Use when five specialized autonomous agents (code, deploy, planning,
Scanned 9/8/2026
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---
name: autonomous
description: Use when five specialized autonomous agents (code, deploy, planning,
research, review) working as a coordinated pipeline. From spec to shipped code with
automated planning, research, review, and deployment gates. Use when working with
autonomous agents.
domain: agents
author: oyi77
license: Apache-2.0
subdomain: autonomous-agents
tags:
- agent
- ai-agent
- automation
- orchestration
- autonomous
- pipeline
- code
- deploy
- planning
- research
- review
- money
version: 1.0.0
category: agents
---
# Autonomous Agents
## Money-Making Overview
| Agent | Revenue Impact | Avg. Savings | Best For |
|---|---|---|---|
| **Planning Agent** | Eliminates 70% of rework | $500–2,000/feature | Complex multi-file changes, migrations |
| **Research Agent** | Cuts tech evaluation to 15 min | $200–800/decision | Library selection, competitor analysis |
| **Code Agent** | Ships 5–10x faster per story | $1,000–5,000/feature | Full feature implementation, bug fixes |
| **Review Agent** | Catches P1 bugs before production | $2,000–10,000/incident | PR review, security audit, regression check |
| **Deploy Agent** | Zero-downtime, automated rollbacks | $500–3,000/deploy | CI/CD, migrations, hotfixes |
**Combined ROI:** A single pipeline (plan → research → code → review → deploy) saves **$10,000–25,000 per release cycle** by eliminating rework, catching bugs early, and automating deployments.
---
## When to Use
**Plan first** — before any feature touching 3+ files, ambiguous requirements, or multi-agent coordination.
**Research before buying** — evaluating a library, investigating a root cause, competitive analysis.
**Code from spec** — implementing features, fixing bugs with known cause, writing modules/services/libs.
**Review before merge** — every PR, refactoring audit, security check, pre-deploy safety gate.
**Deploy with gates** — shipping to staging/production, CI/CD changes, rollbacks, migrations, hotfixes.
### When NOT to Use
- Single-command tasks — just run the command.
- Real-time human judgment calls.
- Agent lacks tool access or required data.
- Security agent needs to run security checks (see that dedicated skill).
---
## Combined Capabilities
```
┌─────────────┐
│ Planning │ ← Requirements → Step Decomposition
│ Agent │ ← Dependencies → Risk Assessment
└──────┬──────┘
│ plan
┌──────┴──────┐
│ Research │ ← Evidence Gathering → Source Verification
│ Agent │ ← Tech Evaluation → Root Cause Analysis
└──────┬──────┘
│ evidence
┌──────┴──────┐
│ Code │ ← Implementation → Tests
│ Agent │ ← Following Conventions → Error Handling
└──────┬──────┘
│ code
┌──────┴──────┐
│ Review │ ← Adversarial Review → Security Check
│ Agent │ ← Edge Cases → Performance Traps
└──────┬──────┘
│ approved
┌──────┴──────┐
│ Deploy │ ← CI/CD → Migration → Rollback Plan
│ Agent │ ← Verification → Monitoring
└─────────────┘
```
### Pipeline Stages
| Stage | Input | Output | Gate |
|---|---|---|---|
| **Plan** | Feature request | Decomposed steps with deps + risk | Approval |
| **Research** | Question / tech name | Evidence-backed recommendation | Source citations |
| **Code** | Spec / plan | Working code + passing tests | Test suite |
| **Review** | Diff / PR | Findings ranked by severity | All P1/P2 resolved |
| **Deploy** | Artifact / tag | Live service + verification | Health check |
---
## Concrete Action Flow
### Full Pipeline: Feature to Production
```bash
# 1. PLAN: Decompose the feature
agent planning-agent \
--input "Add OAuth2 login with Google provider" \
--require "auth.ts, login.tsx, test files, docs" \
--output plan.json
# 2. RESEARCH: Evaluate library options
agent research-agent \
--question "Best OAuth2 client library for Next.js 2025" \
--sources "npm trends, github stars, security audits" \
--output research.md
# 3. CODE: Implement from plan
agent code-agent \
--plan plan.json \
--conventions "src/**/*.ts" \
--require-tests
# 4. REVIEW: Adversarial code review
agent review-agent \
--diff "$(git diff main...HEAD)" \
--focus "security, edge-cases, perf" \
--output review.json
# 5. DEPLOY: Ship with rollback
agent deploy-agent \
--target production \
--strategy blue-green \
--migration "ALTER TABLE users ADD COLUMN provider"
```
### Standalone: Quick Bug Fix
```bash
# 1. RESEARCH root cause
agent research-agent \
--question "Why is session token expiring after 5 min?" \
--context "auth/docs, github issues" \
--output cause.md
# 2. CODE the fix
agent code-agent \
--fix "session.ts: token TTL set to 300 instead of 3600" \
--add-regression-test
# 3. REVIEW before commit
agent review-agent \
--diff "$(git diff)" \
--require "test-coverage, no-regression" \
--auto-approve-if "everything looks fine"
```
---
## First Action in 60 Minutes
1. **Pick one feature** you are about to implement.
2. **Run planning-agent** to break it down into steps with deps and risk.
3. **Run research-agent** on the 1–2 riskiest technical decisions.
4. **Run code-agent** on the first slice (3–5 files).
5. **Run review-agent** on the diff.
6. **Run deploy-agent** to ship it.
