hansonkd

2,000 gold bars were stopped out of iraq. and that is just what was stopped / reported.

Dictators and autocrats may or nay not have cash sitting in a bank account, but there are most likely multiple with $1B in gold.

Not to be pedantic and I agree with what you are saying but:

> As a rule of thumb, if you look at something for 3 minutes and have some obvious questions, the scientists that looked at it for several years of their life in great detail might have had those same obvious questions as well

This does not mean that just because they had those obvious questions that they were properly resolved. Human history has a long track record of people who knew better but chose to ignore. In science there is an incredible pressure to have positive results rather than negative ones (IE nobody would care or know about this study if the title was "we looked and iphone doesn't explain 33-52% of fertility decline"

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We combine fintech, legal infrastructure, and thoughtful product design to turn what used to be months of paperwork and six-figure legal bills into a streamlined, guided platform. Our customers are venture-backed founders preparing for exits when the stakes are high and precision matters.

We’re early, fast-moving, and product-obsessed. This is a chance to help define the system of record for founder wealth.

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email: kyle@getdynasty.com

Contact: kyle@getdynasty.com

In general once or twice a month cleaners aren't hired to "tidy up", they deep clean.

a bit like the difference of brushing your teeth and going to a hygienist.

They almost certainly are, even if unknowingly, because HN and all blogs get piped continuously into all models' training corpus.

After the steep increase in sales of Mac Studios specifically for LLMs, I'm waiting for Apple to release a frontier level model, optimized for highest end of apple hardware (probably would be hardware locked by a certain neural processor needed (which would then lock the memory config).

The built in Apple Intelligence right now is very small, but even just having a small LLM you know is always there, online, fast and ready makes you think about building app differently. I would love the context to expand from the meager ~4K tokens.

bigger filter = less noise to move more air

Its actually simpler since the skill can be 100% a MD file.

idk, just have a standard internet request tool that skills can describe endpoints to. like you could mock `curl` even for the same CLI feel

I've been thinking a lot about this lately. It seems like what is missing with most coding agents is a central source of truth. Before the truth of what the company was building and alignment was distributed, people had context about what they did and what others did and are doing.

Now the coding agent starts fresh each time and its up to you to understand what you asked it and provide the feedback loop.

Instead of chat -> code, I think chat -> spec and then spec -> code is much more the future.

the spec -> code phase should be independent from any human. If the spec is unclear, ask the human to clarify the spec, then use the spec to generate the code.

What happens today is that something is unclear and there is a loop where the agent starts to uncover some broader understanding, but then it is lost the next chat. And then the Human also doesn't learn why their request was unclear. "Memories" and Agents files are all ducktape to this problem.

You know, that would actually be pretty fun and cool. Like if you had home automation set up with a "pet assistant", but it would only follow your commands if you made sure to keep it happy.

I mean emails were and still are a huge security risk. Sometimes I'm more scared of employees opening and engaging with emails than I am than anything else.

Apple is terrible for business. Every portal and product require a new apple id. apple store and apple business can't be same apple id. your device id can't be the same as either. Its madness. Last count i have 4 apple ids that I have to shuffle around.

Any of these abstractions are just temporary.

Floats break the basic expectation of == for round-trip verification, not due to programmer error, but because NaN is non-reflexive by spec. A bit-perfect round-trip can reproduce the exact bit pattern and still fail an equality check. The problem is intrinsic to the type, not the operator.

I love to build a plan, then cycle to another frontier model to iterate on it.

skills obviously are a temporary thing. same with teams. the models will just train on all published skills and ai teams are more or less context engineering. all of it can be replaced by a better model

GetDynasty.com | San Fransisco, CA | Sales (In-Person SF only) | Engineering (In-Person or US Remote initially OK)

Dynasty helps startup founders legally eliminate millions in capital gains taxes through QSBS trust planning. Today, sophisticated tax strategies are locked behind elite law firms and opaque processes. We’re building the software layer that makes advanced trust and tax infrastructure accessible, understandable, and fast.

