Developers know TDD (Test-Driven Development). But when your agent operates in an infinite natural language input space, traditional testing breaks. Tikal’s Eval-Driven Development Launchpad embeds a structured evaluation architecture into your team, moving from subjective “vibe checks” to engineering contracts, automated graders, and production observability. Debug the Spec, not the code.
The EDD Launchpad is a fixed-scope, 5 to 6 week engagement that gives engineering teams the methodology, tooling, and habits to test AI agents like real software. It replaces ad-hoc prompting with version-controlled datasets, layered graders, and a continuous production feedback loop that turns every failure into institutional memory.
The Launchpad integrates with your existing observability stack. We work with platforms like LangSmith, Braintrust, or Promptfoo for full trajectory visibility, and LiteLLM for centralized model routing during evaluations. The grading layer is built on standard frameworks like Pytest or Jest. All datasets, graders, and directives live in Git, wired into your CI/CD pipeline via GitHub Actions or GitLab CI.
A governed, measurable evaluation system that catches agent failures before they reach production.
Replace ad-hoc prompting with strict binary specs that define success before writing a single line.
Version-controlled Gold Sets become the definitive ground truth for your agent’s capabilities and behavior.
Fast structural checks and LLM-as-a-Judge semantic graders catch what no unit test ever could.
Failed traces flow directly into your test suite, so the system grows smarter with each incident.
Evaluate how your agent thinks, not just what it says, across every tool call and step.
No prompt change reaches main unless the full evaluation pipeline turns green.
The EDD Launchpad runs as a focused 5 to 6 week engagement.
(Week 1)
We map current AI testing practices, review 50 to 100 real production traces to identify recurring failure modes, and establish your Escape Rate baseline. We scaffold the evaluation infrastructure and observability stack ready for the work ahead.
(Weeks 2-3)
Four hands-on sessions covering engineering contracts, the Evaluation Pyramid, trajectory diagnostics, RAG decomposition, and scaling human judgment via Annotation Queues, all built around your team's actual agents.
(Weeks 4-5)
Tikal embeds into a live sprint alongside your team. We build the first Gold Set, write and wire graders into your CI/CD pipeline, and configure production observability to sample live traffic automatically.
(Week 6)
We measure the new Escape Rate against the original baseline, validate adoption across the team, and transfer full ownership of the evaluation stack, datasets, and observability dashboards to your team.
Sounds right?
Let’s embed a real evaluation system into your team and start measuring what matters.
