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Moda: The Continual Learning Layer for AI Agents

Turn production agent traces into validated improvements for your agent harness.

Details

External ID
98435
Source
YC
Company
Moda
Product
Moda: The Continual Learning Layer for AI Agents
Website domain
moda.dev
Launched
March 4, 2026
Cohort
Winter 2026
Upvotes
122
Upvotes percentile
0.9565217391304348
Tags
—
Fetched at
Sept. 30, 2026, 5 p.m.
Updated at
Sept. 30, 2026, 5 p.m.

Enrichment

Theme
ai agent infrastructure and tooling
Vertical
Horizontal
Function
Observability & eval
Audience
Developer
AI stance
AI feature
Project type
Commercial product
Normalized one-liner
continuous learning for ai agents
Manually corrected
False

Could you build this?

Partial An agent observability dashboard can be built quickly, but unsupervised intent clustering, frustration detection, and automated harness tuning from raw OTel traces require non-trivial ML and data systems.

What it would actually take: The backend requires high-throughput streaming ingest for OpenTelemetry agent traces (e.g., using Kafka and ClickHouse), coupled with unsupervised hierarchical clustering pipelines (e.g., HDBSCAN on trace embeddings) to group user intents. The evaluation engine needs deterministic harness optimization algorithms that simulate agent runs and validate prompt/tool mutations against regression test suites.

Competitors

Other products that read as similar to this one — 2159 launches clear the similarity bar, closest 8 shown.

Attention rank: #99 of 2160 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).

Launched 126 days after the earliest competitor.

Other launches for this product

Same idea, different domain

Nobody's really built a observability & eval tool for Media & entertainment yet.