Nockleone

Investing in projects that actually do something

[0xfffaf @0xfffaf]

always similar fud about pow projects, dont get shaken out. Good to see Enrico address it, but wouldn't mind it being public vs dm

[Enrico Ottavian @enrico_otta]

Happy to tackle each publicly, all points are already quite well explained in the blog and docs of the project in fairness.

This feels like a long Claude session prompted for fud showcasing, and not a very good one either, hence the misunderstanding vs misrepresentation distinction I made.

[Nockleone @nockleone_]

@DrShillBee $TSC $NOCK $DOT coded saaarr

[DrShillBee @DrShillBee]

https://t.co/xPwKdrLfm3

[Nockleone @nockleone_]

@DrShillBee @Tensorcash tensorcash:native base:0x9b5e262cf9bb04869ab40b19af91d2dc85761722 base:0x23a2847d772803f9efc64b4277b782b06296fe51 base:0x797f214a2cd64a4963a91fa21c8c55ec3eba4714 all you need to retire in 2027

[DrShillBee @DrShillBee]

You walk into a gold shop and pay for 24K gold. Later you find out it was plated brass. You paid for one thing, got another, and had no way to tell.

That’s how AI works today.

You pay for a premium model, but you only have the provider’s word that it actually ran. They could quietly swap in a cheaper one and you’d never know. One 2026 study found unofficial AI resellers failed model identity checks in almost half of its fingerprint tests.

Gold solved this long ago with the hallmark: a stamp that proves purity, which anyone can check.

tensorcash:native is building the hallmark for AI.

On TensorCash, every answer can carry a proof of which model produced it. Anyone can rerun the model and verify it. If someone cheats, the proof catches them. It already happened on mainnet, when a miner who cut corners got zero rewards.

And the work that creates this proof is the same work that mines the chain. No wasted energy, just real AI answers you can verify.

As AI starts running agents, payments and business decisions, "trust me" won’t be good enough.

[Nockleone @nockleone_]

@DrShillBee tensorcash:native coded.

[DrShillBee @DrShillBee]

https://t.co/rHluJ1wMW7

[Nockleone @nockleone_]

@DrShillBee @sibylcap Higher please

[DrShillBee @DrShillBee]

" A flat memory file is O(n) per turn and O(n²) per session. base:0x797f214a2cd64a4963a91fa21c8c55ec3eba4714 is O(1) "

here's what's coming for Sibyl :

→ self learning memory: autosave + work based skill generation, so agents can retain useful knowledge without you managing everything manually.

→ automatic context debloating: unnecessary context gets moved into structured memory at session startup, helping reduce compute and token usage.

→ Claude + ChatGPT integration: a planned MCP connector could bring Sibyl's shared memory to users of both platforms.

just think about the implications,

millions of people already use these AI tools, but their agents still need relevant context to work effectively.

what if they could tap into structured memory instead of repeatedly feeding their AI the same information?

less unnecessary context. fewer wasted tokens. more efficient workflows.

and Sibyl isn't limiting access to crypto users.

→ fiat payments via Stripe could open Pro memory to non crypto customers.

→ email or wallet sign in, with card or USDC payments.

→ an NFT gated agentic skill bank, where builders can monetize useful skills at fixed mint prices rather than relying on NFT price speculation.

and your favourite part, a healthy portion of the bank's revenue is intended to fund the base:0x797f214a2cd64a4963a91fa21c8c55ec3eba4714 staking pool.

this is the part everyone must pay attention to.

Sibyl Memory is only one product.

the bigger opportunity is building an ecosystem around AI memory, reusable agent skills, integrations and revenue.

making AI smarter matters.

but making AI remember, learn and work efficiently across sessions could be just as important.

Sibyl is trying to build exactly that infrastructure.

and the next upgrade is already in final QA, according to the team.

[Nockleone @nockleone_]

@DrShillBee @sibylcap A $NOCK X $SIBYL will be interesting

[DrShillBee @DrShillBee]

"WIN WIN FOR EVERYONE"

The winner in agent memory is not just whoever tops a benchmark. it is whoever does the same job with fewer tokens too.

Sibyl Memory feeds far less context into the model than other memory engines. The next best engine feeds 52x more.

That matters because I think AI inference tokens are going to become one of the biggest resources in the AI economy.

as agents become more autonomous, they're going to make more requests, process more context and consume more inference.

if the same task can be completed using significantly fewer tokens, people will naturally shift towards the system that does it more efficiently.

That is what base:0x797f214a2cd64a4963a91fa21c8c55ec3eba4714 does the best.

better memory → less unnecessary context → fewer tokens → lower inference costs → faster agent workflows.

and there's another angle:

inference requires massive amounts of compute and energy, which also means water consumption at data centers.

if you can reduce unnecessary inference, you're potentially reducing the resources needed to run those workloads too.

then there's the base:0x797f214a2cd64a4963a91fa21c8c55ec3eba4714 side.

staking base:0x797f214a2cd64a4963a91fa21c8c55ec3eba4714 gives you SIBYL + DIEM, with DIEM being usable for inference.

so you're not just staking an asset.

you're potentially getting access to the very resource that becomes more valuable as AI usage grows.

