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OpenAI Codex Mid-Turn Steering: The Killer Feature for GTM Teams [2026]

· 6 min read

When GPT-5.3-Codex dropped on February 5, 2026, everyone focused on the "25% faster" headline. But the real game-changer? Mid-turn steering.

This feature lets you redirect an AI agent while it's working—not after it finishes. For GTM teams running complex automation, this changes everything.

Codex mid-turn steering: Human directing AI mid-task

What is Mid-Turn Steering?

Traditionally, when you ask an AI to do something, you wait until it's done to give feedback. If it goes off track, you:

  1. Wait for completion
  2. Read the output
  3. Write a correction prompt
  4. Start over

Mid-turn steering breaks this pattern. You can intervene during execution:

You: Build a lead scoring model based on our HubSpot data

Codex: [starts working]
- Pulling contact fields...
- Analyzing conversion patterns...
- Building scoring criteria...

You: Actually, weight company size more heavily than title

Codex: [adjusts mid-task]
- Updating weight for company_size field...
- Recalculating score thresholds...
[continues with adjustment]

No restart. No lost work. Just a course correction.

Why This Matters for GTM

1. Complex Automation Doesn't Fail Silently

When building sales automation, you often don't know exactly what you want until you see the first attempt. Mid-turn steering lets you:

  • Watch the agent's approach in real-time
  • Correct misunderstandings immediately
  • Guide toward edge cases as they appear

Without this, a 20-minute automation task might need 3-4 full restarts to get right.

2. Better Collaboration with AI

Mid-turn steering makes AI feel less like a black box and more like a collaborator. You're not just prompting and praying—you're actively directing.

For sales leaders building complex workflows, this means:

  • Faster iteration cycles
  • More precise outputs
  • Higher confidence in automation

3. Reduced Token Waste

Every restart burns tokens. Mid-turn steering reduces:

  • Repeated context loading
  • Duplicate work
  • Prompt engineering overhead

For teams running Codex at scale, this adds up.

Human giving mid-task feedback with course correction

GTM Use Cases for Mid-Turn Steering

Building Custom Lead Scoring

Traditional approach:

  1. Ask Codex to build a lead score
  2. Wait 10 minutes
  3. Realize it weighted "email opened" too heavily
  4. Start over with clarification
  5. Wait another 10 minutes

With mid-turn steering:

  1. Ask Codex to build a lead score
  2. Watch it start weighting criteria
  3. "Wait—de-emphasize email opens, focus on website visits"
  4. Codex adjusts in real-time
  5. Get the right model in one pass

Generating Email Sequences

Traditional approach:

  1. "Write a 5-email nurture sequence"
  2. Wait for all 5 emails
  3. Email 3 is too salesy
  4. Restart or write complex follow-up prompt

With mid-turn steering:

  1. "Write a 5-email nurture sequence"
  2. After email 2: "Make these more educational, less pitch-focused"
  3. Codex adjusts emails 3-5 accordingly
  4. Done

Building Pipeline Dashboards

Traditional approach:

  1. "Build a pipeline dashboard showing X, Y, Z"
  2. Wait for completion
  3. Visualizations aren't quite right
  4. Describe changes in detail
  5. Hope it understands

With mid-turn steering:

  1. "Build a pipeline dashboard"
  2. See the chart types being chosen
  3. "Actually, use bar charts for that, not pie"
  4. Watch it switch mid-build
  5. "Add a filter for deal size"
  6. Done with all adjustments in one session

How to Use Mid-Turn Steering

In Codex CLI

# Start a task
codex run "Build a HubSpot integration that syncs new contacts"

# While it's running, type to intervene
> Also add error handling for rate limits
> Skip the logging for now, we'll add that later

In Codex Cloud (Web UI)

The Codex dashboard shows real-time execution. A sidebar lets you:

  • See what the agent is currently doing
  • Type interventions
  • Pause/resume execution
  • Save partial progress

Via API

const session = await codex.createSession({
task: "Build lead enrichment pipeline",
onProgress: (state) => console.log(state),
allowSteering: true
});

// Intervene mid-task
await session.steer("Use Apollo for enrichment instead of Clearbit");

Best Practices for Mid-Turn Steering

1. Let It Start Before Steering

Don't intervene in the first 10 seconds. Let Codex show its approach first—you might learn something.

2. Be Specific with Corrections

❌ "That's not quite right"
✅ "Use percentage instead of raw numbers for the conversion column"

3. Steer Early, Not Late

If you see it going the wrong direction, intervene immediately. Don't wait until it's 80% done.

4. Save Checkpoints

For complex tasks, tell Codex to checkpoint progress: "After each major step, commit and show me the current state"

This lets you roll back if steering doesn't work.

5. Don't Over-Steer

Every intervention has overhead. If you're steering every 30 seconds, your initial prompt probably wasn't clear enough.

Mid-Turn Steering vs. Other Approaches

ApproachProCon
Single promptFast for simple tasksNo correction possible
Chain of promptsMore controlContext lost between prompts
Agent loopsAutonomousHard to intervene
Mid-turn steeringBest of both worldsRequires Codex

Mid-turn steering gives you the autonomy of agents with the control of manual prompting.

Real Example: Building a Competitor Alert System

Here's a real session transcript (abbreviated):

Me: Build a system that alerts me when competitors publish new content

Codex: Starting. I'll:
1. Set up RSS feeds for competitor blogs
2. Create a daily digest
3. Send via email

Setting up RSS parser...

Me: Actually, send via Slack not email

Codex: Switching to Slack webhook...
Setting up #competitor-intel channel post...

Me: Also check their Twitter, not just blogs

Codex: Adding Twitter API integration...
Will monitor @Warmly_AI, @CommonRoom...

Me: Add @6sense too

Codex: Added. Continuing with alert formatting...

[5 minutes later]

Codex: Done. System checks hourly, posts to #competitor-intel
when new content detected.

That would have been 3-4 restarts without mid-turn steering.

Limitations to Know

1. Not All Tasks Support Steering

Some operations (like API calls mid-flight) can't be interrupted. Codex will tell you when steering isn't possible.

2. Token Cost Still Applies

Steering doesn't reduce total tokens—it just uses them more efficiently.

3. Requires Real-Time Attention

If you're not watching, you can't steer. For hands-off automation, traditional approaches might be better.

The Bottom Line

Mid-turn steering is Codex's competitive moat for complex GTM automation. It transforms AI from "prompt and pray" to "collaborative building."

For teams building:

  • Custom integrations
  • Complex workflows
  • Multi-step automation

This feature alone justifies using Codex over alternatives.


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