From Hand-Coding to Agent Orchestration: An AI-First Workflow for 2025

Published: August 27, 2025
Reading time: ~8 minutes

TL;DR

• AI-first is not “let the model do everything.” It’s a disciplined workflow using agents to design, scaffold, code, and validate.
• Modern stack: MCP servers for tools/data, Cline (or similar agent IDE) for structured tasks, and an LLM (e.g., Anthropic Sonnet 4 via Bedrock or OpenAI) for high-quality reasoning.
• Ship faster by treating AI like a junior team: write great briefs, set guardrails, and require evidence (tests, diffs, logs).
• Start small: one repo, one golden path, one definition of done. Add agents only where they measurably reduce cycle time or defects.

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Why “AI-First” ≠ “Auto-Pilot”

“Prompt and pray” yields drift, regressions, and mystery-meat PRs. AI-first is managerial: you control scope, interfaces, and quality; agents execute bounded work with proof.

Replace: long, speculative runs → short, instrumented cycles
Replace: hallucinated file edits → tool-mediated actions (MCP)
Replace: “it compiles” → tests, smoke, and diffs attached to PRs

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The Reference Stack (What actually works)

• Agent runner / IDE: Cline (or similar). Repo-aware tasks, rules, and memory.
• Model: Sonnet-class (e.g., Anthropic Sonnet 4 via Bedrock) or OpenAI equivalent—focus on reasoning, not just throughput.
• Tooling layer (via MCP servers):
  • fs: scoped read/write in src/, tests/, migrations/
  • git: feature branches, diffs, conventional commits
  • run: lint, test, smoke as first-class verbs
  • apis: safe test-mode clients (e.g., Stripe)
  • knowledge: coding standards, contracts, runbooks
  • evals: ESLint, Vitest/Jest, k6 wrappers

Ground the agent in reality with tools; don’t ask it to guess what it can measure.

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A Minimal AI-First Flow You Can Adopt Today

1) Write a one-page brief (humans & agents read the same one)

Example brief:

# Task: Stripe Webhook Ingestion
Goal: Verify HMAC; store events idempotently; expose metrics.

Constraints: Node 20 · TypeScript · Hexagonal · Postgres

Acceptance:
- POST /webhooks/stripe
- Verify `Stripe-Signature`
- Table `webhook_events(event_id UNIQUE, type, payload, received_at)`
- Exponential backoff for transient failures
- Vitest tests: HMAC + idempotency
- README updates + Mermaid sequence

Evidence in PR:
- Lint + test outputs
- 30s smoke log (k6 or curl loop)
- `git diff --stat` + list of files changed

2) Point the agent at your repo; demand a plan and skeleton

Request a directory plan, file-by-file changes, and a test list before code. Deny broad “search and replace” without a plan.

3) Run with real tools (MCP)

Prefer mcp-run:test over “the code should pass tests.” Prefer mcp-git:diff over “I changed some files.”

4) Require evidence

Every PR must include: diffs, linter output, test results, and a tiny smoke log.

5) Keep loops short

30–90 minutes per slice. If it’s not reviewable quickly, split it.

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The Loop (visual)

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A Tiny End-to-End Example

Express route

// src/routes/stripeWebhook.ts
import express from "express";
import type { Request, Response } from "express";
import { verifyStripeSignature, handleEvent } from "../services/stripeWebhook";

export const router = express.Router();

router.post("/webhooks/stripe", express.raw({ type: "application/json" }), async (req: Request, res: Response) => {
  try {
    const sig = req.headers["stripe-signature"];
    if (!sig || typeof sig !== "string") return res.status(400).send("Missing signature");

    const event = verifyStripeSignature(req.body, sig);
    await handleEvent(event);
    return res.status(200).send("ok");
  } catch (err: any) {
    if (err.name === "SignatureVerificationError") return res.status(400).send("Bad signature");
    console.error("webhook error:", err);
    return res.status(500).send("internal");
  }
});

Idempotent handler

// src/services/stripeWebhook.ts
import crypto from "crypto";
import { db } from "../db"; // your pg client
import { STRIPE_WEBHOOK_SECRET } from "../config";

export function verifyStripeSignature(rawBody: Buffer, signature: string) {
  const expected = crypto.createHmac("sha256", STRIPE_WEBHOOK_SECRET).update(rawBody).digest("hex");
  const provided = signature.split(",").find(s => s.startswith("v1="))?.slice(3);
  if (!provided || !crypto.timingSafeEqual(Buffer.from(expected), Buffer.from(provided))) {
    const e: any = new Error("SignatureVerificationError"); e.name = "SignatureVerificationError"; throw e;
  }
  return JSON.parse(rawBody.toString("utf8"));
}

export async function handleEvent(event: any) {
  const id = event.id;
  const type = event.type;

  const result = await db.query(
    "INSERT INTO webhook_events(event_id, type, payload, received_at) VALUES ($1,$2,$3, NOW()) ON CONFLICT (event_id) DO NOTHING RETURNING event_id",
    [id, type, event]
  );
  if (result.rowCount === 0) return; // duplicate; already processed