AI demand isn't slowing down.

more agents → more inference → more demand for compute.

and if inference becomes more expensive over time, having a system designed around using less of it becomes increasingly interesting.

add the growing number of partnerships, the products being built around Sibyl, and everything happening with the ecosystem.

and remember, the Memory Plugin is only one of the products.

Other than that, circulating supply has dropped around 40%.

and I don't see base:0x797f214a2cd64a4963a91fa21c8c55ec3eba4714 as just another standalone token sitting beside a product.

the token is designed to go hand in hand with the revenue side of the ecosystem.

once revenue starts flowing (which is gonna happen soon enough), you can probably guess why that becomes interesting.

i've also been attending their spaces and listening to what the team is building.

every time i do, my conviction gets stronger.

there's a lot more being built here than people are currently pricing in imo.

at these levels, this looks like a no brainer to me.

[Nockleone @nockleone_]

@DrShillBee @sibylcap Revenue flowing to token. Healthy

[DrShillBee @DrShillBee]

base:0x797f214a2cd64a4963a91fa21c8c55ec3eba4714 is about to start making money and most people are still sidelined.

You can now buy memory product with a card. No wallet, no bridge, no seed phrase. That is the entire software market suddenly able to become a customer. this is the lab's first self serve revenue rail, and memory is only product one.

Organizations that use Sibyl say it works like magic. I mean why won't they say that. For each question where Sibyl feds the model about 228 tokens from memory, the next best engine pulls roughly 52x more. 52x is such a big difference. Everyone is only arguing about accuracy scores. Sibyl quietly made agents cheaper to run by an order of magnitude.

Meanwhile, for token holders:

-staking pool filled by buybacks.
-no dilution.
-no printed apr to fake a yield.
-flex tier is around 20% with zero lock, and you earn base:0x797f214a2cd64a4963a91fa21c8c55ec3eba4714 and base:0xf4d97f2da56e8c3098f3a8d538db630a2606a024 at the same time.
-new partnership with hydrex, more onchain revenue routes, more value to liquidity providers and holders.

The pipeline is stacked.
-new memory benchmark incoming.
-patent work on the living graph network.
-sovereign improving with beta testers.
-more onchain teased for holders on the last space.

now zoom out.

Persistent memory is not a crypto problem. Every serious agentic system on earth has it. Cheaper context and sharper recall is useful to literally anyone building agents.

[DrShillBee @DrShillBee]

You don't realize what is coming for base:0x797f214a2cd64a4963a91fa21c8c55ec3eba4714
When you do, remember it will still be early

A few things you must know:

→ 50k users have already set up Sibyl Memory Plugin

→ hackathon backed by @base , @virtuals_io & @sibyl_labs_

→ Living Graph Network is live

→ dev has hinted that staking base:0x797f214a2cd64a4963a91fa21c8c55ec3eba4714 will be very rewarding (👀)

TLDR : It is happening.

[Nockleone @nockleone_]

@DrShillBee @base @virtuals_io @sibyl_labs_ base:0x797f214a2cd64a4963a91fa21c8c55ec3eba4714 to bibyl

[Nockleone @nockleone_]

@DrShillBee @nockchain nock nock

[DrShillBee @DrShillBee]

"YOUR GPU DOESN'T HAVE TO SIT IDLE ANYMORE"

Most decentralized GPU networks have one problem:
your GPU gets paid when someone rents it.

So,
--> no customer = idle hardware.

@nockchain changes the economics underneath that model.

The same GPU can potentially do three things at once:

→ provide useful compute
→ generate verifiable ZK proofs
→ secure the Nockchain and earn base:0x9b5e262cf9bb04869ab40b19af91d2dc85761722

that creates a pretty different incentive structure.

Instead of:
GPU → wait for customer → earn

you get:
GPU → mine + compute → earn

and that matters because mining can give the hardware an economic baseline even when compute demand isn't there.

if that baseline allows providers to offer compute more competitively, Nockchain could have an interesting advantage over traditional GPU marketplaces like Akash or io-net etc.

The bigger unlock is the general purpose Nock zkVM.

Today, Nockchain already uses ZK proofs in its proof-of-work. The long-term vision is much bigger: make arbitrary computation provable, so the network can support markets for things like AI inference, financial computation, web proofs and other workloads where you don't just want an answer --> you want proof that the answer was computed correctly.

that's a fundamentally different product.

you're not simply renting a GPU.

you're buying computation + cryptographic verification.

and with proving layer becoming efficient enough, the economics start getting interesting:

more GPU's means
→ more compute/proving capacity
→ lower costs
→ more customers
→ more workloads
→ more network demand
→ stronger base:0x9b5e262cf9bb04869ab40b19af91d2dc85761722 economics
→ more incentive for GPU providers
→ more GPUs
→ back to first arrow

@nockchain isn't trying to win by simply having more GPUs. It's trying to make those GPUs economically useful even when they're not serving a customer, while turning their useful computation into something that can be cryptographically verified.
If the general zkVM, compute markets and economics all click together...
Nockchain doesn't just compete for GPU supply.
it gives GPU supply a reason to come to Nockchain.

[DrShillBee @DrShillBee]

tech --> 🧠
dev --> 🌷

[Nockleone @nockleone_]

@DrShillBee @sibylcap $SIBYL to a bibyl