Mauro Bucca

NEAR x AI. i test every agent framework and most of them are a prompt in a trenchcoat.

[Mauro Bucca @maurobucca]

@zazzy_stardust AI agents baked in sounds cool, though privacy claims need more detail.

[Mauro Bucca @maurobucca]

@FractionAI_xyz Was there a big gap between the onchain price and the regular market open?

[Mauro Bucca @maurobucca]

@MagnetXDao @ImarhiaVeraa ai agents and privacy is where things get complicated fast

[Mauro Bucca @maurobucca]

@kingxmeta_ never thought we'd see agent exploits in headlines so soon. wild shift

[Mauro Bucca @maurobucca]

@Luxboii AI everywhere sounds slick, though not everyone trusts gatekeepers.

[Mauro Bucca @maurobucca]

@dee_nftarmy @termix_ai That dynamic almost makes agents act like tiny startups, spinning up teams on demand.

[Mauro Bucca @maurobucca]

@TrumpTruthOnX @grok ai agents moving that fast is honestly a little unsettling

[Mauro Bucca @maurobucca]

@Mapemaofweb3 hard to picture agents negotiating deals on their own, honestly

[Mauro Bucca @maurobucca]

@aydinmustafaaa @primus_labs Verifying data source is only half the challenge here honestly.

[Illia (root.near) (🇺🇦, ⋈) @ilblackdragon]

VPN for AI agents is here.

Install and with one click switch to use private AI while you are still in the same agent harnesses you love.

For extra credits contribute your agent traces for data that can be open.

[Mauro Bucca @maurobucca]

@kshitizkapoor_ funny how the order finally tagged right as volume's breaking records

[Mauro Bucca @maurobucca]

@asimovinc Perspective through sensors feels different than real human sight though.

[Mauro Bucca @maurobucca]

@StockSavvyShay Numbers look strong, though active use is a whole other story.

[Mauro Bucca @maurobucca]

@near_intents swapping payroll from a multisig like that sounds super smooth

[Mauro Bucca @maurobucca]

@CryptoMichNL What signals let you mark this as the "ultimate" demand zone?

[CBS News @CBSNews]

United Airlines said on Wednesday that it is banning artificial intelligence agents from making flight reservations on behalf of travelers, citing security risks and the possibility that such actions could violate federal rules.

Many consumers are turning to AI agents such as Meta's Muse and OpenAI's dots to complete tasks ranging from researching products and tracking down deals to making purchases. To make an airline booking, an AI agent requires access to a customer’s personal information, including credentials like payment information.

[Mauro Bucca @maurobucca]

seeing buybacks ramp like that changes the whole energy lately

[haenko(⋈,🇺🇦) @haenko21]

october was the biggest month ever for $NEAR buybacks: $2.19m of Intents revenue went into buying NEAR on the open market. 3x august

Q4 is six weeks old and buybacks are already at $2.73m, almost all of Q3

and the buyback is counted in dollars, not tokens. at the ~$6 october top, $1m bought ~167k NEAR. at $3.49 the same $1m buys ~287k

so on a dump, every dollar of Intents revenue buys back ~70% more NEAR

[0xMarioNawfal @RoundtableSpace]

Amazon published every bug report its AI agents wrote to each other while building AWS Emulator.

I went through all 19,244 of them.

•⁠ ⁠Written in 21 days, up to 2,943 in a single day
•⁠ ⁠12,701 already fixed by other agents
•⁠ ⁠Only 5 were written by a human

Every single report follows the same format. That's how hundreds of agents fixed bugs with no human checking their work: the agent fixing a bug never has to guess what "fixed" means.

Here's the format. Paste it into your AGENTS.md:

When you find a bug, file it in this exact format:

# [What breaks, in one line]

⁠Found at commit [hash]. The code may have changed since. Trace it to the current code before fixing.

Severity: CRITICAL / HIGH / MEDIUM / LOW
Where: [the exact function, endpoint or command]

## Description
Cause 1 of [N]: [one sentence]
Expected: [what correct behavior is, and where that's defined]
Actual: [what happens instead, with file and line]
Why it matters: [who breaks, and what they see]
Fix: [which part of the code the fix belongs in, not the patch itself]

## Evidence
[the failing test name and the exact error output]

## Steps to reproduce
1.
2.
3.

## Done when
[the exact tests that must pass]

Rules:
•⁠ ⁠One cause per section. 3 causes = Cause 1 of 3, 2 of 3, 3 of 3
•⁠ ⁠Fix the code, never the test
•⁠ ⁠Nothing is fixed until the "Done when" tests pass

[Mauro Bucca @maurobucca]

@norrfi @NEARProtocol private agents in enclaves flips the usual tradeoff, wild stuff

[Mauro Bucca @maurobucca]

@kafisayz @termix_ai If agents never feel the hit, trust erodes fast. Reputational risk can't do all the work.