Stop watching your production agents fail invisibly. Get the telemetry layer that surfaces tool-call loops, silent API mismatches, and memory conflicts before they cost you revenue.
Priced for medium-severity observability gaps. Severe multi-agent or cross-schema complexity may qualify for the $5,000 tier — assessed during kickoff.
Delivery in 5 business days from kickoff confirmation.
Five concrete artefacts — not decks, not "recommendations." Deliverables you integrate directly.
Structured write-up of recurring failure patterns — tool-call misroutes, silent schema guesswork, multi-step loops — annotated with parent-span traces and severity ratings. Includes an executive summary scoped to your specific agent topology.
Instrumentation config preserving parent-child relationships across multi-agent handoffs. Compatible with OpenTelemetry collectors, Honeycomb, or your preferred tracing backend. Ships with annotation attributes pre-defined for LLM invocation events.
Replayable test harness that scores every production trace against pass/fail rules. Failures feed automatically into your CI regression suite. Pre-loaded with scoring criteria for tool-selection accuracy, memory read/write integrity, and response latency bounds.
Contract-check YAML defining every tool invocation's expected request/response shape. Blocks deployments where the LLM fills integration gaps with guesswork — the silent failure mode responsible for up to 40% of lost API calls in production.
SLO document defining observability coverage thresholds (e.g., "trace coverage must exceed 95% of tool invocations"). Appendix lists approved tracing SDKs, evaluation frameworks (Braintrust, Athena), and CI/CD integration patterns with direct links.
Any LLM-powered autonomous system that performs multi-step tool invocations, API calls, or decision-making in a live environment — including copilots, workflow automations, coding assistants, and retrieval-augmented pipelines. The sprint is stack-agnostic: OpenAI, Anthropic, open-source models, and custom fine-tuned agents all qualify.
Standard application logs capture what happened — not why the agent decided it. This sprint instruments the reasoning layer: tool-selection rationale, memory state at each span, model confidence signals, and schema contract violations. Without that layer, failures are invisible until a customer reports them. Per industry data, up to 40% of AI integration failures are silent — they never appear in standard logs at all.
Yes. If the Day 1 trace audit reveals complexity beyond the $3,500 scope (e.g., 5+ agent handoffs, cross-tenant data isolation, or regulatory audit requirements), Milo's analysis will surface this within 24 hours and recommend the $5,000 Deep tier. You can adjust before any payment is finalized — no surprises.
The 5-day window covers artefact production from confirmed kickoff. Milo's sprints include one round of targeted revisions (scope: minor attribute adjustments, missing trace event coverage, or doc formatting). Major scope changes — adding a sixth agent type or redesigning span topology from scratch — are scoped separately. Contact miloantaeus@gmail.com before day 4 to flag scope concerns at no charge.