Is AI actually replacing software engineers or just changing their work?

According to the post, AI is not replacing software engineers but is instead taking over the repetitive "grunt work" of coding so that engineers can focus on higher-level, high-value engineering problems. The post cites discussions on YC's Hacker News where engineers report that AI is replacing the parts of their jobs they never liked, which shifts their attention toward more strategic and complex work.

How much of new code is currently AI-generated according to this post?

The post states that, according to Microsoft and Google, over 30% of new code is now AI-generated, which is an increase from about 25% just a few months earlier. This statistic is used to illustrate how quickly AI-assisted coding is being adopted in software engineering workflows.

What should sales engineers change in their approach when selling to engineering teams using AI?

The post advises sales engineers to shift their narrative from offering more tools to reducing decision load, positioning their solution as an accelerator for high-leverage engineering work rather than just an automation layer. Sales engineers are encouraged to understand where AI still struggles, such as debugging, system integration, and edge cases, and to use those friction points as anchors in conversations while demonstrating precise, well-researched understanding of the buyer’s context.

Where does AI still fall short for software engineers according to this post?

The post explains that AI performs well at generating boilerplate code and speeding up prototyping but often falls short in debugging, system integration, and handling edge cases. These shortcomings are described as areas where engineering pain accumulates and where sales engineers can anchor value when discussing solutions with technical buyers.

What does the post mean by saying solutions engineering is becoming context engineering?

The post describes solutions engineering as context engineering because AI is increasingly handling the "what" of code generation, while engineers and sales engineers must focus on the "why" and the broader context. In this framing, the primary responsibility of a sales engineer is to connect a solution to the buyer’s evolving workflows and strategic priorities, building trust by deeply understanding daily engineering work and uncovering real technical pain points.

Is AI Replacing Your Software Engineering Customers?

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This post explains how increasing AI-generated code, now over 30% according to Microsoft and Google, is changing the role of software engineers and how sales and solutions engineers should adapt. Software engineers are using AI to handle repetitive coding tasks so they can focus on higher-level, high-leverage engineering work rather than being replaced. The post argues that sales engineers need to shift their narrative toward reducing decision load, understand where AI still falls short in areas like debugging and integration, and respect technical buyers’ time with precise, well-researched conversations. The post reframes solutions engineering as context engineering, where the key value is aligning a solution with the evolving workflows and strategic priorities of engineering buyers.

AI is writing code, and it's getting much better. But what is it doing to the roles of software engineers? According to Microsoft and Google, over 30% of new code is now AI-generated, up from just 25% a few months ago.

The engineering world is shifting rapidly. But here's what most people miss:

If you're selling to engineers, you need to understand how their jobs are changing.

Engineers Aren't Being Replaced. They Are Being Freed Up for Higher-Level Engineering Work

Long acknowledged being the realest source of what's happening with software engineers, YC's Hacker News recently posed the question: Is AI replacing engineers? The thread reveals a key pattern:

Engineers aren't worried about being replaced.
They are rethinking what's worth their time.
And they're relying more on AI for "grunt work" so they can focus on solving high-value problems.

One engineer put it best:

AI isn't replacing me. It's replacing the parts of my job I never liked.

That means your technical buyer is no longer optimizing for efficiency. They're optimizing for strategic leverage.

What Sales Engineers Need to Know

If you're selling to engineering personas, here's what AI adoption could mean for your strategy:

Shift your narrative: Engineers aren't looking for more tools—they're looking for fewer decisions. Position your solution as an accelerator of their high-leverage work, not just an automation layer.
Understand where AI still falls short: AI excels at generating boilerplate code and speeding up prototyping, but it often struggles with debugging, system integration, and handling edge cases. These are the exact areas where engineering pain tends to accumulate. Depending on the buyer's AI maturity—what tools they use, how well their LLMs are fine-tuned, or whether they've successfully implemented modular component platforms—these unresolved friction points become critical value anchors in your sales conversation.
Respect their time differently: Technical buyers may be more skeptical of generalized pitches given how the first wave of "vibe coding" fell flat. They expect precision, and they really expect you to have done your homework.

Solutions Engineering = Context Engineering

AI is taking over the "what." Engineers are now focused on the "why." As a sales engineer, this is your moment to shine, by framing your solution not just in technical specs, but in terms of strategic alignment with their evolving role.

The more you understand how your buyer's daily workflow is evolving, the more trust you build—and the faster you uncover real technical pain your product can solve for.

Your Turn

If you're selling to engineers, how has AI changed your technical discovery? Are you seeing new objections, or new urgency?