We combine fintech, legal infrastructure, and thoughtful product design to turn what used to be months of paperwork and six-figure legal bills into a streamlined, guided platform. Our customers are venture-backed founders preparing for exits when the stakes are high and precision matters.

We’re early, fast-moving, and product-obsessed. This is a chance to help define the system of record for founder wealth.

Positions:

* Engineering: Hiring an experienced python / react engineer to help build the next generation of financial platforms. -> kyle@getdynasty.com

* Sales: We need to hire our second sales rep ASAP -> alessandro@getdynasty.com

If you want to work in SF, and want to join an extremely ambitious and fast growing startup, please reach out

Agents will dominate the internet and open source code in a few years.

I like the idea of we will always need Pilots.

We have autopilot and i'm sure if we tried could automate take off and landing of commercial flights.

But we will keep pilots on planes long after they are needed.

A lot of people running OpenClaw just have it generated and burning tokens for no reason. They just know more tokens = doing stuff so want to spend as many tokens as possible.

I've only seen it in job postings and linkedin posts from SF founders.

I've been saying this for the past 2 years. Even think about the stereotypical "996" work schedule that is all the rave in SF and AI founder communities.

It just takes thinking about it for 5 seconds to see the contradiction. If AI was so good at reducing work, why is it every company engaging with AI has their workload increase.

20 years ago SV was stereotyped for "lazy" or fun loving engineers who barely worked but cashed huge pay checks. Now I would say the stereotype is overworked engineers who on the midlevel are making less than 20 back.

I see it across other disciplines too. Everyone I know from sales, to lawyers, etc if they engage with AI its like they get stuck in a loop where the original task is easier but now it revealed 10 more smaller tasks that fill up their time even more so than before AI.

Thats not to say productivity gains with AI aren't found. It just seems like the gains get people into a flywheel of increasing work.

Dynasty | https://www.getdynasty.com | San Francisco, CA (in-person) | Full-Time

Building the next generation of trust & estate planning software

Dynasty is building a modern trust platform for startup founders and families, with a focus on QSBS trust stacking so founders can multiply the Section 1202 capital gains exclusion across beneficiaries. We make it possible to set up, fund, and maintain QSBS eligible trusts with ongoing compliance through a vertically integrated model that includes trust administration

We are based in San Francisco and work together in person.

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- Sales

You will work directly with prospective customers, many of whom are founders, operators, and high net worth families. You will guide them through understanding our solutions, manage pipeline, and close new business. This role is ideal for someone who is consultative, comfortable discussing financial concepts, and excited to help people make important long term decisions.

- Onboarding

You will help new customers successfully set up their trusts through our platform. This includes collecting information, coordinating next steps, answering questions, and ensuring a smooth transition from signup to completed structure. This role is great for someone detail oriented who enjoys guiding people through complex processes with clarity and care.

What We Look For

    * Strong communication skills
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To appy: email your resume to kyle <at> getdynasty <dot> com

On some levels its insane that billion dollar companies are pouring resources into something and the name was only relevant for like a couple hours before things moved. Fast paced world.

Singularity of AI project names, projects change their names so fast we have no idea what they are called anymore. Soon, openclaw will change its name faster than humans can respond and only other AI will be able to talk about it.

Somethings get packaged up and distributed in just the right way to go viral

There was always going to be a first DAO on the blockchain that was hacked and there will always be a first mass network of AI hacking via prompt injection. Just a natural consequence of how things are. If you have thousands of reactive programs stochastically responding to the same stream of public input stream - its going to get exploited somehow

Does that affect the autogenerated migrations at all? Teh only time I ran into that issue as if I generated a table, created a data migration and then it failed because the table was created same transaction. Never had a problem with autogenerated migrations.

They don't need to work in every case. For the past `~15 years 100% of the autogenerated migrations to generating tables, columns or column names I have made just work. and i have made thousands of migrations at this point.

The only thing to manually migrate are data migrations from one schema to the other.