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Operator is a search backend for your own agents, jobs, and tools, not a browser tab. These are concrete systems you can build once you have the API wired into your stack. Unlike interactive tools such as Perplexity, these run on your schedule and inside your infrastructure.

Daily Briefing Agents

Trigger.dev or cron jobs that use Operator to send you a morning brief on what changed.

Self-Explaining CI

CI pipelines that ask Operator why a build failed and post a human-readable diagnosis.

Release & Risk Radar

Watchlists that track frameworks, APIs, and vendors and summarize only high-risk changes.

Context-Aware Slack Bots

Bots that answer “what’s going on?” by searching your stack and the broader web together.

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1. Daily research agent (Trigger.dev + Operator)

What you build
A scheduled agent that emails or Slacks you a short briefing every morning so you do not have to manually scan release notes, blog posts, and status pages. Stack
  • Trigger.dev (or any scheduler / job runner)
  • Operator API (OpenAI-compatible client)
  • Your email provider (Resend, Postmark, SES, etc.)
How it works
  • At 08:00 every weekday, Trigger.dev runs a job.
  • The job calls the Operator API with prompts like:
    • “What changed in Next.js, Prisma, Vercel, and Postgres since yesterday that could affect production apps?”
    • “Summarize the top three breaking changes or regressions I should know about, with links.”
  • Operator fans out across docs, GitHub issues, changelogs, and status pages, then returns a concise summary and links.
  • The job formats that into an email and sends it to your team.

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2. Self explaining CI failures

What you build
A CI pipeline that automatically explains failing jobs in human language and suggests likely fixes, right where developers already look. Stack
  • GitHub Actions / GitLab CI / CircleCI
  • Operator API
  • GitHub PR comments or Slack notifications
How it works
  • When a job fails, a follow-up step sends the error logs (or the key error lines) to Operator with a prompt like:
    • “Explain this CI failure and list the top three likely causes and fixes. Prefer solutions that reference official docs or GitHub issues.”
  • Operator:
    • Searches issues and docs for the error text.
    • Checks recent changelogs for breaking changes.
    • Synthesizes a short explanation plus probable fixes.
  • The CI workflow posts that explanation as a PR comment or Slack message, next to the failing job.

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3. Release and risk radar for your stack

What you build
A weekly “risk report” that tells you which libraries, APIs, or vendors in your stack shipped changes that could break you, and which are safe to ignore. Stack
  • A scheduled job (Trigger.dev, cron, Airflow, etc.)
  • Operator API
  • Notion/Confluence page, Slack channel, or email
How it works
  • You maintain a simple list of dependencies and services you care about (Next.js, Prisma, Stripe, your own API, etc.).
  • Each week, a job calls Operator with something like:
    • “For these dependencies, summarize what changed this week. Flag anything that looks breaking or high risk, and include links to the source docs or issues.”
  • Operator searches:
    • Official release notes and docs.
    • GitHub issues and discussions.
    • Vendor blogs and status pages.
  • The job writes a short report to a doc, wiki, or Slack channel so the team can skim it in minutes.

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4. “What is going on” Slack bot

What you build
A Slack bot that can answer questions like “what’s going on with our payments right now?” by combining external search with your own logs and dashboards. Stack
  • Slack bot / app
  • Operator API
  • Your own status endpoints, dashboards, or log summaries
How it works
  • In Slack, someone writes: “@OpsBot what’s going on with checkout errors in the last 24h?”
  • Your bot:
    • Pulls a short summary from your logs or observability tools.
    • Calls Operator with that summary plus a prompt:
      • “Given these errors and the services we use (Stripe, Cloudflare, Vercel), search for ongoing incidents, recent breaking changes, or known issues that might explain this.”
  • Operator searches vendor status pages, incident reports, and GitHub issues, then returns a synthesized answer with likely causes and links.
  • The bot posts a concise explanation and links to the relevant dashboards or incidents.

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5. “Explain this system” agent

What you build
An agent that can take a codebase, architecture diagram, or spec and generate an up-to-date, cited explanation using the best external material available. Stack
  • Your own agent (CLI, VS Code task, web app)
  • Operator API
  • Optional: repo indexing / code search
How it works
  • You send a short description of a system or component to your agent, for example:
    • “Explain how this Next.js + tRPC + Stripe stack works, and what I should watch out for when upgrading.”
  • The agent:
    • Optionally inspects your repo or config.
    • Calls Operator with the stack description and a prompt like:
      • “Search for up-to-date best practices, migration guides, and pitfalls for this stack. Return a concise, structured explanation with links.”
  • Operator searches docs, blogs, and issues, then returns a structured brief you can drop into docs, onboarding materials, or planning notes.