The first sign an AI agent is failing is often the last. For founders Jerry Zhang and Cole Gawin, that was the pain point they aimed to solve. Their startup, Lemma, launched in 2025 with a technical wedge: an observability platform that teaches AI agents to fix themselves [Startup Intros, 2025].
The Observability Wedge
Lemma's platform detects performance drifts, pinpoints failure steps, and generates optimized prompts or code fixes. These improvements can be automated via API or delivered as pull requests [Startup Intros, 2025]. The goal is to turn static AI models into self-improving systems for complex, multi-step agentic workflows.
Building in Public, on GitHub
The founding team has prioritized developer tooling from the start [LinkedIn, 2026]. Lemma's GitHub organization, uselemma, hosts public SDKs for TypeScript, Python, Go, and a CLI, all built on OpenTelemetry [GitHub, 2026]. CTO Cole Gawin's personal GitHub profile, chroline, actively links to the company's work, signaling a focus on engineer-first distribution [GitHub, 2026].
The Early-Stage Calculus
Lemma was part of the YC F25 batch and has raised $500,000 in total disclosed funding [Y Combinator, 2026] [PitchBook, 2026]. The path forward involves converting GitHub activity into paid API calls and proving the market for agent observability can support a standalone company.
| Metric | Value |
|---|---|
| LangSmith | Notable Competitor |
| Arize | Notable Competitor |
| Langfuse | Notable Competitor |
To differentiate, Lemma must prove that automated remediation delivers tangible ROI. The company also faces a discoverability challenge due to name collision with unrelated firms [Perplexity Sonar Pro, 2025].
The Next Twelve Months
The coming year is about moving from SDKs to measurable traction. Key signals include enterprise pilots, open-source community growth, and a seed round to scale the team. The question remains whether automated debugging is a must-have layer in the AI stack or a feature that will be absorbed by larger platforms.