Implementation BlueprintExecution layer

Coral Bricks Client Agent Deployment (5-7 days)

A five to seven day playbook for agencies to stand up a client coding or research agent on Coral Bricks' OpenAI-compatible endpoint, using free cached reads and pay-per-token pricing to keep delivery costs predictable. Time: 5-7 days.

By InnovaAI ResearchPublished Updated

AI Infrastructure

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Blueprint

Coral Bricks Client Agent Deployment (5-7 days)

A five to seven day playbook for agencies to stand up a client coding or research agent on Coral Bricks' OpenAI-compatible endpoint, using free cached reads and pay-per-token pricing to keep delivery costs predictable.

Prerequisites
  • A cb_... API key created from the Coral Bricks dashboard
  • One client coding or research agent tool already in use (OpenCode, Codex CLI, GitHub Copilot, Cursor, Cline, Continue, or aider)
  • A representative agent loop with tool calls and long-context input to test against
  • Written client agreement on usage volume, since Coral Bricks bills per token rather than per seat
  • A staging environment where the client's existing stack can point at https://inference.coralbricks.ai/v1
Execution Timeline
  • 1.Create the cb_... API key in the Coral Bricks dashboard and store it in the client's secret manager
  • 2.Send an OpenAI wire-format request to https://inference.coralbricks.ai/v1 against coralbricks/glm-5.3-fp4 to confirm the key and endpoint respond
  • 3.Log the baseline latency and token counts for the client's current provider so the comparison is documented
  • 1.Run the client's real agent loop against coralbricks/deepseek-v4.1-flash-fast-fp4 and confirm streaming tool calls complete
  • 2.Test a long-context prompt up to 1M tokens to verify the client's use case fits inside the served window
  • 3.Record decode throughput on the client's own workload rather than relying on published benchmarks
  • 1.Point the client's chosen tool (OpenCode, Codex CLI, GitHub Copilot, Cursor, Cline, Continue, or aider) at the Coral Bricks endpoint
  • 2.Configure model selection and prompt templates for the client's specific coding or research task
  • 3.Verify that repeated context hits the free cached reads path so the client is not billed twice for the same prefix
  • 1.Instrument the agent loop to log input tokens, cache write tokens, and cache read tokens per session
  • 2.Build a simple cost tracker that multiplies logged usage against the published GLM 5.3 rates
  • 3.Set a monthly token ceiling in the client's application layer to prevent runaway agent loops
  • 1.Run a full end-to-end session with the client's team on their own data
  • 2.Document failure modes: context overflow, tool-call timeouts, and model fallback behavior
  • 3.Confirm the client can swap model slugs without rewriting their integration
  • 1.Write the runbook covering key rotation, model slug changes, and usage monitoring
  • 2.Train the client's internal owner on reading the cost tracker and adjusting the token ceiling
  • 3.Hand over the staging configuration as the reference implementation
  • 1.Deploy the configuration to the client's production environment
  • 2.Monitor the first production day for unexpected token spikes or cache misses
  • 3.Deliver the final usage and cost report against the day-one baseline
$2,500 setup fee for the Starter Agent offer, plus client usage billed at Coral Bricks rates: $1.12 per 1M input tokens and $1.68 per 1M cache write tokens on GLM 5.3, with cached reads free. Enterprise clients wanting dedicated VPC capacity are quoted by resources rather than tokens through contact sales.5-7 days
ROI Logic

The agency collects a $2,500 setup fee against roughly 20 hours of configuration work, so the delivery margin sits in the labor spread rather than in token resale. Ongoing margin comes from a monitoring retainer, since the client's token spend flows directly to Coral Bricks and the agency is not marking up inference. Free cached reads on repeated context keep the client's monthly bill low enough that the retainer survives budget review.

Deliverables
  • A working Coral Bricks endpoint configuration with the client's cb_... key wired into their agent tool
  • A cost tracker that maps logged token usage to Coral Bricks' published per-million rates
  • A runbook covering key rotation, model slug swaps, and token ceiling adjustments
  • A baseline-versus-production performance report covering latency, throughput, and cache hit rate
  • A trained internal owner at the client who can read usage logs and adjust limits
Definition of Done

The client's production agent loop runs against https://inference.coralbricks.ai/v1 with streaming tool calls, long-context handling, and a documented monthly token ceiling that the client's own team can adjust without agency involvement.

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