AI-generated code is great. But only if we can trust it. At Leapter, we want to reinvent how software is delivered, from prompt to production.
Read more about how we're approaching the problem on our blog: www.leapter.com/blog/
If you’re curious, don’t overthink it. Build one blueprint, and you’ll understand the model.
AI agents are great at natural language. They are less reliable when the same input must produce the same output every time.
We documented a simple pattern for deterministic tools without writing code: spec → visual review → boundary testing → export to n8n, MCP, API, or code.
https://www.leapter.com/post/deterministic-tools-for-ai-agents-without-writing-code
If you prefer to learn by clicking around: Leapter docs home is the best starting point.
The “face vs brain” split for agents: natural language on one side, deterministic business rules on the other.
“For quick prototypes, speed can be enough. But when it comes to business-critical systems, speed without understanding isn’t an advantage; it’s a liability.”
That’s the trust gap behind “vibe coding.” It runs, but nobody can confidently explain it, change it, or debug it when the real world gets messy.
Leapter’s take: assistive AI should output verifiable system logic (blueprints) that humans can review together before deployment.
If your agent workflow includes pricing, eligibility, routing, or policy decisions, you need a trust boundary.
Leapter is that layer: deterministic execution + inspectable logic + reproducible outcomes.
https://www.leapter.com/post/introducing-leapter-the-logic-layer-every-ai-agent-needs
Most AI agent demos look great until you ask: can we reproduce this outcome?
Human-verifiable logic = visual + deterministic + executable. You can inspect each branch, run test inputs, and only then publish it as a tool.
Example in the post: “>€500 + new customer => 10% else 5%.” The ambiguous parts become explicit nodes you can verify.
https://www.leapter.com/post/what-does-human-verifiable-logic-actually-look-like
“We shipped the ticket” isn’t the same as “we shipped the intent.”
Leapter exists to close that gap by making logic visible and verifiable earlier. https://www.leapter.com/post/what-is-leapter
Keeping humans in the loop isn’t a vibe. It’s the difference between “AI shipped something” and “we can verify what actually runs.”
We don’t need more black boxes that dump the cost into review + incident response. We need a glass box: logic you can inspect, test, and repeat.
Read: https://www.leapter.com/post/mind-the-gap-why-we-don-t-trust-ai-generated-code-yet
