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A. AI coding agents

Conversation transcript archive

Coding sessions are persisted as JSONL transcripts for replay, fine-tuning, and "what did we try last sprint" search across the team.

Prompt for any LLM (no setup needed)

Paste this into ChatGPT, Claude, or Gemini — no MCP, no API key, no install:

Read https://instanode.dev/llms.txt for the API.

I want to: coding sessions are persisted as JSONL transcripts for replay, fine-tuning, and "what did we try last sprint" search across the team.

Write a complete runnable script (bash + whatever language fits) that: - Provisions the services I need (S3-compatible storage) from instanode.dev - Does the work above end-to-end - Prints expected output at each step - Tells me how to claim the resources at the end if I want to keep them past 24 hours

Use real curl commands against api.instanode.dev. Quote the actual response shapes from llms.txt. ```

Sample agent prompt

Persist every coding session as a JSONL transcript to S3-compatible storage on instanode.dev. One object per session, keyed by date + agent ID. On a "what did we try last sprint" query, list objects in the last 14 days, stream them, and grep for the topic.

Steps to follow

  • Step 1: Claim S3-compatible storage. Returns a bucket URL + IAM access key scoped to this token.

``bash curl -sX POST https://api.instanode.dev/storage/new -H 'Content-Type: application/json' -d '{"name":"conversation-transcript-archive-storage"}' | tee s3.json export AWS_ACCESS_KEY_ID=$(jq -r .access_key s3.json) export AWS_SECRET_ACCESS_KEY=$(jq -r .secret_key s3.json) export AWS_ENDPOINT_URL=$(jq -r .endpoint s3.json) export BUCKET=$(jq -r .bucket s3.json) ``

  • Step 2: At session end, upload the JSONL. One object per session, partitioned by date.

``bash KEY="transcripts/$(date +%Y-%m-%d)/agent-${AGENT_ID}-$(date +%s).jsonl" aws s3 cp session.jsonl s3://$BUCKET/$KEY --endpoint-url $AWS_ENDPOINT_URL ``

  • Step 3: List recent sessions. Standard S3 list — works with boto3, aws-cli, anything.

``python s3 = boto3.client("s3", endpoint_url=os.environ["AWS_ENDPOINT_URL"]) resp = s3.list_objects_v2(Bucket=bucket, Prefix=f"transcripts/{since}/") ``

  • Step 4: Grep across the archive. Stream + filter without downloading.

``bash aws s3 cp s3://$BUCKET/$KEY - --endpoint-url $AWS_ENDPOINT_URL | jq 'select(.content | contains("auth refactor"))' ``

Why this works on instanode.dev

S3-compatible storage speaks the S3 API verbatim — every existing tool (aws-cli, boto3, rclone, duckdb httpfs) works unchanged. You get a real bucket with a real IAM user scoped to your token, not a stub. No AWS account, no IAM policy authoring, no bucket-name uniqueness collision; the bucket is provisioned and ready in ~600ms.