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ochronus

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Head of engineering https://leadership.garden/ https://the.managers.guide/

hi@ochronus.com

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leadership.garden 2y ago

Your Brain Needs a Break from Work

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leadership.garden 2y ago

How to Build a High Performing Team

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leadership.garden 2y ago

How to Get Your Work Recognized

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leadership.garden 2y ago

3 Layers to Unlocking Team Trust: A Leader's Guide

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leadership.garden 2y ago

Leadership Styles Every Manager Needs to Know

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leadership.garden 2y ago

Productivity Techniques that won't burn you out

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leadership.garden 2y ago

Productivity Techniques Which Won't Burn You Out

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leadership.garden 2y ago

How to Have More Effective Performance Review Talks: 6 Expert Techniques

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leadership.garden 2y ago

The Office Odyssey: Return, Resist or Remodel?

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leadership.garden 3y ago

Zoom fatigue unpacked

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133pts159
leadership.garden 3y ago

Great Leaders Make People Feel Safe

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leadership.garden 3y ago

Demystifying burnout – A deep dive into its symptoms and remedies

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104pts91
leadership.garden 3y ago

Leadership Lessons from the Fields: Advice from Farmers

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leadership.garden 3y ago

How to Start Managing People – The First 3 One-on-Ones

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leadership.garden 3y ago

The First 3 One-on-Ones

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leadership.garden 4y ago

The Most Important Characteristics of High-Performance Teams

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leadership.garden 4y ago

Quantifying Burnout

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leadership.garden 4y ago

The Guide to Onboarding Software Engineers

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leadership.garden 4y ago

Your guide to Onboarding Software Engineers

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leadership.garden 4y ago

Communication skills for successful software engineers

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leadership.garden 4y ago

Product Development Fallacies

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leadership.garden 4y ago

Kindness Is a Hidden Software Engineering Superpower

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leadership.garden 4y ago

Harmful Biases in Performance Reviews

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leadership.garden 4y ago

How to approach and prioritize technical debt

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leadership.garden 4y ago

How to talk about technical debt with non-technical folks

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leadership.garden 4y ago

Building High-Performance Teams

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leadership.garden 4y ago

Characteristics of High-Performance Teams – And How To Build Them

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leadership.garden 4y ago

Key Ways We Fail as Engineering Managers

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leadership.garden 4y ago

Use Active Listening to Boost Your Career

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leadership.garden 4y ago

Common Mistakes of New Engineering Managers

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I don't think they are clueless, but rather, struggling. Being an AI provider is a money burner, and they probably don't have enough fuel for the fire anymore, so they are trying things to squeeze more $$$ and limit usage at the same time.

Yes, it's related to the limits of the subscription plans. 2ish months ago the same sub started hitting limits earlier and earlier on very similar tasks/codebases. Then they said, Oh, sorry, it was a caching bug, now it's fixed. It wasn't. Then a couple more bugs. Still no fix. Recently they announced "doubling the limits" (made possible by the Grok deal) - still hitting limits super fast compared to how it used to be 2+ months ago. Moreover, the models got somewhat dumber and slower, too.

Yeah, claude code is mostly unusable at this point. It's been in a constant decline for a good 1-2 months. It's more like a scam now.

This discussion feels analogous to me to the age-old "we can do it fast now, and do it right later" tradeoff discussion, except now it's about knowledge, maintainability etc.. There are stages of companies and types of products where solution quality has a bigger buffer, some are more critical. We also know that in many places, once you shipped a crappy solution in a week, you've now set an expectation, and management will expect you do repeat that forever, not getting the time to actually fix/rearchitect when needed.

We used to brush that off with the "we'll fix all of that once we've shipped", now we brush it off with "doesn't matter, AI can fix it later easily". This applies to knowledge about the code, domains and quality itself, too.

To me, this is a reasonable tradeoff to discuss, and sticking to either extreme ("AI is cancer" and "AI is the silver bullet") feels silly.

There's real risk here, and I do see a lot of seniors act like kids in the candy store. That speaks volumes to what AI really unlocks (cheap experimentation, for one!), but also warrants caution.

Based on the data (not great quality tbh...) we have, the net speedup is more realistically around 5-10% of the total time of software engineers, and we're yet to see the cost of that speedup.