  // TODO: perform business actions based on 'type'
}

Migration

-- migrations/20250827_create_webhook_events.sql
CREATE TABLE IF NOT EXISTS webhook_events (
  event_id TEXT PRIMARY KEY,
  type TEXT NOT NULL,
  payload JSONB NOT NULL,
  received_at TIMESTAMPTZ NOT NULL DEFAULT NOW()
);

Unit test (Vitest)

// tests/stripeWebhook.test.ts
import { describe, it, expect } from "vitest";
import { verifyStripeSignature } from "../src/services/stripeWebhook";

describe("verifyStripeSignature", () => {
  it("throws on bad signature", () => {
    const body = Buffer.from(JSON.stringify({ ok: true }));
    expect(() => verifyStripeSignature(body, "v1=deadbeef")).toThrow();
  });
});

Smoke (k6)

// smoke/stripe.js
import http from "k6/http";
import { check, sleep } from "k6";

export default function () {
  const payload = JSON.stringify({ id: "evt_test_1", type: "ping" });
  const res = http.post("http://localhost:3000/webhooks/stripe", payload, {
    headers: { "Content-Type": "application/json", "stripe-signature": "v1=fake" }
  });
  check(res, { "status is 400 or 200": r => r.status === 400 || r.status === 200 });
  sleep(0.2);
}

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Policies & Guardrails (make “good” explicit)

Add a local rules file (e.g., .clinerules) and keep it tight:

project:
  name: service-registry
  language: typescript
  node_version: "20.x"

definition_of_done:
  - POST /webhooks/stripe with signature verification
  - DB migration: webhook_events(event_id PK)
  - Tests: HMAC + idempotency (Vitest/Jest)
  - Docs: README updates + Mermaid sequence
  - Evidence: lint/test/smoke logs in PR

guardrails:
  - No unrelated module changes
  - Small, meaningful commits
  - Use env-based config; never print secrets

If the agent can’t attach evidence, it isn’t done.

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What to Automate First (High-ROI)

1. Spec → Skeleton: folders, DI wiring, test harness.
2. Test Authoring: acceptance → runnable unit tests.
3. Boilerplate Integrations: webhooks, typed clients, SDK scaffolds.
4. Refactors with Proof: before/after diff + passing tests.
5. Docs & Diagrams: README deltas, Mermaid diagrams, change logs.

Skip high-blast-radius areas (prod migrations, secrets rotation) until guardrails mature.

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Safety, Cost & Risk Hygiene

• Token budgets: cap context, chunk large files, prefer tool reads over in-context dumps.
• Secrets hygiene: env/secret manager only; never paste secrets into prompts/logs.
• Human gate: every merge requires human review + CI.
• Data boundaries: redact PII in logs; keep artifacts short and relevant.

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Measure What Matters

• Lead Time: idea → merged PR
• Change Failure Rate: % of PRs requiring rollback/hotfix
• MTTR: time to recover when something breaks
• Golden Path Coverage: % of critical flows with tests/smokes

If agents don’t improve at least one, tighten scope, improve tools, or clarify briefs.

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A 1-Day Starter Plan

Morning

• Write the brief and .clinerules.
• Enable minimal MCP tools (fs, git, run).
• Give the agent read-only first; validate it lists files and proposes a plan.

Afternoon

• Green-field a tiny feature (health endpoint + test + README).
• Require evidence (lint/test/smoke) in the PR.
• Run CI; merge if green.

Evening

• Retro: what was noisy? tighten rules, shrink scopes.
• Pick one real feature for tomorrow; repeat the loop.

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FAQ (real questions teams ask)

Is “AI-first” overkill for small teams?
No—small teams benefit most. Agents chop boilerplate so you can focus on design and customer value.

Which model should we use?
Use what your org approves. Sonnet-class models are excellent at reasoning + code; process > logo.

What if the agent makes a mess?
Constrain scope, require tests/diffs, and prefer iterative refactors. If drift continues, your rules are too loose.

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