People go into Big Tech for all sorts of reasons. Big projects. Big tasks. Big tools. A big ego. A big algorithmic past. In short — everything has to be big. Big. Big Tech. Only one thing stayed big But it just so happens that in recent years the only things that stayed big are the layoffs. The instability. The chaos. The politics. You go on vacation — and your project gets rewritten. You miss a meeting — and the platform gets migrated onto a different platform. ...
The morning starts with going through the logs — the errors that piled up overnight. Nothing complicated. You read the errors, you go into the code, you see why a wrong parameter came in here, and over there why a parameter is missing instead. You commit. Note to self: check again in a couple of hours. At the meeting you describe what you spent your time on — and the response is an idea. Maybe you need a skill? Look: Claude Code will do all of this for you, and you just review the merge requests. We schedule the skill with cron and that’s it. ...
A bug comes in from users. Your program crashes with an error at some indeterminate moment, for unclear reasons. (Are there ever any other kind?) It’s serious. Lots of users complaining. It’s urgent — every engineer drops what they’re doing and piles onto the task. What’s the CPU doing? Which processes are running? Are there logs? Are there repro steps? What about the dump? Etc. The war room Only they’re not exchanging files anymore. They’re exchanging prompts. ...
A task’s status updates itself, automatically, from the pull request. Sprints have been replaced by an optional weekly call. There’s no sprint planning either — you have an LLM generate a one-page design doc for the feature, and that’s the whole ceremony. Agents work the codebase autonomously. They write the tests. They review the code. They open small pull requests and merge them. Programmers are involved only in the big architectural decisions, the designs, and in giving feedback to the agents. ...
Agentic, agentic, a-d-gentic. (In Russian, ад means hell. Keep that in mind as we go.) Ctrl-b, right We added verification. Our agent spins in a feral loop, checking itself against a thousand linters. The strictest checks are running — checks you don’t even know exist — something like LintLikeAGodIsLookingAtYouStrictly. It is, as far as I can tell, very thorough. I have not read a single line of its output. ...
I remember when we used to repeat the mantra to each other — and from conference stages — that there is no silver bullet. It was practically a professional creed. And then AI showed up, and it turned out that wherever you add it, everything gets better. For managers. For products. For designers. For SaaS companies. Add AI to anything and it simply becomes better. Better how? Better in what way, exactly? And the way things worked before — why doesn’t that work anymore? Those are details. Digging into them feels almost impolite. So, anyway — the silver bullet is AI. ...
If an engineer at Big Tech can simply be fired, managers get hurt differently. They get converted into an IC — an Individual Contributor. On paper it’s a kind of tech lead: someone who both writes code and helps others write it. Except they code… so-so. The industry moved on without them During their years away from the keyboard, the industry changed so much that even the tools and the terms they used to rely on are gone. The ground they once stood on has been repaved twice. ...
Continuing the tokenmaxxing theme. Google says 75% of its code is written with AI. Meta says 90%. Uber burned a whole year’s worth of tokens in the first four months of the year. Programmers tokenmaxx. Managers token-flex — about how much their team spends on tokens per month, as if the API invoice were a performance review. Everything’s better with AI Need a status report? AI bot. Monitoring? AI bot. Code review? AI bot. Dashboard? AI bot. Every action a programmer takes, every automation, every cron job that used to be twelve lines of bash — must now go through an AI. Because everything’s better with AI. Obviously. ...
We used to count lines of code, then we’re counting commits, then tasks closed. And now it’s tokens. And if there’s a metric, there’s a way to inflate it. That’s how tokenmaxxing was born. Tokenmaxxing is when a developer maximizes the number of tokens they burn in order to climb the leaderboard. The manager’s leaderboard. The company dashboard, where you light up as “AI activist of the month.” Whatever scoreboard someone decided to wire up to the API bill and mistake for productivity. ...
You can listen the full episode of the podacst here: https://javaswag.github.io/episode/78/ Interviewer: Welcome to this special interview, drawing on insights from the recent Java Swag podcast with Filipp, an architect at lektone.op. Filipp, thank you for joining us. Filipp: Glad to be here. Interviewer: You’ve had a long and varied career in programming. Could you start by telling us about your journey into Java and how you began writing industrial systems? ...