practical. When support tickets started repeating the same failure patterns, I realized I was optimizing local speed and sacrificing system stability.
I had to stop asking, “Can I make this work?” and start asking, “Can this keep working without me babysitting it?”
Building the agentic stack
I moved toward an agentic architecture: explicit state, separate planning and execution steps, typed tool contracts, and more deliberate fallback behavior.
That removed a lot of hidden coupling. It also made collaboration easier, because the system became legible to other developers.
The operating system I use now
My default now is simple: prototype quickly, then graduate winners into owned workflows with release checks, runtime visibility, and test coverage on business-critical paths.
I still value creative speed. I just refuse to confuse creative speed with production readiness.
Internal Links
More pieces that map the same evolution from different angles.
Vibe Coding Is Not Enough
Why prototypes and production need different standards.
My AI Team Works While I Sleep
How orchestration enabled overnight shipping velocity.
Work With Me
If you want this transition in your team, we can map it fast.
AI Agent Services
Implementation support for teams operationalizing agentic workflows.
FAQ
Common questions about this transition
What was the biggest mindset shift in your transition?
Treating AI output as one input in a system, not the system itself. Once I separated orchestration from generation, reliability improved quickly.
Did moving to agentic workflows make you slower?
For the first week, yes. After the base patterns were in place, I shipped faster because fewer releases required emergency fixes.
What should a solo builder do first?
Pick one revenue-critical workflow and add contracts, logging, and a fallback path. You do not need a full platform rewrite to get leverage.
How do you keep speed while adding reliability?
Use a two-lane model: rapid prototyping for discovery, then a production lane with typed interfaces, QA checkpoints, and explicit owners for each workflow.