for the last two years you’ve been sold the same dream on repeat:
“plug in ChatGPT / Cursor / a dozen prompts — and you’ll finally breathe.”
the punchline for a lot of people is the opposite:
“i’m doing everything right: watching webinars, saving ‘100 prompts for productivity,’ running tasks through ai… and by evening it still feels like i didn’t move anything forward.”
sound familiar?
in this piece we’re offering a different diagnosis:
often you’re not burned out. \n you’ve got context obesity.
and yeah — ai, courses, and “magic prompts” are basically tossing more firewood on the pile.
we’re the team behind AI Mindset and {context} lab. for the last two years we’ve been running labs and communities for people who build an ai stack and a personal operating system — not just “mess around with prompts.”
more than 700 people have gone through our formats already: product folks, developers, hr, consultants, founders.
from the latest lab:
and they all share the same plot: people come in “for ai tools” — and hit a wall where their brain can’t handle the context configuration they’re living in.
this article is our attempt to describe that layer honestly.
classic burnout is about depletion. \n context obesity is about overloaded working memory.
if we simplify hard: your head has a limited “context window.” only a few items fit in there at once. when those items get closed — the system chills out. when they don’t — you drag tail-ends behind you.
psychology has been pointing at a couple key effects for a while:
in a world where you have one project and one notebook, it’s manageable. but when you’ve got:
those tails start eating your ram.
classic burnout:
context obesity:
these two can overlap. but a lot of people who self-diagnose burnout are actually living in chronic context overload.
let’s call them Alex, a product manager in a big company. but feel free to swap in yourself.
you’re not burned out, you’ve got context obesity
09:10 Alex opens the laptop and, on autopilot, boots up:
somewhere in the background there’s a thought looping: “i should finish that experiment concept we came up with last week.”
10:30 on a call they discuss a new hypothesis. someone drops a link: “10 ways to use ai in analytics.” Alex opens it, scrolls, saves it to “read later.” meanwhile, a personal todo gets a new entry: “think about an ai assistant for reports.”
12:15 Alex decides to “speed up” and asks ChatGPT to draft an email to a client. the text is fine, but:
so instead of 15 minutes for an email — it’s 25 minutes of review.
14:40 sprint planning time. Alex has:
some tasks are duplicated, some contradict each other. Alex promises: “tonight i’ll consolidate everything into one system.”
18:30 Alex closes the laptop with this feeling:
“i was spinning all day, but not a single track feels finished.”
this isn’t about Alex “doing nothing.” it’s about nothing closing a loop: not the email, not the experiments, not the task system.
in interviews, our lab participants described it almost word for word:
and almost everyone showed up with: “i think i’m burned out.”
you’re not burned out, you’ve got context obesity
the industry responds to this state like this:
what happens when someone in Alex-mode walks into that content?
people said it like this in interviews:
“i used ai every day, but it felt like another layer of work. the only thing that helped was when we started discussing the architecture of context — not just touching tools.”
so yeah: “100 prompts” isn’t medicine. it’s a new set of calories for an already overloaded context.
ai tools amplify the system they land in.
if you’ve got a clean process and sane load — they really do remove routine.
if your task configuration is already chaotic — they amplify the chaos.
you’re not burned out, you’ve got context obesity
there’s a useful term here: the “hidden tax of context switching.” when you jump between tasks and apps, your brain pays a reboot cost. across different reviews, estimates say it can eat up to 20–40% of work time.
some breakdowns here:
add research on technostress — digital stress from too many tools and notifications. meta-reviews in recent years show that introducing digital tech without changing processes often increases stress and burnout risk at first, not lowers it (the review, and a popular retelling).
now let’s look at three layers of taxes in the “you + ai” bundle.
every new service means:
in our interviews, many participants spent the first weeks not solving tasks, but maintaining the tool zoo.
ai writes — you review. the responsibility for meaning is still on you:
that’s another stream clogging your working memory.
especially nasty when ai lands on top of an existing graveyard: notion, obsidian, multiple todo apps.
instead of admitting “my system can’t hold reality,” we slap one more smart layer on top.
if the foundation is rotten, no ai penthouse will save it.
you’re not burned out, you’ve got context obesity
when you say “i’m burned out,” you usually get advice like:
all of that can be fine, with one catch:
you bring the same context habits with you.
on vacation your brain keeps looping:
a job change swaps the set of tasks — but doesn’t change how you:
a new notion workspace without new logic turns into the same landfill in a month.
this isn’t willpower. \n this is missing an explicit system prompt for yourself.
large language models have a system prompt — a text that defines:
you’re not burned out, you’ve got context obesity
most people don’t have that explicit layer. every morning we boot life in a mode like:
“take everything that lands,”
“don’t say no to tasks,”
“reply immediately so you don’t feel guilty.”
\ at one lecture on context, a participant said:
“when i realized my head has a context window too, i stopped shoving everything in there.”
that’s basically the first sketch of a personal system prompt:
spoiler: you don’t need to “burn it all down and go back to a paper notebook.”
you’re not burned out, you’ve got context obesity
you need to rebuild your context configuration honestly.
in our labs, three mandatory layers show up almost every time.
as long as your head is the only database, you’re doomed.
exercise: “15 unfinished loops”
people usually freak out at the volume. one participant said after doing it:
“i realized i’m not burned out — i’ve got a whole jira board open in my head.”
the simple fact these things moved from brain to text already brings relief.
after the offload, you don’t need to “optimize everything.” you need to format the chaos.
frameworks help here — not as religion, as a grid:
micro-format: burn / delegate / keep
once a week:
often at this step the list shrinks 2–3x — and the guilt shrinks with it.
the last layer is turning all of this into explicit rules.
exercise: three rules for my brain-llm
imagine your brain is an llm and you can write its system prompt. answer in writing:
what three rules do i put into my system prompt for 2026?
it might look like this:
then:
for many lab participants this step alone changes their week configuration — without adding a single new service.
you’re not burned out, you’ve got context obesity
context lab was born from a painfully grounded question:
why do smart, motivated people with “good systems” in notion and obsidian still feel like Alex from this article?
we started gathering small groups and testing a hypothesis: if you give people language for context, offloading practices, and basic frameworks — does their “i’m not getting anything done” feeling change?
interviews show that this exact layer — understanding context and working with it regularly — is what people most often name as their main “click.”
context lab is a place where you don’t get another set of “secret prompts.” you build your context stack and your system prompt — and only then hang ai assistants and automations onto it.
second article in the series:
the productivity museum: why notion, ai, and task courses only make it harder to live
and in the third we’ll share a personal story of someone who drowned in obsidian, crawled out through their own system prompt, and along the way helped invent the context lab formats.
Ray Svitla \n stay evolving 🐌


