Latitude for Claude Code vs Seeknal

Latitude is an observability platform specifically tuned for Claude Code usage. It captures every turn an agent runs — the prompts, tool calls, bash output, files touched, system prompt, and the tool schemas Claude Code composes at runtime — then surfaces it as cost breakdowns per prompt, per session, and per workspace. The platform routes Claude Code traffic through Latitude's instrumentation layer, giving engineering teams real visibility into what their AI coding agent is actually doing versus what they expect it to do. Teams can trace expensive tool-call chains, spot runaway loops, identify which slash-commands are budget-efficient, and attribute costs to specific tasks or repos without wading through raw OpenTelemetry traces. In a world where Claude Code rate limits and API costs are a real engineering budget concern, Latitude fills a genuine observability gap. It launched on Product Hunt today with 150 votes and complements Claude Code's native OpenTelemetry support by adding a human-readable interface and cost attribution dashboard that raw traces simply don't give you.

Seeknal is a Data & ML CLI designed for teams running agent-driven data pipelines. The core workflow follows three verbs: Organize (define pipelines in YAML or Python), Expose (materialize data to PostgreSQL and Apache Iceberg), and Action (query and transform data in natural language). It uses a draft, dry-run, apply progression that gives teams control before changes hit production. The natural language query layer is what sets Seeknal apart from standard data pipeline tools. Instead of writing SQL to explore a freshly materialized table, you describe what you want — and Seeknal translates that to the appropriate query against your Postgres or Iceberg target. The combination of structured pipeline definition (YAML/Python) with flexible natural language exploration is designed for the reality that data teams include both engineers who want explicit control and analysts who want fast iteration. The 'built for the agent world' framing reflects a genuine architectural choice: Seeknal's API is designed to be called programmatically by AI agents, not just by humans with keyboards. This matters because data pipeline management is increasingly something agents need to do autonomously — fetching fresh context, materializing results, and querying outputs — without human intervention at each step. Seeknal launched on Product Hunt today targeting teams that have adopted agentic workflows but still treat their data infrastructure as human-operated.