The Year Behind Tech Trenches
Look at what a company promised, see what happened, and then figure out what caused the difference. That’s the approach Tech Trenches found over fifty-eight essays. Now that it turns one year old on August 10, I’m giving it the same treatment.
By my own archive count: fifty-eight essays in 359 days, about 93,400 words. My dashboard says the correction post on backing the wrong company drew 3,559 views and 10 subscribers. The largest teardown got 140,433 and 789. I did not read either number as an incentive structure. This publication spent the year reading incentive structures.
The subject was the first wrong call
My second post started with “Hey tech leaders!” and ended by offering to send a template if you replied with the word template. That’s classic growth newsletter style, and I wrote four more in that vein. The first six essays covered topics like 1:1s, hiring trials, 90-day onboarding, and why we don’t allow process exceptions. None of them included any external links.
Five of those six sit at the bottom of my own all-time table. The publication was built for engineering leadership, but the readers who stayed came for a teardown with numbers. Week six produced the biggest post of the year. Nothing since has matched it. The audience settled on one format, and I never went looking for it. I spent the next three months publishing eight essays and called it a plan.
The wrong company, named
In October 2025 I split AI into the kind built to be used and the kind built to be consumed. I put Anthropic on the useful side, naming them as proof that a responsible AI company could succeed. I recommended them to clients and defended them in online discussions.
In April I published the correction. It closed on this. I had got both directions wrong: the company I criticized course-corrected, the company I defended accelerated.
The correction ended with a prediction: at Anthropic’s growth rate, the distinction between moral and business positions would collapse. Six weeks later I had the receipt: the last binding commitment had already been deleted in February, before I published the correction. The company was valued at $380 billion that month, and I cannot show the two are connected. I had spent months telling engineers that commitment was the reason to pick this vendor.
Right direction, wrong by half
September 2025: $364 billion in annual AI capex, and my read was that it was hope with a procurement budget.
February 2026: Amazon alone projected $200 billion in capex for the year. That was $44 billion above Wall Street expectations, and the stock dropped 6% in a session. Amazon filed with the SEC the next day, warning it might need to raise equity and debt to fund the buildout.
I expected a revision to that industry figure. It nearly doubled.
The window I was standing at
For most of the year I called the replacement story a lie. I still do. What I missed was where the damage was landing.
That read came from where I was sitting. No one on my team was laid off. I was hiring the whole time, and our last round attracted 2,253 applicants for just a few spots. When you’re in a position that so many people want, saying “they will land somewhere” isn’t optimism. It’s just what you see happening every day.
An engineer with about a hundred days of runway answered one of my posts and walked me to the other window in an afternoon. The correction did not start with research. It came from that engineer. He was living in the part of the market my data could not see, and my data was real. It was a solid sample of the people applying to me. Now I have 2 open positions, and the market is broken even more than before, ~ 70% of applicants do not even read the job description and apply for a full-stack vacancy as a Frontend Engineer in the CV title, but it is a different story.
Same verdict, different cause
In September 2025 I called it a software quality collapse and built the case out of static metrics and a calculator app leaking 32GB of RAM. I blamed AI writing worse code.
By June the same collapse turned up in production telemetry, and I traced part of it to an incentive structure that counts tokens in performance reviews and moves the people who catch defects onto other work.
Nine months, and it took another company’s breach notification to surface that incentive reading. I still mark it as something I cannot prove. Software quality is now degrading at a pace I could not have imagined a year ago.
What the misses have in common
Most of these calls started from a position. I wanted responsible AI, so I named a company. I treated $364 billion as a ceiling. I called the replacement story propaganda and stopped there.
Each one got corrected later by something that turned up: a deleted policy, an SEC filing, one reader’s account.
The replacement call breaks the pattern. I had a document: 2,253 applications. It pointed the wrong way, because it described everyone walking toward my chair, not away from someone else’s. A real sample of the wrong population is more dangerous than no sample, because it brings confidence. I still think the layoff wave is a huge mistake that will hit us in the near future, but no one sees the dude who stays on the ground when you are somewhere in the sky.
What the structure was paying for
These are my own Substack numbers. You cannot check them. Hacker News is the number I have quoted to people all year. It sent 28,285 unique visitors, 10.23% of all traffic, second only to direct. It produced 102 subscribers.
Substack’s own network sent 12,153 visitors, well under half of that, and produced 994 subscribers, 562 of them from Notes. Per visitor arriving, that works out to about twenty-three times the conversion of the orange site. Reddit sent 8,683 and does not appear anywhere in the top seven subscriber sources. Google sent 4,785 and produced 50, which works out to roughly three times the per-visitor conversion of the channel I keep quoting. Direct and Direct to App together are 63.3%. Just under two thirds of my traffic arrives with no attribution, so I cannot see most of my own distribution.
The traffic engine and the subscription engine are two different machines. The one I could recite from memory was the wrong one. I spent the year doing this to other companies. I did not do it to myself until a birthday made me open the page.
Who pays
When a company here gets a call wrong, the cost lands on somebody who acted on it.
Somebody picked a vendor because I vouched for a commitment that was already deleted. Somebody read a year of confident writing about a market that still worked, from a man whose entire view of it was two thousand incoming applications. Neither of those people has a way to send me the bill. That is the same gap I have described in every piece about a lab, a platform or a regulator. I cannot promise that I will not make mistakes in the future; what I can promise is that I will say out loud that I was wrong.
The bookend
Post one, 10 August 2025, opens on two developers telling me something the dashboard would not: velocity steady, deployment frequency fine, sprint goals met, every number suggesting everything was fine. Post 58, 4 August 2026, opens on Hugging Face spending four days reconstructing a breach of its own production systems while the frontier models it pays for refused most of the forensic work, because a guardrail cannot tell reverse-engineering an exploit from launching one.
Same essay. Bigger machine.
What next
I do not know.
Substack turned out to be the same kind of broken system I write about. In 2023 it promised a feed built to reward quality over shallow engagement and dopamine hacks. Then it wrote the cadence instructions itself, and when the volume showed up it licensed a scanner and pointed it at the results. I took that apart two weeks ago. Two weeks later most of my appetite for writing here is gone. What killed it reads to me as hypocrisy.
Large changes are coming in my life over the next few months and the details are not going in this piece. I am not sure I will have the hours or the head to keep this rate. There is a stack of drafts that will ship. What happens after them is open. It might change nothing. It might stop.
I also started a book. Writing that sentence still feels absurd. There is an introduction and one chapter, I do not know whether it gets finished or published, and nobody should wait for it.
The part worth reporting is the measurement. An article takes me about a week. Three weeks passed between the introduction and chapter one. Same material, same method, and the form is much harder than I expected.
The uncomfortable truth
This blog exists because the man writing it is the same kind of broken system as the ones he writes about.
I am naive enough to believe you answer for your words and your actions. So when I watch a bullshitter contradict himself in public and pay nothing for it, I need it written down somewhere, on the record, in one place. That is the impulse sitting under the method. The research came later.
There is no reputation institution left. Nothing checks whether a man’s word survives contact with what he does next. So watching your words stopped being a requirement. I have made that argument here before at more length than it needs.
It’s just a guy shouting online about how unfair things are. That sounds a bit pathetic, and I won’t argue with that. This blog is my personal stand-in for an institution that’s gone, written by someone who made five public mistakes in his first year. All it does is put my words and actions side by side, with dates attached.
That is the whole of it.
Strange year. Thanks for reading, from the trenches.