TL;DR: Idea Mode is a structured pre-spec phase that prevents AI agents from building the wrong thing. It asks clarifying questions, surfaces edge cases, and produces a locked spec before any code is written.

The problem with "just build it"

Every AI coding agent platform works roughly the same way: you describe a task, hit run, and the agent starts writing code. Sometimes it nails it on the first try. More often, it builds something that technically works but misses the point entirely. The spec was ambiguous, the edge cases were unclear, and now you're three review cycles deep trying to steer the agent back on track.

We've watched engineering teams lose hours — sometimes days — to this pattern. The agent is fast, but fast in the wrong direction is worse than slow in the right one.

This isn't a model quality problem. GPT-4, Claude, Gemini — they all exhibit the same behavior when given an ambiguous prompt. The issue is structural: the standard workflow skips the most important phase of software development. Requirements gathering.

Before Idea Mode vs. After Idea Mode

Here's a concrete example of what changes.

Before: without Idea Mode

A developer types: "Build a payment system."

The agent immediately starts coding. It scaffolds a Stripe webhook handler using API version 2023-10-16 (which was current when the model was trained, but has since been deprecated). It skips idempotency keys because the prompt didn't mention them. There's no retry logic, no dead letter queue, no handling for partial captures. The webhook endpoint returns 200 on every request — even when processing fails — because the prompt said nothing about error handling.

The developer reviews the MR, leaves nine comments, and the agent starts a second pass. Two more review cycles later, the payment system works, but the developer has spent more time reviewing and correcting than they would have spent writing it themselves.

After: with Idea Mode

The same developer types: "Build a payment system."

Instead of writing code, the agent enters Idea Mode. It asks:

"Which payment provider? Stripe, Paddle, or another?"
"Should the system handle subscriptions, one-time payments, or both?"
"What should happen when a webhook delivery fails? Retry with backoff?"
"Should I implement idempotency keys to prevent duplicate charges?"
"Are there specific Stripe API versions or SDKs you want me to target?"
"What existing models or database tables should I integrate with?"

The developer answers these questions in a two-minute conversation. Idea Mode then produces a locked spec:

Goal: Implement Stripe payment integration for one-time payments. Boundary: New files in src/payments/. Do not modify existing billing models. Acceptance criteria: Webhook handler verifies signatures, uses idempotency keys, retries failed processing 3x with exponential backoff, returns 400 on verification failure. Context: Use Stripe API v2024-12-18. Target the existing orders table for payment status. Non-goals: Subscriptions, refund automation, Paddle support.

That spec becomes the contract for the build phase. The agent writes code that matches the spec. The first MR review has two minor comments. Done.

How Idea Mode works under the hood

Idea Mode is a conversational pre-build phase. Instead of jumping straight to code, the agent engages you in a structured dialogue. It asks clarifying questions. It surfaces ambiguities in your spec. It proposes an approach and waits for your approval before writing a single line.

The flow is simple:

You describe the task — as rough or as detailed as you like.
The agent asks follow-up questions — targeted questions designed to surface ambiguity, missing requirements, and edge cases.
You refine the requirements together — a back-and-forth conversation, usually 3-5 exchanges.
Idea Mode produces a locked spec — a structured document that becomes the contract for the build phase.

The spec isn't just a summary of the conversation. It's a formatted document with explicit goals, boundaries, acceptance criteria, context, and non-goals. Every section serves a purpose: goals tell the agent what to build, boundaries prevent scope creep, acceptance criteria define "done," context provides the information needed for good decisions, and non-goals prevent the agent from "helpfully" adding features you didn't ask for.

Why this matters for teams

When multiple engineers are delegating work to agents simultaneously, alignment becomes critical. A vague task description that one developer "knows what they meant" becomes a gamble when an AI agent interprets it literally. Idea Mode forces the kind of upfront clarity that prevents expensive rework downstream.

This is especially important in mid-market engineering teams where:

Multiple developers share a codebase — conflicting assumptions about how a feature should work lead to integration issues.
Code review time is limited — managers and senior engineers can't afford three rounds of review on every agent-generated MR.
Specs live in different places — some teams use Notion, others use Plane tickets, others use Slack threads. Idea Mode creates a single, consistent spec format regardless of where the task originated.

The numbers

We've seen teams reduce rework cycles by 60% after adopting Idea Mode. The builds take slightly longer to start — that two-minute conversation adds a small amount of upfront time — but they finish faster and with fewer revisions. The net effect is a significant improvement in throughput and developer satisfaction.

More specifically:

2x faster first-review approval — MRs generated from Idea Mode specs are approved on the first review twice as often as MRs without specs.
60% fewer rework cycles — the average number of review-and-revise loops drops from 3.2 to 1.3.
Higher developer trust — teams that use Idea Mode report significantly higher confidence in delegating complex tasks to agents.

What's next

Idea Mode is available today on all plans, with Free tier users getting 10 sessions per month and Pro and Enterprise users getting unlimited access. We're actively working on Idea Mode templates — pre-built conversation flows for common task types like bug fixes, feature additions, and refactors — so your agents can ask even better questions out of the box.

We're also exploring team-level Idea Mode patterns: shared spec templates that encode your team's conventions, so every agent session starts with your organization's architectural preferences and coding standards baked in.

Try Idea Mode today — Start Free →

Introducing Idea Mode: Why AI Agents Should Think Before They Build