The myth that AI is replacing engineers, in three numbers from this week

The myth

I have been counting the times I heard “AI is replacing engineers” this week, and I gave up after twelve.

The latest round started Sunday when news broke that Cognition was raising at a $25 billion valuation. As the humai.blog writeup put it, that is “more than the market cap of Etsy. More than Snap.” And the product Cognition sells is Devin, billed as “the world’s first autonomous AI software engineer.” The pitch in a sentence: point it at a Jira ticket, walk away, and the code, the tests, and the pull request show up while a human sleeps.

The market is currently pricing in that pitch. Engineers are reading it as an eviction notice. Boards are asking founders if they should freeze the headcount plan. None of those reactions are crazy. They are also, mostly, wrong.

Why it sounds right

The replacement story sounds true because three things are simultaneously real. Coding agents have gotten dramatically better in the last twelve months. Senior engineers I talk to are doing in an afternoon what they used to scope at two weeks. And the customer logos on the autonomy side are not theoretical. According to the same humai.blog piece, Devin’s customer list reads like a “Goldman Sachs cocktail party”: Goldman Sachs itself, Citi, Dell, Cisco, Palantir, Ramp, Nubank, and Mercado Libre.

When Cognition shows up at $25 billion in seven months, having gone from $1 million in ARR to $73 million inside nine months, the smoke-or-fire question feels settled. Something is on fire. The instinct to ask “do I still need engineers” is rational once you have seen those numbers in the same week.

The instinct is also incomplete. Because the same week produced two other numbers, and they live in a different story.

What the evidence says

Number one: IBM.

On Tuesday, IBM launched Bob, its own AI development partner. The line in the press release that nobody in the headlines picked up was the deployment metric. Specifically: 80,000 employees, surveyed users reporting an average 45 percent productivity gain. Eighty thousand. Still employed. Still using the tool.

That is the full vendor narrative for one of the most aggressive AI-coding rollouts in the world right now. It is not “we replaced 80,000 engineers.” It is “we gave 80,000 humans a 45 percent productivity uplift.” And IBM’s most quotable line from the same release was the part that should have led the news: “Fast AI without the right guardrails is not progress. It is just faster risk.”

Number two: Microsoft.

Asanify’s April 27 digest pulled the preview metrics Microsoft published when Copilot Agent Mode went generally available across Word, Excel, and PowerPoint. The line that nobody is quoting yet: engagement on Excel grew 67 percent, retention sat at 50 percent, satisfaction at 65 percent. Half of users churn out before retention sticks. Half. On Microsoft’s own scoreboard. With Copilot Agent Mode priced at $30 per user per month, and the rest of the Microsoft 365 ecosystem already paid for. The retention number is in the headline of the announcement, and it is 50 percent.

If half of users walk away from a tool bundled into the software they already pay for, “AI is replacing engineers” is not the right framing. The right framing is “AI is being tried, partially adopted, and partially abandoned, simultaneously, in the same org.”

Number three: NetSuite.

Also Tuesday, NetSuite announced SuiteCloud Agent Skills and became the first ERP platform to adopt the agentskills.io open standard. Brian Chess, their head of AI, named the actual problem: customers want to “move from lengthy, error-prone coding cycles to AI-assisted development that is fast, secure, and consistent.” Read that again. AI-assisted. Not AI-only. The reason NetSuite shipped a knowledge package with 684 permission codes and 60-plus interface components is that general-purpose coding agents do not know any specific platform, and someone has to teach them. Someone human.

The reframe

The cleaner question for any executive looking at this is not “will AI replace my engineers.” The cleaner question is “what percentage of my engineering budget should be variable spend on agents, and how do I tell whether the agents are actually getting used.”

Cognition raised at $25 billion on the autonomy story. IBM rolled out a tool to 80,000 humans on the augmentation story. Microsoft showed 50 percent retention on its own scoreboard. AWS made Codex procurable on Bedrock the same week, with what one analyst called “IAM, audit, and procurement attached,” because the actual blocker for enterprise adoption is not capability. It is the procurement, audit, and identity story around the human who triggers the agent.

The replacement narrative is doing more damage to engineering org morale this quarter than any actual layoff. And the data does not support it.

What the data supports is a slower, less photogenic story: tools getting better, humans staying in the loop, half the seats getting unused, and the orgs that quietly measure adoption are the ones that figure out what their next hire actually looks like.

So what

If an exec is reading the Cognition headlines and wondering whether to freeze the 2027 hiring plan, three concrete moves before the next leadership meeting.

First, ask whoever owns the harness budget for the active-user count, not the seat count. If retention is closer to Microsoft’s 50 percent than IBM’s 80,000-strong fleet, the company is paying for shelfware, and the engineers who silently dropped the tool will explain exactly why if anyone bothers to ask them.

Second, ask the loudest “we are replacing engineers with agents” board member to name the customer. Not the model. The customer. The deployments that are working at scale this week have names: IBM, NetSuite’s customer base, the Goldman and Citi and Dell list. They are augmentation deployments with humans inside, and most of those humans are the same ones who were there a year ago.

Third, write down what an engineer plus an agent stack would actually do, versus what an agent alone would do. Cognition’s pitch is the second number. IBM’s deployment is the first. The truth in most engineering orgs is going to look more like the first one for at least the next twelve months, and the budget should reflect that.

The replacement story is the loud story. The 80,000 IBM humans are the quiet one. Quiet stories tend to be the ones that turn out to be true.