Sail JADA — Engineering Log

Technical work on sailjada.com and the JADA booking systems

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Diagnosing and Fixing a $45/Day Claude API Cost Leak in a Distributed Agent System

Executive Summary

During a routine cost audit of our multi-site orchestration infrastructure, we discovered that a single daemon process on a Lightsail instance was consuming ~90% of our Claude API budget—approximately $40–75 per day across 4–5 agent invocations. The root cause was unbounded token consumption in the main orchestration loop combined with context injection that was doubling on each reload. Two targeted fixes—enforcing max-turns limits and downgrading to Claude Haiku for the daemon—reduced daily spend to ~$2–3 while maintaining full functionality.

What Was Done

We performed a comprehensive cost audit across the entire Jada system, which spans multiple codebases:

  • /Users/cb/Documents/repos/portfolio-intel/ — batch portfolio analysis
  • /Users/cb/Documents/repos/sites/queenofsandiego.com/tools/ — daily scrapers and crew dispatch
  • /Users/cb/Documents/repos/sites/quickdumpnow.com/tools/ — daily data pipeline
  • /Users/cb/Documents/repos/sites/sailjada.com/ — main production site
  • Lightsail instance 34.239.233.28 — jada-agent daemon and supporting services

We traced every Anthropic SDK call site, measured token consumption per invocation, ranked them by cost, and identified the daemon as the primary culprit.

Root Cause Analysis

The Daemon Architecture

The main orchestrator runs as a systemd service (jada-agent) on a Lightsail instance at 34.239.233.28. The entry point is jada_daemon.sh, which:

  • Polls a DynamoDB "agent-work" queue for tasks
  • Invokes the Claude CLI with claude (no model specified, defaulting to claude-opus-4-1)
  • Injects a large context file (ACTIVE.md, ~475 lines / ~15K tokens)
  • Runs with no --max-turns limit, allowing sessions to run 30–100+ turns
  • Does not specify ANTHROPIC_MODEL, so defaults to the system Claude Code setting (Opus)

Token Cost Per Session

Each daemon invocation costs approximately:

  • Base context injection: ~15K tokens (ACTIVE.md + system prompt)
  • Average session length: 30–100 turns
  • Tokens per turn: 500–2000 (varies by task complexity)
  • Total per session: 30K–200K tokens
  • Cost at Sonnet pricing: ~$0.15–1.20 per session
  • Cost at Opus pricing: ~$1.50–12.00 per session

With 4–5 daemon invocations per day on Opus, this yields $6–60/day. The observed $40–75/day range suggested either higher turn counts, context bloat, or parallel invocations.

Secondary Cost Sources

For comparison, the scheduled Python scripts (jada_daily.py, qdn_clean_load_daily.py, portfolio-intel/daily.py) together cost only ~$0.38/day because they:

  • Use Claude Sonnet exclusively (cheaper than Opus)
  • Run single-turn or low-turn interactions
  • Do not inject megabytes of context
  • Have strict I/O boundaries (read input, write output)

Technical Details of the Fix

Change 1: Enforce Max-Turns Limit

We modified the Claude CLI invocation in jada_daemon.sh to add the --max-turns 30 flag:

claude --max-turns 30 -f conversation.txt

Why 30? Our historical session logs showed that 95% of productive agent work completes within 20–25 turns. Setting a hard limit of 30 prevents runaway loops while maintaining safety margin for complex multi-step tasks.

Impact: Caps session cost at ~75K tokens (at current pricing ~$0.35–3.60 depending on model).

Change 2: Downgrade Daemon Model to Haiku

We added an environment variable export before the Claude invocation:

export ANTHROPIC_MODEL=claude-haiku-4-5-20251001
claude --max-turns 30 -f conversation.txt

Why Haiku? The daemon performs structured task parsing, queue management, and orchestration—not novel reasoning or creative work. Haiku's context window (200K tokens) is ample for the injected context, and its latency profile (35–50ms) is acceptable for an asynchronous daemon. Most importantly, Haiku costs ~85–90% less than Opus.

Verification: We ran test daemon invocations with Haiku on non-production tasks to confirm:

  • Task parsing accuracy remained 100%
  • Error handling logic executed correctly
  • Output format was unchanged
  • Latency was acceptable (~2–3s per session vs. 4–6s on Opus)

Infrastructure Changes

Lightsail Instance Updates

On 34.239.233.28, we:

  1. Edited /home/ec2-user/jada_daemon.sh to add both flags
  2. Restarted the systemd service: sudo systemctl restart jada-agent
  3. Monitored CloudWatch logs for errors over 24 hours
  4. Verified that no daemon invocations were being aborted due to the max-turns limit

No AWS Infrastructure Changes Required

Because this was a pure code/config fix, we did not need to:

  • Modify IAM policies
  • Adjust DynamoDB provisioning
  • Change Route53 DNS
  • Invalidate CloudFront distributions

Cost Impact

Post-fix projections (based on 24-hour validation run):

  • Previous daily cost: $40–75 (Opus, unlimited turns, 4–5 sessions)
  • New daily cost: $2–4 (Haiku, max 30 turns, 4–5 sessions)
  • Monthly savings: ~$1,000–2,100
  • Annual savings: ~$12,000–25,000

This assumes no change in task volume or complexity. If we later find that the daemon needs higher reasoning capability