Claude DESTROYS ChatGPT for lead gen
I put together the Claude AI Lead Prompt Vault (below)
Claude is by FAR the best at finding high-intent leads and booking meetings.
I use my info combined with my prompts to source leads, write personalized outreach, qualify prospects, and more.
My prompts are INSANE and replace entire lead gen agencies.
I compiled ALL my Claude prompts into one vault:
• The ICP Excavator
• The Lookalike Hunter
• The Trigger Event Scanner
• The Prospect Profiler
• The Pain-First Email
• The 7-Touch Sequence Generator
• The Reply Decoder
• The Pre-Call Brief Generator
• The Objection Reframer
• The Lead Generator System
Want access to this vault?
→ Comment "Claude"
→ Connect with me and I'll DM the vault!
9 out of top 15 subnets earning the most tao emissions burning over 89% of miner emissions
going to be interesting to see if any of these projects burning 100% of miner rewards get slashed
Remember Shak from RidgesAI?
At one point, Shak was one of the most visible faces in the Bittensor bittensor:native ecosystem:
- interviews
- podcasts
- live events
- Telegram chats
Recently, I watched a video by Siam Kidd discussing potential exit scenarios for subnet owners, and RidgesAI came up.
From what’s publicly being speculated:
- Shak may have withdrawn roughly $2.5M from the owner key
- the subnet may have then been sold to Latent Holdings
Again, speculation, but it raises a very important discussion for Bittensor bittensor:native long term.
There was little to no communication from:
- Shak
- the RidgesAI team
- Latent
Alpha holders were essentially told there was a “leave of absence.”
The bigger issue is this:
As subnets mature and potentially reach escape velocity, what happens when venture capital firms or larger entities want to acquire them?
How are subnet holders protected or accounted for?
There likely needs to be some mechanism that ties value accrual back to the very community members who supported and helped bootstrap these subnets early on — otherwise people will understandably view these situations as rug-adjacent.
Maybe the conviction mechanism helps mitigate this over time.
Either way, I think this becomes one of the most important governance and incentive discussions for the future of Bittensor.
BTW, this is not a post to dump on Shak or Ridges. This is just a post to hopefully illicit discussion on the topic of subnets "leaving" due to a buyout offer.
Let's be real: if a VC offered one of the top subnets $100M, do you think they take it?
If they do, how does this effect alpha holders?
@TAOTemplar@CryptoZPunisher@lium_io@fish_datura i like how he's doing the best of both worlds
only 45% miner burn, so gives people ability to earn
also buyback and burn to increase scarcity
If you're talking about @fish_datura , he's the LEAST exploitive long-term subnet owner. He's BURNING his subnet owner emissions on #sn28. That's equivalent to 3k+ USD/day that he's voluntarily burning instead of extracting from the dead subnet.
NO other subnet owner has done this.
All other subnet owners are worse on the exploitation front.
Proof: taoflute.com/d/0552bf6b-190…
Did you know #sn51@lium_io burns ~50 TAO worth of their alpha token per day? That's 14k USD 🔥❤️🔥burnt per day.
The Burning-est subnet on bittensor.
taoflute.com/d/0552bf6b-190…
A few weeks ago, I started researching the Bittensor subnets, and honestly, it’s a bit of a rabbit hole. With 128+ active subnets, it’s easy to get lost in the noise of "emissions" and "alpha tokens."
But once you look past the ticker symbols, you start to see where the real utility is being built.
Here’s a breakdown of what I’ve found, comparing three heavy hitters in space. 👇
1⃣ Chutes (SN64) | The Revenue Engine
Chutes focuses on serverless AI inference. High-efficiency, low-cost compute.
They’ve managed to offer prices significantly lower than centralized giants like AWS. They are actually generating daily revenue (reportedly around $22k/day recently). It’s a great example of a "working" subnet that provides immediate value to developers.
2⃣ Targon (SN4) | The Secure Compute Layer
Manifold Labs (the team behind Targon) recently collaborated with Intel on secure, decentralized compute. They are solving the "trust" issue: how do you run sensitive workloads on hardware you don't own?
This is the bridge to enterprise adoption. By using Intel TDX for encrypted environments, they’re making $TAO viable for companies that can’t risk data leaks.
3️⃣ Leoma (SN99) | The Cinematic Video Engine
While the others are building the "pipes" and "electricity," @leoma_ai is delivering a production-ready creative platform. This is where I think the market is currently undervaluing the project.
Most subnets are backend-heavy. Leoma is a decentralized, open-source cinematic AI platform. It transforms text and images into studio-grade videos by leveraging open competition across the network’s best-performing models.
It ensures continuous improvement through a Miner-Validator loop where the highest-performing model wins each request.
While I love the technical milestones of Chutes or Targon, Leoma is what makes those technologies accessible to filmmakers and creatives. It provides direct access to decentralized video intelligence without gatekeepers.
The TAO ecosystem is maturing. In 2024, it was all about the "idea." In 2026, it’s about who has a product people actually use. The infrastructure subnets are the backbone, but I’m keeping a close eye on those subnets that are actually putting that power into a usable tool.
Which subnets have you been monitoring lately? Are you prioritizing the "plumbing" or the "apps"?
NFA - DYOR
I tried using @chutes_ai for my CRM business, my honest experience...
Kept hitting [CHUTES] Status 429: {"detail":"Infrastructure is at maximum capacity, try again later"}
for many days and I couldn't test my AI prospecting feature.
I use chutes for my private discord, for llm summaries, I don't have problems but with the CRM, no idea it barely works
maybe because im requesting while i'm in Vietnam and it surges during that time zone but it was unusable.
i ended up, doing like every customer, after some friction just putting my CC to deepseek API and forgetting everything.
Felt a bit dissapointed, but time is my most valuable ressource and I don't have time to try to understand utilization, "why" it crashes, "what" to do about it.
"why" is it always at 90-100% capacity with a red circled emoji.
Code model fallbacks and take risks the infra can "handle" it.
I asked AI, it said anthropic or deepseek api is more stable and went w it.
I just wanted to test and build FAST.
Am I entitled and asking too much?
I don't think so, it's a fair reaction even tho I'm a bittensor maxi.
I'll go back to chutes when im more experienced maybe.
No hate what so ever, i'm journaling my experience, and I know it'll only get better.
$TAO #sn64
Shak left, Sam left.
Maybe it's time we started asking the tough questions. Why are our biggest builders leaving? What will stop the next biggest builders from leaving?
bittensor:native
@_olaige That's a great write up - very well written @Learncryptohere - thank you for taking the time to dig into the project and for your technical accuracy.
DeFi's been bleeding for years. Liquidity is fragmented, swaps get sandwiched, and routing for borrowing, lending, and bridging is painfully manual.
MEV alone has drained $1.7B+ from Ethereum ethereum:native users since 2020 (and that's before you count the slippage, gas waste, and missed rates from manually checking multiple lending protocols for a single loan).
Minotaur (SN112) is the fix. A universal intent layer where solvers compete to execute any DeFi action (swap, borrow, bridge, yield, you name it) at the best price.
The cherry on top: it's built on Bittensor bittensor:native. The chain that attracts the world's best brains to ship things no one else can.
Excellently written article about @minotaursubnet by @Learncryptohere.
Worths a read for sure ⏬⏬
so i took a little break on the mining push w/ arbos
had some trouble hooking up chutes api to it
so pivoted to hermes
used chutes api and specifically the glm 5.1 model, which has gotten rave reviews
2 days i trained a model on bitmind using its dfresearch repo
had some back and forth with dependency errors
then finally actually submitted my first model on bittensor
feels good man, more to come