This channel will be used for different UX-Core and KeepSimple-related updates.

As of now, we're working on adding a new language (Armenian) into the UX Core. This will be done within the next ten days.

After that we'll focus on refinement of KeepSimple articles.

Since 2019 we’ve been steadily building modules and tools on keepsimple.io. But with that growth came a mountain of technical debt we never had the chance to properly address.

In mid-2025 a good friend joined as a contributor, leading one of our most exciting projects (targeted for release by year’s end). His involvement gave us the breathing room to dedicate three months to some much-needed foundation work:

1. Clearing technical debt - massive SEO and performance improvements.
2. Refining GitHub repos - added documentation, guidelines, and everything you’d expect from a solid open-source project.
3. Going open-source - frontend repos are now open; backend and infra stay closed for security reasons.

The goal is to make it easy for anyone who shares our mission to fork, contribute, and improve what we’re building.

As always, we’re looking for dedicated, quality engineers who want to lend a hand in building free, public, and genuinely epic tools - never commercial, always for the community.

P.S. Currently we have four projects in our pipeline: one related to books and literature, one related to company operations, one related to project and program management, and another related to longevity.

🌻 Build in public.

Asked Claude Opus 4.6 Extended on his opinion regarding Longevity protocol. It was interesting how he highlighted as "good" those parts that I had the biggest concern about showing.

Good read on the topic of Product Managers in the AI World.

https://www.linkedin.com/feed/update/urn:li:activity:7441718075441324032/?originTrackingId=IbHrYUjevK4gp%2F7g2V6f3g%3D%3D

Hey friends 👋
I created this channel a while ago, and now it's finally becoming what it was always meant to be - a real home for the KeepSimple community.

The plan is simple. I'll be writing about things happening around us: science, health, cognition, career stuff, and what I actually think about them.

Heres the agenda:
🧠 #Mind: cognitive biases, behavioral science, how people actually think. The stuff that makes you see the world a little differently.

💼 #Career: how to get genuinely good at what you do. Frameworks, decision-making, leadership, product thinking.

🫀 #Body: because your mind lives in a body. Food, movement, supplements, longevity.

Will be aiming not to have any AI-slops, only authentic content

One thing though, this isn't my diary - It's our community. Ask questions, share your stories.

The best thing about KeepSimple has always been the people who care about the same things we do, and now we have a place to find each other.

Really glad you're here. Let's build something good 🙌

Remind people that humans suck, and suddenly AI looks fair.

A study from the University of Exeter found something every AI sales team already knows intuitively. When you remind people that human decision-making is biased, they suddenly rate AI as more fair and impartial.

Not because anyone tested the AI. Not because it improved. Just because the comparison shifted.

They had people evaluate discrimination risk in public sector hiring. Half evaluated AI first, then humans. The other half - humans first, then AI. The order changed everything. Think about human bias first, and AI looks reasonable by comparison.

This is literally the contrast effect wearing a lab coat. Your brain doesn't evaluate things in absolute terms, it evaluates them relative to whatever it just processed. Show me something broken, and the next thing looks functional by default.

Every company selling an AI hiring tool already knows this playbook. You don't need to prove your algorithm is fair. You just need to remind the buyer that the alternative is a hiring manager who went to the same university as her favorite candidates. The framing does the work. Not the evidence.

The researchers even warned about this, that debates about AI might shift toward emphasizing human weaknesses instead of actually demonstrating that the AI system works fairly. Which, if you think about it, is already happening.

I'm not saying human decision-making is great. It's really not. But "at least the robot is consistent" is not the same as "the robot is fair." Consistency just means the same mistake, at scale, every single time.

#mind

One in four executives admitted in a BambooHR survey, that they hoped employees would quit when they announced return-to-office. Not as a side effect. As the goal.

Just think about it. You issue a five-day office mandate, you know a chunk of your workforce will leave voluntarily. No severance. No bad press. No layoff tracker listing your company. You just... made the building less convenient and waited.

And the data on who actually leaves is the real shit. A University of Pittsburgh study found that highly skilled employees are 77% more likely to quit after an RTO mandate than less skilled ones. So you're not losing the people you quietly wanted gone. You're losing the ones who have options. The ones good enough to walk.

Amazon, JPMorgan, Meta, Instagram — all pushing five-day mandates in 2025-2026. And only 27% of companies are actually fully in-person. The rest are performing in-person culture while their best people update their LinkedIn.

Meanwhile remote and hybrid job listings are 20% of LinkedIn but get 60% of applications. The market is screaming a preference. Companies are ignoring it because office leases are expensive and empty floors make the CFO nervous.

RTO isn't a collaboration strategy. It's a financial one wearing a culture costume.

Happy Friday 🌻

#career

University of Iowa researchers just did something nobody had done before. They measured brain activity directly — using implanted electrodes — in people before and after a 20-minute cycling session.

What they found: a single exercise session triggered a burst of high-frequency brain waves called "ripples" connecting the hippocampus to cortical regions involved in learning and memory.

Twenty minutes on a bike and your brain's memory-consolidation network lits up.

We've known for years that exercise helps cognition. But it was always behavioral data - people who exercise do better on tests. The mechanism was fuzzy. Blood flow, BDNF, hand-waving about neuroplasticity. This study skipped the proxies and looked at the neurons directly.

And there's a UCSF study from last month that found the actual mechanism for how exercise protects the brain as you age. Your liver produces a protein called GPLD1 when you exercise. It travels to the blood-brain barrier and trims off another protein that makes the barrier leaky. Less leakage, less inflammation, better cognition. They reduced TNAP in old mice and the mice performed better on memory tests. At the equivalent of 70 human years.

So you've got two studies in the same month: one showing the immediate neural effect of a single bout of exercise, another showing the long-term protective mechanism. Both traceable to specific biological pathways. This is not a yet another "exercise is good for you." but actual mechanics.

Some time ago i was riding almost every day. Nowadays, it's once or twice a week. These research papers will hopefully motivate me to move more.

#body

Researchers at the University of Tübingen tested whether LLMs have the same cognitive biases we do. Specifically the addition bias — our tendency to solve problems by adding things rather than removing them, even when subtraction would be simpler.

Turns out GPT-4 and GPT-4o don't just have this bias. They amplify it.

Think about that. We trained these systems on human text. The text carries our thinking patterns. The AI absorbed them. And in some cases, made them worse.

Now let's bring it home. You're in a product meeting. Someone says "let's add a feature to fix the retention problem." Nobody says "let's remove the three things confusing users." That's addition bias in action — it's not even a choice, it's a default. Your brain reaches for more before it considers less.

And now the tools we use to help us think... have the same default. You ask an AI to improve your report, it'll add paragraphs. You ask it to optimize a workflow, it'll suggest new steps. Subtraction isn't in its vocabulary, because it wasn't in ours when we generated the training data.

I'm not saying this makes AI useless. But there's a weird circularity here. We offload our thinking to tools that inherited our worst thinking habits. And because the output looks clean and confident, we trust it more than we'd trust our own messy reasoning.

The tool that's supposed to help you think better thinks exactly like you do. Including the parts that don't work.

#mind