@FinanceYF5: 1/ There's a new tax on AI engineering. According to BVP's latest survey, 90% of tech/engineering teams have already integrated AI into their core workflows; code generation 92%, code review augmentation 79%, Agentic development 60%. The real differentiator is not whether you use AI, but whether you can still maintain quality and understanding after accelerating.

1/ 🧭 New Tax on AI Engineering

In BVP’s latest survey, 90% of tech/engineering teams have integrated AI into core workflows; code generation 92%, code review enhancement 79%, Agentic development 60%.

What truly widens the gap isn’t whether you use AI, but whether you can maintain quality and understanding after speeding up. 👇 https://t.co/TX0Hutvfs6

2/ Speed Needs Layers

Ramp ships major features daily, but instead of having leadership chase every detail, they split releases into two layers.

Anything goes into early access immediately—10% of customers, 5000+ companies in the test group; before GA, evidence is required: a 3-minute demo, KPIs, customer feedback, support readiness, and a launch plan.

3/ Governance Doesn’t Equal Uniformity

Shopify didn’t mandate a single AI tool—it unified the infrastructure underneath the tools.

Requests from Claude Code, Copilot, Cursor, Codex, etc., first go through an internal LLM proxy; the company gets cost control, team usage visibility, and model switching capability, while engineers keep their own workflows.

4/ Agents Reshape Leadership

Engineers are shifting from “writing code themselves” to “orchestrating multiple AI agents simultaneously.”

Senior engineers at Shopify already run agents in parallel, review results, discard bad ones, and merge good ones; leaders now manage not just people, but code-writing systems and their new failure modes.

5/ Organizational Inflection Points

Jessica Popp gives a very practical breakdown: 0–10 people must be able to ship hands-on; 10–20 start adding management layer and technical structure; 20–50 need to diagnose whether the problem is in “people,” product, or architecture.

Many founders realize too late that early small decisions have already become team culture.

6/ Biggest Risk Is Understanding Debt

AI makes code faster, but it can also make engineers increasingly unfamiliar with the systems they deliver.

BVP calls this understanding debt: you can ship fast, but can’t explain why something breaks, nor reason about system behavior without AI; rollback rate may not reveal it, but weekly demo will.

7/ Only Give the Grind to AI

Farhan Thawar: Abdicate the toil, never abdicate the thinking.

AI can write boilerplate, research, and run parallel explorations; but engineers must at least understand 2–3 layers down the system. Speed expires—understanding is the asset when incidents happen.

Read the original:

That’s all.

If you like this topic:

1. Follow me (@FinanceYF5)
2. Like + retweet the first post below