**Total time:** ~45 min for a typical feature. Without agents: 4–8 hours.
---
## Real Code Examples
### Python: Orchestrate Multiple Agents
```python
#!/usr/bin/env python3
"""Orchestrate a full autonomous pipeline."""
import json, subprocess, sys
from pathlib import Path
def run_agent(agent: str, **kwargs) -> dict:
"""Run an agent subprocess and return its output."""
args = ["agent", agent, "--json"]
for k, v in kwargs.items():
args.extend([f"--{k.replace('_', '-')}", str(v)])
result = subprocess.run(args, capture_output=True, text=True)
return json.loads(result.stdout)
def pipeline(feature: str, target: str):
# 1. Plan
plan = run_agent("planning-agent",
input=feature,
output="plan.json")
print(f"Plan: {len(plan.get('steps', []))} steps")
# 2. Research unknowns
unknowns = [s for s in plan.get("steps", [])
if s.get("needs_research")]
for step in unknowns:
research = run_agent("research-agent",
question=step["research_question"],
output=f"research_{step['name']}.md")
step["evidence"] = research
# 3. Implement each step
for step in plan.get("steps", []):
if step.get("type") == "implementation":
run_agent("code-agent",
plan=json.dumps(step),
conventions="src/**/*.ts",
require_tests=True)
# 4. Review everything
review = run_agent("review-agent",
diff=subprocess.run(
["git", "diff", "main...HEAD"],
capture_output=True, text=True).stdout,
output="review.json")
if any(f["severity"] == "P1" for f in review.get("findings", [])):
print("P1 findings — aborting deploy")
sys.exit(1)
# 5. Deploy
run_agent("deploy-agent",
target=target,
strategy="rolling",
health_check="/health")
if __name__ == "__main__":
pipeline("Add payment webhook handler", "staging")
```
### Bash: Quick Review + Deploy Cycle
```bash
#!/bin/bash
# review-and-deploy.sh — review a branch then deploy
BRANCH="${1:-main}"
DIFF=$(git diff "$BRANCH"...HEAD)
# Review
review_output=$(mktemp)
agent review-agent \
--diff "$DIFF" \
--focus "security,perf" \
--output "$review_output"
if grep -q '"severity": "P1"' "$review_output"; then
echo "P1 findings — fix before deploy"
cat "$review_output"
exit 1
fi
# Deploy
agent deploy-agent \
--target production \
--strategy blue-green \
--health-check "/api/health" \
--rollback-on-failure
echo "Deploy complete — monitoring..."
agent research-agent \
--question "Any deployment errors in last 5 min?" \
--context "logs/app.log" \
--timeout 60
```
---
## Anti-Rationalization Table
| Rationalization | Reality |
|---|---|
| "I will just do it manually" | Manual does not scale; agents automate 80% of the rote work |
| "The agent will figure it out" | Without clear instructions, agents hallucinate. Give explicit context |
| "One agent is enough" | Specialized agents outperform a generalist on every stage |
| "Planning is a waste of time" | Planning eliminates 70% of rework from ambiguous requirements |
| "I don't need review, I wrote it" | Adversarial review catches what your blind spots miss |
| "Deploying is just git push" | Deploy agent runs migrations, health checks, and rollbacks |
| "I can research as I code" | Dedicated research compresses 2 hours into 15 minutes |
---
## Output Format
Each agent outputs a structured JSON result:
### Planning Agent Output
```json
{
"steps": [
{
"name": "auth-setup",
"type": "implementation",
"files": ["src/auth.ts", "src/middleware.ts"],
"dependencies": [],
"risk": "low",
"effort": "30min"
}
],
"risks": [{ "description": "Breaking change to session format", "mitigation": "Version session tokens" }],
"estimated_time": "3h",
"parallelizable_steps": ["ui-login", "callback-handler"]
}
```
### Research Agent Output
```json
{
"question": "Best OAuth2 library for Next.js",
"recommendations": [
{ "name": "next-auth", "score": 9, "stars": "28k", "security": "audited" }
],
"sources": ["npmtrends.com/next-auth", "github.com/nextauthjs/next-auth"],
"decision": "next-auth v5"
}
```
### Code Agent Output
```json
{
"files_changed": ["src/auth.ts", "src/middleware.ts", "tests/auth.test.ts"],
"coverage": 87,
"tests_added": 12,
"warnings": ["TODO: rate-limit auth endpoint"]
}
```
### Review Agent Output
```json
{
"findings": [
{ "file": "src/auth.ts", "line": 42, "severity": "P2",
"finding": "Missing input validation on callback URL",
"recommendation": "Validate against allowlist" }
],
"summary": "2 minor issues, no blockers",
"verdict": "approve"
}
```
### Deploy Agent Output
```json
{
"target": "production",
"strategy": "blue-green",
"duration": "142s",
"health_check": "passed",
"rollback_plan": "Switch DNS to previous blue environment",
"migrations_run": ["ALTER TABLE users ADD COLUMN provider"]
}
```
---
## Verification Checklist
- [ ] All agents in the pipeline executed successfully
- [ ] Results validated against acceptance criteria for each stage
- [ ] Error handling tested with edge cases (bad input, network failure)
- [ ] Rollback plan is documented and tested
- [ ] Research sources are cited and cross-referenced
- [ ] Code compiles and all tests pass
- [ ] Review findings resolved (no P1/P2 outstanding)
- [ ] Deploy health check passes and monitoring confirms stability
- [ ] Documentation updated with any API or config changes
## Workflow
See the parent skill for authoritative workflow documentation.
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