How It Works
Answer once, agents run.
From first message to working agent in under 3 minutes. No tutorials. No documentation. No flowcharts. Just tell Onnebo what you need, and it builds itself.
Tell Onnebo what you need
Describe the job in your own words. What should the agent do? When should it act? What information does it need?
Onnebo asks follow-up questions to fill in the gaps. You don't need to think of everything upfront. Start with what you know, and Onnebo helps you discover what matters. The conversation is the configuration—no forms, no flowcharts, no technical knowledge required.
“I need an agent that reads incoming inquiry emails, qualifies whether they're a good fit based on my criteria, and drafts a response, warm if qualified, polite decline if not.”
— Example user input
Onnebo might ask: Onnebo might ask: What criteria determine a 'good fit'? Should it check your calendar before suggesting meeting times? How quickly do you want responses sent?
- Natural language agent configuration — no technical knowledge required
- Onnebo asks clarifying questions to fill in the gaps
- Agent understands context and infers your intent
- Iterative refinement through conversation, not configuration screens
Review, adjust, launch
Onnebo assembles your agent and shows you what it built: its role, its permissions, its defaults.
Accept it as-is or refine anything—tone, autonomy level, which actions need your approval before executing. Every setting has a sensible default, so you only need to adjust what matters to you. When it looks right, turn it on with a single click.
“Looks good, but flag any inquiry over $10K for my personal review before responding. And keep the tone direct, no filler.”
— Example user input
Onnebo might ask: You can also set notification preferences: email summaries, Slack alerts for high-priority items, or a weekly digest of everything your agent handled.
- Transparent agent configuration—you see exactly what was built
- Granular permission thresholds by action type
- Communication style presets (concise, thorough, technical, plain)
- Safe defaults with gradual autonomy expansion
Use it. It learns.
Your agent runs. When it handles something well, it reinforces that pattern. When it misses, you correct it.
Correction happens in plain language—just tell it what was wrong and how to do better next time. Over days and weeks, it becomes the agent you would have built if you'd had six months and an engineering team. No retraining cycles. No prompt engineering. Just use it and it gets better.
“That last decline was too blunt. Soften the language for small firms, they sometimes come back with bigger projects.”
— Example user input
Onnebo might ask: The agent logs every correction and the resulting behavior change, so you can see exactly what it's learned over time.
- Implicit learning from your approvals and corrections
- No manual retraining or prompt engineering cycles
- Preferences persist across sessions and agents
- Transparent feedback log so you can see what it's learned
What to Expect
Your agent gets better with time.
Here's how your relationship with your agent evolves as it learns your preferences and handles more situations.
First day
Your agent handles the basics. It might ask for clarification on edge cases. You'll approve or adjust a few outputs.
First week
It's learned your preferences. Fewer approvals needed. It starts anticipating what you want.
First month
It's running autonomously on routine tasks. You only hear about exceptions and high-value opportunities.
Three months
It's better than if you'd spent months designing the perfect workflow. Because it learned from real situations, not hypothetical ones.
No tutorials. No documentation. You talked to it, and now it works for you.
That's the whole point. The barrier between "I have an idea" and "I have a working agent" collapses to a single conversation.
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