Bittensor Has A Marketing Problem (And How We Can Fix It)
Transforming Bittensor's Marketing Strategy
As I continue my journey into the Bittensor ecosystem, I've noticed something troubling.
The technology is brilliant, the vision is compelling and the potential is enormous.
But something is off.
We've got subnets competing for attention with their miners pushing computational boundaries. Yet despite all this activity, Bittensor remains largely unknown outside crypto-native circles.
I've written here before about when I tried explaining Bittensor to my wife.
Her takeaway: "So its a bunch of computers arguing about who's smartest and getting paid for it?"
Not a bad effort, but if even my simplified pitch left her puzzled, imagine how outsiders feel.
This isn't just a gripe, it's a barrier to the open AI revolution we all strive for.
And it isn't a technology problem. It's a marketing problem.
Why Bittensor's Marketing Is Broken
The Tower of Babel Problem
Bittensor has over 100 active subnets, each with its own narrative, terminology, and value proposition.
Chutes talks about serverless AI compute.
Targon discusses high-speed confidential AI.
Lium promises permissionless high-performance GPUs.
To a newcomer, it sounds like different languages being spoken in the same room. There's no unified story that connects these pieces into a coherent whole.
As I noted previously when evaluating subnet landing pages: subnets assume users already speak the language of validators, miners and machine learning, without explaining the basics. They fail to answer the toddler-level question: 'What does this do, and why should I care?'
The "Bitcoin for AI" Trap
Too many explanations fall back on the tired "Bitcoin for AI" analogy. This ties Bittensor's identity to cryptocurrency at a time when crypto still has negative connotations for many.
It oversimplifies the actual innovation (Bittensor isn't just a token, it's an entire market mechanism) and misses the real value proposition: democratizing AI development.
When I first explored Bittensor in 2023, I stepped away multiple times because these shallow analogies didn't help me grasp the actual value.
The Technical Jargon Wall
Most marketing materials assume technical proficiency that newcomers don't have.
Take this real example from a top 5 subnet this week where they shared a huge update on their X account:
"The short 70B tests are behind us and the results were strong. Now begins the long war. The mission: to prove that our SparseLoco optimizer and Gauntlet incentive mechanism can carry us all the way through at this scale. This is the largest decentralized training run ever attempted by any lab."
What does this mean to someone who just wants to understand how Bittensor helps them?
Though it sounds impressive, not a whole lot.
They also received the below as a top response:
Compare this to how I previously broke down the whitepaper: "A peer-to-peer network of computers that monetize machine intelligence work by turning AI development into a decentralized economy." That's something more people can grasp.
The Missing "So What?"
In an earlier issue, I addressed critics who question whether Bittensor can compete with big tech. But the deeper problem is this: we're not clearly articulating why people should take any notice.
Most explanations focus on how Bittensor works rather than why it matters.
We lead with mechanics instead of meaning.
When I explained Bittensor to my wife I could not articulate a compelling narrative.
Something more broad I could lead with in future could be: "Bittensor ensures AI serves humanity rather than controlling it, by making sure no single company owns the future of intelligence."
What Successful Marketing Looks Like
Ethereum's "World Computer"
Ethereum didn't market itself as a decentralized platform running smart contracts. They called it the "World Computer": a simple phrase that captured imagination while remaining technically accurate.
Bitcoin's "Digital Gold"
Bitcoin moved beyond "decentralized digital cash" to "digital gold", a narrative that resonated with institutional investors and created a clear value proposition.
OpenAI's "ChatGPT"
OpenAI didn't lead with transformer architectures or RLHF. They gave people something tangible: "An AI that chats like a human." Simple and immediately relatable.
A subnet that got it right: Autoppia (subnet 36)
Check out this article from Autoppia (subnet 36) who explain their business case in clear and accessible language, focusing on real world benefits and emphasizing the benefits of their decentralized approach:
The Bittensor Narrative We Need
The Bittensor ecosystem needs a narrative that connects to universal values, not just technical specs.
It needs to show through tangible use cases what it actually does while speaking to multiple audiences, not just machine learning engineers.
And crucially, it needs to create emotional resonance beyond just financial incentives to make a real impact.
Here's a framework I've been developing:
For the Privacy-Conscious User
"Bittensor keeps your data private while giving you access to powerful AI. No corporate surveillance, no data harvesting, just intelligence that works for you."
For the Developer
"Bittensor turns your AI skills into income by connecting your models with users who need them. No VC funding required, just code that delivers value."
For the Institutional Investor
"Bittensor creates the economic plumbing for open source AI, turning community contributions into measurable value. Like Linux for the AI era, but with built-in economics."
This approach mirrors what I outlined in my funnel framework: different messages for different entry points into the ecosystem.
Practical Fixes We Can Implement Today
1. Create a "Bittensor Elevator Pitch Kit"
Develop 3 versions of a 30-second explanation:
Technical: For developers and validators
Value-based: For end users and investors
Visionary: For media and influencers
2. Implement the Awareness Stage Framework
As detailed in my previous issue, create content specifically for each stage:
Stage 1: Content about AI privacy concerns and centralized control
Stage 2: Comparisons between centralized and decentralized AI
Stage 3: Bittensor-specific value propositions
Stage 4: Clear paths to participation
Stage 5: Advanced contribution guides
3. Standardize Core Messaging Across Subnets
Subnets should maintain their unique identities while aligning on:
A shared value proposition statement
Consistent explanation of core concepts
Common entry points for beginners
4. Build "Try Before You Commit" Experiences
As with Kaggle datasets for aspiring data scientists, create low-barrier ways to experience Bittensor's value:
Browser-based demos
Simple API playgrounds
Guided tutorials with immediate feedback
Our Role in Fixing This
You don't need to be a marketing expert to help. Here's how we can contribute:
When explaining Bittensor, diagnose awareness stage first.
Share simple explanations that focus on value, not mechanics.
Create beginner-friendly resources (even a single clear tweet helps).
Call out confusing jargon when you see it.
The Opportunity Ahead
Open source has given us the internet as we know it. But AI is different. The costs of development are orders of magnitude higher.
Without an economic model, open source AI will remain a toy while corporations control the future.
Bittensor provides that economic model: but it's useless if nobody understand.
By fixing our marketing problem, we can create experiences that guide users through the path of each stage rather than expecting them to leap from "What is AI?" to "Let me deploy a miner" in one bound.
This isn't about dumbing down the technology, it's about elevating the message to match the brilliance of what we're building.
Let me know your thoughts on this framework. What marketing messages have resonated with you? What's still confusing? I'd love to feature community contributions in a follow-up piece.
Until next week.
Cheers,
Brian