A short read on the topic's time range, peak episode, and strongest associations. Use it as the quick orientation before drilling into examples.
downside risk appears in 36 chunks across 32 episodes, from 2023-10-02 to 2025-10-20.
Its densest episode is Bits and Bobs 4/22/24 (2024-04-22), with 2 observations on this topic.
Semantically it travels with prompt injection attack, broken glass, and perfectly bespoke, while by chunk count it sits between coordination cost and Openclaw; its yearly rank moved from #20 in 2023 to #53 in 2025.
Over time
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Raw mentions over time. Use this to see absolute attention, not relative rank among all topics.
Range2023-10-02 to 2025-10-20Mean1.1 per episodePeak2 on 2024-04-22
Observations
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The primary evidence view for this topic. Sort it chronologically when you want concrete examples behind the larger pattern.
Showing 36 observations sorted from latest to earliest.
...g software.
The benefit of this ability accrues to the entities that have lower downside risk.
The asymmetry is now much stronger than before.
That means startups as a class have an advantage.[jb]
Many startups that use it will blow themselves...
...e cool features can never be possible.
Why would you ever pick the second team?
Downside risk will be discovered the hard way, since the teams that know why it's there will be considered party poopers, and the naive teams will seem more chill.
Constantly worrying about downside risk is like distracting eddy currents.
The eddy currents make you much less efficient, making it impossible to have the smoothness of laminar flow.
How t...
...ng offensive.
Self-distributing code is different because it can do things.
The downside risk is orders of magnitude higher.
TikTok, like all engagement-maxing hyper-scale services, optimizes for the revealed preferences of what we want, not w...
...en more as a liability.
Origins should prefer not to have the data with all the downside risk of having sensitive data.
There should be ways for creators of code to write arbitrary code that runs blindly.
This would allow them to do useful thi...
...CRUD workflows.
Because they are forced by their employers to, and there's more downside risk.
Consumers have lower standards for quality, and also lower pain tolerance.
...allowed the integrations in the Max subscription.
When you're worried about the downside risk of a feature and want to experiment to see how bad it is in the wild, a classic technique is to roll it out to a very small audience and watch carefu...
...it to coordinate across network boundaries with less-trusted collaborators.
The downside risk is proportional to the multiplication of:
1) The breadth of sources in your context.
2) The power of the tools you've plugged in.
The larger the amou...
A pattern to dull the downside risk of agents: have them only write "drafts".
The drafts still need to be activated by a human before executing the action in the real world.
This provid...
...m.
Even if 99% of people in the ecosystem aren't savvy enough to understand the downside risk, it doesn't matter–the system will limit itself naturally to avoid that worst case downside risk.
Technically the expected value of the worst case do...
Filters are better than agents[agw][agx].
Agents take actions on your behalf.
They might take the wrong action, causing difficult-to-reverse downside.
Dangerous!
Filters[agy] help sort information and make recommendations.
The end user decides whether to act or not.
Having the user in the loop provi
...tions on your behalf.
That's a high bar to meet if there's even a little bit of downside risk... and if they're flexible and open-ended there's always downside risk!
Another approach is not an over-the-top of existing software, but new softwar...
...t would take to document a seedling, you can plant 10 seedlings.
As long as the downside risk of the seedling is capped and small, it's just opportunity cost, and making it fully legible just kills the seedling before it even gets started.
...g?
Does it have a physical manifestation that is possible to model?
What is the downside risk if it doesn't work?
This technique works in physical systems where interactions can be precisely modeled, but could not work in complex adaptive syst...
The downside of centralization can't be seen by the winning centralized player.
"Why does everyone dislike me? I'm doing nice things for them! I think this setup works pretty well for everyone! Everyone's lucky to have such a good guy like me holding all the power. Imagine how bad it would be if my
How can you make people think less about downsides ("what if I do it wrong") and more about the upsides ("I wonder what will happen if I do this?")
Instead of the system saying "No." how can it say "Yes!"
...entralization gets scaling benefits... but also centralizes power and increases downside risk.
A person relying on a centralized resource can be cut off from it by the controller of the resource and have no fallback.
...eract with this person again directly or indirectly?
If not, it's not worth the downside risk for no upside.
Do you think the other person will have power relevant to you in the future?
If so, then the downside risk of them not wanting to work...
Looseness is a downside when trying to have an efficient, correct, tightly steerable system.
Those situations are where you want something that is hard.
But looseness is great for resilient, adaptable systems.
Those are situations where you want something that is soft.
Looseness is antifragility; it
The Experimenter mindset: curious and willing to try out options to see what works.
Hold lightly to your current understanding, and try many safe-to-fail experiments.
A playful, open, curious mindset.
This mindset is useful when the downside is capped and the upside is uncapped.
In those cases, you