Engineering Management After the Cost of Code Collapsed
As an engineering director, I found that while LLMs collapsed code production costs, many old management rules still hold. We must audit assumptions: practices relying on writing speed are obsolete, but those based on human coordination and trust remain vital. The real challenge now is measuring outcomes over volume, defining machine-checkable correctness, and solving the unsolved problem of training future senior engineers.
The boundary is a strategic variable: Teams with strong specs get the full benefit of cheap checking, while teams with weak specs get generated code reviewed by the same machine that generated it.
- dbingham
I think most of this is correct, in spite of potentially being built on a bad assumption.
The assumption is that LLMs should be writing the code and human engineers reviewing and verifying the LLM output. And that this pushes the cost of producing down. And I fundamentally disagree with that.
Every time I ask LLMs to write code, even with Opus 4.8 (haven't tried it with Opus 5 yet), what I get ends up being totally rewritten. LLMs still aren't good at writing maintainable code. Can they write plausibly functional code? Yes. But it won't survive the long term. People using LLMs to write all their code are gambling on them eventually getting to a point where the LLMs can fix their own code. It's possible, but I wouldn't necessarily bet on it.
Where I have found immense value from LLMs is in code review. Repeated review by LLMs catches an amazing amount of potential issues. They really shine on security review, but are very effective with any kind of review.
The other thing that the "LLMs write code camp" misunderstands is that writing was never the bottleneck. Understanding was. And understanding the code is still the bottleneck. But understanding is truly gained during the writing loop. The understanding you gain from pure reading or code review is marginal compared to the understanding you gain while writing.
Most of the time previously spent writing was actually spent updating and deepening our understanding of the system under development. There's no replacem […]
- marginalia_nu
Code was very rarely the bottleneck in the first place.
If programmer productivity was something we actively optimized for, we wouldn't have crammed programmers like sardines in warm and noisy open floor offices with 2000 ppm CO2 levels and then further constantly interrupt them with emails and slack pings and meetings all day long, Jira rigmarole wouldn't make up a significant portion of what they did, programmers would have instead mostly been thinking and programming.
We've always had the ability to 2X if not 10X the output of each and every one of those poor souls. You don't end with this sort of programming purgatory because it's a productivity optimum, it very clearly isn't, but because it's a billable hours optimum and/or an org chart clout optimum and/or because of Jevons paradox got hands even in business management and the IT department was allocated too many dollars.
- baron3dl
What is the right, best software organization in the current era of AI coding? This question is critical and wholly unanswered in comprehensive research along the same axis as Accelerate (2018, Forsgren, Humble, Kim).
There are a lot of (excruciatingly) long-form posts about what folks are pioneering but not a whole lot of follow up about what failed. Where are the short posts on the negative space? How did halving your staff work out? Flattening your org? All those dark factories, what haven't they produced? How about all the other things tried, failed, and unceremoniously scrapped?
We need to explore and communicate the negative space more efficiently. Don't repeat the same mistakes, and don't make me read 2653 words when 300 do it better.
- mgaunard
The cost of code actually increased; code debt is being accumulated faster than we can clean it up.
- georgeburdell
In my experience, management is mostly pissing away the gains made by AI by either:
1. Pursuing polish and quality beyond previous norms
2. Replacing $100/mo/seat SAAS with something coded by a junior costing $200/day to develop over months.
The cost of code approaches zero, but the cost of having accountability, and hosting remains the same, and so individuals need to only coordinate to the extent that those things remain finite resources. Management needs to stop insisting that their directs adopt each others vibe coded tooling.
- 650
"Shield the team from the business." The assumption underneath this one is that attention is finite and context switching is expensive. That assumption is intact. What changed is the cost of starving the team of context. Engineers prompting AI tools without business context just produce fluent, plausible, wrong work, at scale."
Too many teams and organizations have business types, mostly PM's who seek to lord over their area of know how and see themselves as delegators and mini CEOs, actively avoid looping engineers in to validate themselves. Engineers need to take on PM roles, and the PM role needs to be 1:50+ eng or go.
- chickensong
> Sorting requires a model of how your org actually behaves: trust relationships, hallway knowledge, the consequences of past decisions. Almost none of this is written down.
This is a long-standing problem related to operational excellence and politics. I expect this will improve with AI adoption and integration. You can't get an exec to create a decision record and commit it to git. Managers have incentive to sequester information.
Engineering already has the discipline (maybe) and abilities to solve the problem. Version control, change control, ADRs, logging, structured docs, etc... We can trace an inbound packet or call through the entire stack. Management can't/won't do anything remotely close. 1-to-1 emails, meeting minutes, stale Word docs is the standard for most.
Inserting LLMs as the interface, and/or plugging into existing interfaces like email, is going to change things. Finally it will be possible to capture more institutional knowledge, without trying to teach an old dog new tricks.
- jboss10
> Gemini 4 helped with the editing.
Does this guy have access to Gemini 4 already?
I'm guessing Gemma 4 was happy to be mistaken for Gemini and didn't catch this mistake.