INVEST in Autopilot: How a 50-Line Bot Saves Sprint Planning

Why This Matters. 

Long-time readers know we’ve joked about strict Definition-of-Ready checklists before. A simple list can’t capture every detail of product discovery work, and teams sometimes misuse DoR as a gate to block progress. However, we also see value in agreeing on what “ready” looks like, especially when handling AI-generated stories quickly. 

In complex fields like telehealth, fintech, and deep SaaS integrations, the question “Is this really ready?” quickly becomes complicated. Title? Easy. Acceptance criteria that truly prove the feature works? Getting harder. Is this ready for me to start coding? Even more difficult. When are we ready? I have often said that our teams need to embrace ambiguity and have enough knowledge to get started, while being comfortable learning more as we work. That is a delicate balance, though. 

Enter the bot: not to replace judgment, but to highlight obvious gaps before twenty minds gather. It sends a message about “missing acceptance criteria” at 10 a.m., so the PO can fix it by lunch, saving the team a detective mission during Sprint Planning. We still expect developers to challenge assumptions, UX to improve flows, and QA to expand tests; the checklist just helps start those deeper discussions on solid ground. The judgment remains human; the bot simply sets the stage. 

The Pain. 

Most teams “have” a DoR, but it resides in a wiki nobody checks at 4 p.m. on deadline day. Manual gatekeeping fails for three reasons:

1. Invisible checklist: The PO believes the story is Done; developers realize gaps only during planning.
2. Time-box panic: Identifying issues mid-meeting consumes time and frustrates everyone.
3. Human forgetfulness: Even disciplined teams overlook details when 40 tickets flood in the night before.

Result: scope creep (or learn), unclear acceptance criteria, and stories that expand mid-sprint. Not necessarily evil, just is there a way to prevent more of it; maybe, maybe not.

The Bet. 

We’ll connect a Node.js Slack app that listens for new backlog links, reads a JSON checklist, and flags any INVEST violations in under five seconds. The bot doesn’t merge or reject; it starts a thread tagging the story owner: “Missing testable criteria, please add.” We can adjust it to call out issues based on the idea if its an Epic or early idea, perhaps its not necessary to have some of these details. We don't want it noisy, so you might adjust it based on some variables you have in your own work environment. I am a fan of the Product Backlog Iceberg; so tune accordingly. 

Fixes occur asynchronously, not during a call. Planning resumes its true role: negotiating trade-offs and forecasting delivery, we are not taking that away.

Step by Step.

What you need before you start. Keep in mind we chose these tools, you might have something different, it's fine. This is just helping you build out your own framework, but also serving as a working example:

• Slack workspace & channel: choose (or create) #backlog-triage; everyone who refines stories should be in it.
• Slack App credentials: a Bot Token and Signing Secret generated in https://api.slack.com/apps.
• Public URL for events: Heroku, Fly.io, Render, or an ngrok tunnel during dev; Slack’s Events API must reach your endpoint.
• Backlog system API token: we use JIRA (JIRA_TOKEN) with read scope for the fields you’ll check, no I am not a JIRA fanboy; far from, but one of the most widely used tools, so...
• Definition-of-Ready checklist: start simple: ["title","acceptanceCriteria","estimation"]. Map each key to its JIRA field or custom field ID.

Tip: Keep the checklist in dor.json so you can add or drop rules without touching code.

How the Flow Works

Using the Output

The bot’s goal is to provide hints, not final judgments. It highlights missing fundamentals early so the live conversation can focus on nuance, such as hidden dependencies, UX polish, and architectural trade-offs, the human effort that makes backlog refinement meaningful. 

• Real-time readiness dashboard: Filter Slack for messages from the bot to see how many stories still have open gaps; a valuable KPI for PO throughput.
• Facilitator cue: Scrum Master reviews #backlog-triage before planning; red gaps indicate “delay or fix.”
• Training signal: Recurring gaps highlight where the team needs coaching (e.g., missing estimation → revisit story-point process).

 The Steps

INDEX.js

Let's take a look at the code for this magic :) 

// npm i @slack/bolt node-fetch
const { App } = require('@slack/bolt');
const fetch   = require('node-fetch');
const fs      = require('fs');
const app = new App({
  token:  process.env.SLACK_BOT_TOKEN,
  signingSecret: process.env.SLACK_SIGNING_SECRET
});
const DoR = JSON.parse(fs.readFileSync('dor.json')); // e.g., ["title","acceptanceCriteria","estimation"]
// Listen for any link dropped in #backlog-triage
app.event('link_shared', async ({ event, client, context }) => {
  const url = event.links[0].url;
  if (!url.includes('jira')) return;                 // only JIRA links in this bot demo
  // Pull story JSON via JIRA API
  const story = await fetch(url + '?fields=summary,description,customfield_test,storyPoints', {
    headers: { Authorization: 'Bearer ' + process.env.JIRA_TOKEN }
  }).then(r => r.json());
  const gaps = [];
  if (!story.fields.summary)          gaps.push('Missing *title*');
  if (!story.fields.customfield_test) gaps.push('No *acceptance criteria*');
  if (!story.fields.storyPoints)      gaps.push('No *estimation*');
  if (gaps.length) {
    const blocks = gaps.map(g => `• ${g}`).join('\n');
    await client.chat_postMessage({
      channel: event.channel,
      thread_ts: event.message_ts,
      text: `:warning: Definition-of-Ready gaps detected:\n${blocks}\n_Fix and react with :white_check_mark:_`
    });
  }
});
// React with ✅ when gaps cleared
app.event('reaction_added', async ({ event, client }) => {
  if (event.reaction !== 'white_check_mark') return;
  await client.chat_postMessage({
    channel: event.item.channel,
    thread_ts: event.item.ts,
    text: `:tada: All DoR checks passed. Story ready for planning!`
  });
});
(async () => { await app.start(process.env.PORT || 3000);})();
console.log('DoR bot running');

Now for our DoR Checklist (found in dor.json)

[
 "title",
 "acceptanceCriteria",
 "estimation",
 "risk",
 "priority"
]

What Good Looks Like.

When the bot is humming, your backlog workflow feels almost friction-free (almost). Stories appear in #backlog-triage, the bot scans them in seconds, and team members see a short, actionable thread instead of a wall of unknowns. 

Most gaps are resolved the same day they surface, so by the time Sprint Planning arrives, most tickets on the board already meets the team’s Definition of Ready. Meetings begin with estimating and sequencing; work that requires collective brainpower, rather than hunting for missing acceptance tests or arguing over story titles. Over a few sprints, you’ll notice three signals:

1. Slack threads show gaps closed within the hour: fast feedback loops keep momentum high.
2. Sprint planning shrinks by 15–20 minutes: more time for trade-offs, less for detective work.
3. Developers report higher confidence in story clarity: fewer mid-sprint surprises, smoother hand-offs to QA.

The bot helps to shift administrative friction to the edges, leaving the core of refinement, shared understanding and technical creativity, to humans.

Validation beats automation

The bot highlights missing pieces, but the team still agrees on scope, risk, and design. INVEST remains honest, but judgment stays human. Automate the guardrails, and reserve mental effort for nuance.

People thrive → Service shines → Profit follows.