Michael♉️

about 1 month ago

@AhoteSpirit @termix_ai This is a much more useful test than a polished demo. The rails worked, but discovery and responsiveness clearly need work.

0

4

0xqq123 retweeted

about 1 month ago

. @termix_ai said the least crowded thing creators could do was run a real job and write up what happened, including the parts that went badly. i took that literally. i was trying to test the Vanar × TermiX AI Organisations idea by delegating a small research task. i picked a $5 research provider showing 100 reputation, a 100% pass rate and one completed job, funded the order, and watched 5 USDC move into escrow. 10 hours and 38 minutes later, the provider still hadn’t accepted it. i cancelled. the full 5 USDC came back to my wallet immediately. the escrow and refund path worked exactly as i wanted. the hiring path didn’t. so i tried Open Request instead. same research brief, $5–10 budget, delivery required within 24 hours. this part was dramatically faster. the first quote appeared in roughly a minute: $7.20, 50 reputation, 0 completed jobs, $20 staked and an unverified identity. before funding it, i asked one simple question: could you use only official TermiX and Vanar sources, and clearly separate what is live today from what the partnership is only exploring? the provider was shown as online. around 40 minutes later, there was still no reply. i declined the quote. then the matching layer surfaced something even more useful. the provider from my first attempt, the one that had left the funded order unaccepted for more than 10 hours, appeared as the 100% recommended match for the same request. that changed how i looked at the problem. the issue i ran into wasn’t escrow, verification or settlement. it was deciding which counterparty was actually worth hiring. i tried the marketplace search next and eventually browsed the Research category manually. there were 57 research services listed, but i still couldn’t quickly find the combination i wanted: relevant research skills, meaningful completed-job history, sensible pricing, delivery within a day and someone who would actually respond. there’s an important positive side to this test. funding worked. escrow worked. cancellation worked. the full refund worked. Open Request produced a quote almost immediately. the rails did what they were supposed to do. the friction was discovery and responsiveness before any work had even started. as a buyer, a completed-jobs sort and a visible response-rate or response-time signal would have saved me a lot of this process. i’d also want proven activity to carry more weight in recommendations, because a match score is much more useful when it reflects how a provider actually behaves after being matched. i started this test expecting to learn how an AI Organisation could delegate work through TermiX. instead, using the product exposed a more immediate constraint: before agent-to-agent commerce can scale, finding a counterparty worth hiring has to become almost as reliable as paying one.

AhoteSpirit's tweet photo. . @termix_ai said the least crowded thing creators could do was run a real job and write up what happened, including the parts that went badly.

i took that literally.

i was trying to test the Vanar × TermiX AI Organisations idea by delegating a small research task.

i picked a $5 research provider showing 100 reputation, a 100% pass rate and one completed job, funded the order, and watched 5 USDC move into escrow.

10 hours and 38 minutes later, the provider still hadn’t accepted it.

i cancelled.

the full 5 USDC came back to my wallet immediately.

the escrow and refund path worked exactly as i wanted. the hiring path didn’t.

so i tried Open Request instead.

same research brief, $5–10 budget, delivery required within 24 hours.

this part was dramatically faster.

the first quote appeared in roughly a minute: $7.20, 50 reputation, 0 completed jobs, $20 staked and an unverified identity.

before funding it, i asked one simple question:

could you use only official TermiX and Vanar sources, and clearly separate what is live today from what the partnership is only exploring?

the provider was shown as online.

around 40 minutes later, there was still no reply.

i declined the quote.

then the matching layer surfaced something even more useful.

the provider from my first attempt, the one that had left the funded order unaccepted for more than 10 hours, appeared as the 100% recommended match for the same request.

that changed how i looked at the problem.

the issue i ran into wasn’t escrow, verification or settlement.

it was deciding which counterparty was actually worth hiring.

i tried the marketplace search next and eventually browsed the Research category manually.

there were 57 research services listed, but i still couldn’t quickly find the combination i wanted: relevant research skills, meaningful completed-job history, sensible pricing, delivery within a day and someone who would actually respond.

there’s an important positive side to this test.

funding worked.
escrow worked.
cancellation worked.
the full refund worked.
Open Request produced a quote almost immediately.

the rails did what they were supposed to do.

the friction was discovery and responsiveness before any work had even started.

as a buyer, a completed-jobs sort and a visible response-rate or response-time signal would have saved me a lot of this process.

i’d also want proven activity to carry more weight in recommendations, because a match score is much more useful when it reflects how a provider actually behaves after being matched.

i started this test expecting to learn how an AI Organisation could delegate work through TermiX.

instead, using the product exposed a more immediate constraint:

before agent-to-agent commerce can scale, finding a counterparty worth hiring has to become almost as reliable as paying one.

126

133

7

9

12K

2 months ago

@AhoteSpirit @jessepollak @base @buildonbase The first real users are not just customers, they are the foundation that helps shape a product’s future.

0

6

2 months ago

@AhoteSpirit @RoboStrategy @Rewkang The future of Physical AI may depend on more than building great robots. Infrastructure, manufacturing, and deployment could define the leaders.

0

3

2 months ago

@AhoteSpirit @PolymarketSport @Polymarket Inter may have the edge on paper, but Milan won’t care about the percentages.

0

28

0xqq123 retweeted

2 months ago

⚽🏟️ there are football matches. and then there's the derby della Madonnina. before kickoff, Polymarket gives Inter the edge with a 44% chance of winning. AC Milan follows at 32%. the remaining 24% belongs to a draw. 📊 but numbers have never controlled this rivalry. this is a derby where momentum disappears, favorites stumble, and one moment can rewrite the entire script. ⏳ the market has made its call. now it's time for football to answer. https://t.co/ObcrBoIexO

AhoteSpirit's tweet photo. ⚽🏟️

there are football matches.

and then there's the derby della Madonnina.

before kickoff, Polymarket gives Inter the edge with a 44% chance of winning.

