3 decisions to make before starting to vibe code
AI lets comms teams build tools, trackers and workflows without a single IT ticket. The speed is real. So is the risk.
Stephanie Nivinskus is principal at Ragan’s Center for AI Strategy.
Many comms teams eventually hit the same wall: a situation that demands a custom tool, a workflow or a framework, with no clear path to building it fast enough.
That wall is coming down. AI makes it possible for non-technical professionals to describe what they need, refine it through a series of prompts and arrive at a working solution in hours instead of days or weeks. No developers. No scope document. No queue.
It’s called vibe coding, and it is spreading through organizations faster than the governance structures designed to support it.
Decision 1: Define what the team is allowed to build.
The first tool built without a boundary sets the precedent for every tool that follows.
Most comms teams use AI without clear use cases, governance or accountability. Vibe coding accelerates that gap. Tools built without oversight do not automatically meet data security standards.
Applications that pull from internal HR or legal systems introduce exposure that surfaces fast in a breach or compliance conversation. Brand inconsistency emerges when team members build parallel tools with different approved language. This conversation is easier to start than to restart.
- Put the boundary in writing. Specify what is in scope: internal workflow tools, content trackers, FAQ builders, crisis prep checklists. Anything touching employee data or regulated content should default to governed environments, not ad hoc builds.
- Distribute the boundary before the option exists. The line must be in place before the team knows vibe coding is available to them.
Decision 2: Establish who owns what gets built.
Ungoverned tools do not disappear when the person who built them does.
The use cases are immediate. A director of internal communications builds a searchable FAQ hub before a benefits rollout, fielding employee questions before the first inquiry arrives. A crisis team prototypes a tiered response tracker in an afternoon. A global comms function builds a brand review intake form without a formal build request.
Every AI-built tool must have an accountable leader, a stated purpose and a review date. If those conditions aren’t met, it’s not ready to deploy.
- Require documentation at build. Named owner, stated purpose, review date, every time.
- Apply the two-sentence test. If it cannot be explained in two sentences, it does not ship.
Decision 3: Put comms at the governance table
IT and legal will optimize for risk reduction. Only comms understands how messaging, workflow and brand risk collide in real time.
Run vibe coding as a structured experiment within one function first. That pilot gives comms concrete examples to bring into the governance conversation and the standing to lead the outcome rather than inherit it.
- Pilot with one function first. Contain the experiment before it scales.
- Bring findings to the governance table. Concrete examples carry more weight than a policy opinion.
- Define what comms owns. Messaging standards, brand risk and workflow accountability belong to this function.
The bottom line: What to do now
- Define the build boundary. Put approved use cases and off-limits categories in writing before the first tool goes live.
- Require documentation at build. Named owner, stated purpose, review date, every time.
- Lead the governance conversation. Shape the structure before it is handed down.
The speed is already here. The structure is not. That gap is where leadership either shows up or gets bypassed.
Members of Ragan’s Center for AI Strategy can learn even more about vibe coding. Become a member today.
“The speed is already here. The structure is not. That gap is where leadership either shows up or gets bypassed.”
Very true!
Vibe coding does come at a cost we haven’t really seen before. What used to be called technical debt is now getting mixed with something else: comprehension debt.
Comprehension debt is basically the gap between what the system does and how well anyone actually understands it. In theory, you could prevent it with perfect upfront documentation and fully locked-in context—but that’s just not how things go. Requirements shift, prompts change, tools change, and the “source of truth” ends up scattered across chats, iterations, and whatever the AI last produced.
AI only knows what you give it—so if something’s missing, it’ll still produce something that looks right, just not quite right.
That’s where the debt starts to build. One small missed assumption, one vague instruction, and it compounds.
Then something breaks and you end up in that loop:
“…please fix.”
“…still broken, please fix…”
At that point you’re not really debugging—you’re trying to recreate context that was never fully written down in the first place.
And over time, that shifts the work. Less actual building, more figuring out what the system is even supposed to be doing.
A good rule of thumb to help minimize this, is to make sure at least one team member should be able to explain the logic (code) without needing to ask their agent. Actual ownership of the project. Otherwise it’ll end up being a classic, 90% done project..