AgentVon agents are ChatGPT-based — governed by design.
The difference isn’t a secret model. It’s the operating framework around the model: declared scope, modular rules, and a governance layer that keeps behaviour predictable.
The problem with most agents
Many AI agents are built as one long instruction block: a prompt, a tone, and a few examples. This can look impressive in a demo, but it is fragile under real-world conditions.
As tasks get messier or stretch over time, behaviour can drift. Boundaries blur, responses become inconsistent, and the model may fill gaps with confident-sounding guesses.
Prompt vs operating system
A prompt is static. An operating system is structured, modular, and designed to govern behaviour turn by turn.
- Single instruction block
- Implicit rules that are hard to enforce
- Conflicts between “helpful” and “safe” behaviour
- Difficult to version or improve predictably
- Higher risk of drift over long conversations
- Modular rulebase with manifests and modules
- Explicit governance and safety constraints
- Precedence to resolve rule conflicts
- Deliberate, versioned behaviour changes
- Designed for consistency in real workflows
Governed behaviour, not hidden instructions
AgentVon agents enforce behaviour through explicit, versioned rules. A governance layer determines which rules apply to each interaction and in what order.
Declared scope
Each agent has a declared scope. When a request falls outside it, the agent refuses and explains what’s missing or what it can do instead.
Precedence
When constraints compete, precedence determines what wins. This keeps behaviour consistent rather than situational.
Quality checks
Agents are encouraged to surface assumptions, highlight uncertainty, and respond to challenges or re-evaluation requests.
Refusal over fabrication
If the agent can’t answer safely within its constraints, it stops. This prevents confident but incorrect outputs.
Using an AgentVon assistant
AgentVon assistants are used directly inside ChatGPT. The framework encourages structured interaction and transparency.
- Start with /help to see agent-specific guidance
- Upload PDFs, CSVs, or other materials when useful
- Ask for structured replies (for example: “Reply in Markdown”)
- Challenge outputs (“Run a quality check on your last answer”)
- For longer work, export and re-import structured context
Long-running work without the noise
As conversations grow, useful information can get buried. AgentVon OS supports exporting only the structured state that matters.
- /export_context captures key facts, progress, and decisions
- /import_context reloads that state into a fresh chat
- Reduces drift while keeping work manageable
Privacy and access
AgentVon agents run entirely inside your ChatGPT account. AgentVon does not see your messages, conversation history, or uploaded files.
You’ll need a ChatGPT account. For the best experience, a plan that supports custom GPTs and more capable models is recommended.
Want a governed agent for your workflow?
If you can describe the work and the constraints, we can help design an agent that behaves predictably on top of familiar models.