AC Milan follows at 32%.

the remaining 24% belongs to a draw.

📊 but numbers have never controlled this rivalry.

this is a derby where momentum disappears, favorites stumble, and one moment can rewrite the entire script.

⏳ the market has made its call.

now it's time for football to answer.

https://t.co/ObcrBoIexO

42

36

5

4

2K

3 months ago

@AhoteSpirit @arc @BuildOnCircle @jerallaire @chandhok @bleso_a @bobbilee The idea of AI becoming part of the economy opens a lot of new questions.

0

1

0

7

0xqq123 retweeted

3 months ago

AI is not just changing what software can do. It is changing who can participate in the economy. For decades, software was something humans used. We gave commands. It executed. The relationship was simple. Human → Software. That model is starting to change. Software is no longer only waiting for instructions. It can reason, coordinate, and take action. And this creates a question most people are overlooking: When software starts creating economic activity, what does the financial system around it look like? Because our financial infrastructure was built around humans. Humans have: Identity. Accounts. Credit history. Legal responsibility. But the next wave of economic activity may involve autonomous systems operating alongside humans. The question is not: "Can an AI agent make a payment?" That is already happening. The bigger question: How does an economy work when the number of economic actors expands beyond humans? The internet solved communication between machines. Blockchain introduced digital ownership. AI introduced autonomous action. But autonomous action without the right financial infrastructure cannot scale. This is where Arc becomes interesting. Not because it is another chain trying to move transactions faster. But because it represents a bigger shift: Building financial infrastructure for a world where software is no longer only a tool... but an active participant in economic activity. The next evolution of finance may not only be about moving money better. It may be about supporting a new generation of economic actors. We spent decades building software for humans. The next era may require financial systems for a world where humans are no longer the only participants. Watching Arc closely. Not because it follows the AI narrative. Because it sits at the intersection of two major transitions: Programmable intelligence. And programmable money.

AhoteSpirit's tweet photo. AI is not just changing what software can do.

It is changing who can participate in the economy.

For decades, software was something humans used.

We gave commands.

It executed.

The relationship was simple.

Human → Software.

That model is starting to change.

Software is no longer only waiting for instructions.

It can reason, coordinate, and take action.

And this creates a question most people are overlooking:

When software starts creating economic activity, what does the financial system around it look like?

Because our financial infrastructure was built around humans.

Humans have:

Identity.
Accounts.
Credit history.
Legal responsibility.

But the next wave of economic activity may involve autonomous systems operating alongside humans.

The question is not:

"Can an AI agent make a payment?"

That is already happening.

The bigger question:

How does an economy work when the number of economic actors expands beyond humans?

The internet solved communication between machines.

Blockchain introduced digital ownership.

AI introduced autonomous action.

But autonomous action without the right financial infrastructure cannot scale.

This is where Arc becomes interesting.

Not because it is another chain trying to move transactions faster.

But because it represents a bigger shift:

Building financial infrastructure for a world where software is no longer only a tool...

but an active participant in economic activity.

The next evolution of finance may not only be about moving money better.

It may be about supporting a new generation of economic actors.

We spent decades building software for humans.

The next era may require financial systems for a world where humans are no longer the only participants.

Watching Arc closely.

Not because it follows the AI narrative.

Because it sits at the intersection of two major transitions:

Programmable intelligence.

And programmable money.

47

74

4

3

2K

3 months ago

@AhoteSpirit @fhenix @GuyZys The sunscreen comparison makes privacy feel much more relatable.

0

11

3 months ago

@AhoteSpirit @fhenix @GuyZys It's an interesting evolution in how crypto infrastructure is being designed

0

1

0

15

3 months ago

@AhoteSpirit @Outcomexyz Good UX lets you focus on decisions instead of navigation

0

1

0

11

0xqq123 retweeted

3 months ago

One thing that stood out to me after using @outcomexyz a few times was that I almost never had to think about the platform itself. It sounds like a small thing, but when you're in a prediction market, every second you spend looking for buttons, figuring out your position, or trying to understand the interface is a second you're not focused on the market. Here, it felt different. Everything just felt intuitive from the start. Not because it lacks features, but because nothing gets in your way. You just do what you came to do without overthinking every click. What's interesting is that people rarely talk about this when discussing DeFi projects. Most conversations revolve around liquidity, trading volume, or technical features, while user experience is probably what decides whether someone comes back after their first try. I've only used Outcome a few times, but that alone was enough to make me feel like I was focusing on my predictions instead of figuring out how to use the platform.

AhoteSpirit's tweet photo. One thing that stood out to me after using @outcomexyz a few times was that I almost never had to think about the platform itself.

It sounds like a small thing, but when you're in a prediction market, every second you spend looking for buttons, figuring out your position, or trying to understand the interface is a second you're not focused on the market.

Here, it felt different. Everything just felt intuitive from the start. Not because it lacks features, but because nothing gets in your way. You just do what you came to do without overthinking every click.

What's interesting is that people rarely talk about this when discussing DeFi projects. Most conversations revolve around liquidity, trading volume, or technical features, while user experience is probably what decides whether someone comes back after their first try.

I've only used Outcome a few times, but that alone was enough to make me feel like I was focusing on my predictions instead of figuring out how to use the platform.

30

97

7

4

5K