Skip to content
← All Research
Part 1October 2025

Productivity Multipliers

Measuring the productivity multiplier of agentic coding vs pre-AI baselines across churn and net code metrics.

Agentic
Coding

Early Findings Benchmark

Part 1: Productivity Multipliers Insights

Marcio Sete | October 2025

1/12

There's a widespread scepticism about the productivity multipliers coming from AI coding. I'm experiencing unprecedented productivity whilst my industry peers continue to see only marginal gains.

2/12
To resolve the dissonance, I measured it.
Placebo effect or can agentic coding unlock 10X+ productivity?
3/12

The Benchmark Setup

Metrics:
Churn

Lines of code (LOC) added + deleted in commits merged to main.

Net Code

Net new code (Adds - deletes) integrated in production, representing codebase growth.

Measured across TypeScript/JavaScript/React; generated/lock/build files excluded.
4/12

Four Groups

1. Pre-AI Baseline (2020-2023)

Before AI coding was a thing

My control group.

2. AI Augmentation (2024- early 2025)

Where most organisations are now

Using ChatGPT, Copilot, Cursor, and VSCode extensions.

3. Agentic Coding (Aug-Sept 2025)

Soon to be the new normal

One Product Engineer orchestrating a fleet of up to 10 agents working in parallel in one codebase.

4. Founder Mode (Aug-Sept 2025)

The competitive threat

Agentic Coding taken to the extreme: ~100-hour weeks, across multiple product codebases.

5/12

The Results

Baseline Group AI Augmentation Agentic Coding Founder Mode
Churn 5,986 8,079 58,853 126,499
Net Code 1,416 3,870 31,811 61,928
Baseline Group AI Augmentation Agentic Coding Founder Mode
Churn 1X Multiplier: 1.3X Multiplier: 9.8X Multiplier: 21.1X
Net Code 1X Multiplier: 2.7X Multiplier: 22.5X Multiplier: 43.7X
Arithmetic averages per engineer per calendar month; main-branch merges only; generated/lock/third-party dirs excluded.
6/12

Key Findings

Agentic Coding delivered ~22× more net new code than the pre-AI baseline.

At the extreme, founders can reach ~44× productivity, churning ~130,000 lines per month and growing product codebases at ~60,000 lines per month.

Net Code/Churn efficiency improved from ~24% (baseline) to ~50% (agentic)-approximately 2× more efficient.

Net/churn efficiency plateaus around 2× as more agents run in parallel-the likely the ceiling of current tech.

7/12

Time Compression

Project Timeline Comparison
Pre-AI Baseline AI Augmentation Agentic Coding
12 months ~4.5 months 16 days
24 months ~9 months 32 days
36 months ~14 months 48 days
Time to First 100k Lines of Code
Pre-AI Baseline AI Augmentation Agentic Coding
1 engineer ~71 months ~26 months ~3 months
5 engineers ~14 months ~5 months
8/12

What This Means for Organisations

Talent shift

One product-engineer with agentic orchestration can approach the output of 20+ pre-AI engineers (order-of-magnitude shift). This completely changes the ratio of engineers, designers, and product managers.

Time-to-market compression

Features that took quarters now take days; products that took years now take months or weeks.

Competitive moats erode

Incumbents' size advantage diminishes when challengers can build 20-40× faster with a tiny fraction of headcount.

The bottleneck shifts

Product strategy, user research, and go-to-market become the constraints, not engineering capacity.

9/12

Dopamine-Driven Over-Engagement

In high-velocity "fleet orchestration" workflows, engineers can experience rapid, repeated "wins" (tasks getting completed, tests passing, agents reporting back). This compresses natural recovery cycles that used to occur during coding sessions.

The result is a continuous reward loop-akin to doom-scrolling-where engineers chase "just one more prompt," extending sessions, skipping breaks, and losing somatic cues of fatigue.

Short-term output rises; cognitive cost accumulates. Left unmanaged, this increases the risk of over-engagement, decision fatigue, and eventual burnout, despite nominally higher productivity.

10/12
⚠️

The Incumbent's Dilemma

The question for incumbents isn't "can we work like that?" It's "how do we compete when challengers can?"

Your advantages (capital, customers, brand) matter less if a challenger reaches technical parity before your next board meeting.

What are you going to do about it?

11/12

The Question

Can you afford to wait while competitors move up to
22× faster?

Full report available on request.
12/12