How to Engineer a Competitive Miner for Real-Time Search
In Part 1, we explained how skilled developers can earn by competing in real-time search.
If you haven’t read it yet, start here:
How Skilled Developers Can Earn by Competing in Real-Time Search
Now we move to the technical side.
This is a practical roadmap for engineers who want to compete seriously.
Not a setup tutorial.
A competitive engineering guide.
Step 1: Understand the Network You’re Entering
Desearch operates as Subnet 22 on the Bittensor network.
Bittensor is a decentralized AI protocol where machine intelligence is measured and rewarded on-chain. Validators evaluate miner outputs, and emissions are distributed proportionally based on performance.
If you’re new to Bittensor, review:
- https://docs.learnbittensor.org
You don’t need deep protocol expertise to start.
But understanding how scoring affects emissions gives you an edge.
sbb-itb-00b00a8
Step 2: Study the Official Repository
Everything you need to understand lives here:
https://github.com/Desearch-ai/subnet-22
Focus on:
- neurons/miners/
- neurons/validators/
- neurons/validators/reward/
Do not guess what matters.
Read the validator logic.
Understand how scoring works.
Engineer backward from reward distribution.
Competitive miners don’t build blindly.
Step 3: Understand What Actually Gets Scored
When a query is sent:
1. Multiple miners receive it
2. Each miner returns structured output
3. Validators compare responses
4. Scores determine ranking
5. Ranking determines emission share
Scoring typically evaluates:
- X retrieval quality
- Web search relevance
- AI summary quality
- Structural correctness
- Freshness of data
- Latency
You are competing against other engineers.
Relative performance determines reward.
Step 4: Design Your Architecture Strategically
A competitive miner is a real-time backend system.
Treat it like production infrastructure.
A strong design includes:
Query Understanding
Classify query intent.
Route intelligently.
Avoid generic retrieval.
Retrieval Strategy
Use combinations of:
- AI Search
- Web Search
- X data
- Reddit discussions
- Other public sources
Filter early.
Prioritize relevance and freshness.
Ranking Layer
Deduplicate results.
Remove noise.
Score relevance.
Return the strongest top results.
LLM Summarization
Generate grounded summaries.
Avoid hallucination.
Keep structure consistent.
Be dense and precise.
Performance Optimization
Use async pipelines.
Parallelize API calls.
Cache intelligently.
Minimize unnecessary LLM usage.
Reduce latency.
Milliseconds matter.
Step 5: Improve Beyond the Baseline Miner
The repository includes a baseline implementation.
It works.
It demonstrates structure.
It is not optimized for rank.
If you run it unchanged, you will likely rank low.
Serious miners improve:
- Retrieval filtering
- Ranking heuristics
- LLM prompt design
- Data cleaning logic
- Latency management
Optimization separates competitors from participants.
Step 6: Study the Reward Logic Directly
This file is critical:
neurons/validators/reward/reward.py
Understand:
- Weight distribution
- Score normalization
- Emission calculation
If one scoring component carries more weight, optimize there first.
Do not optimize randomly.
Optimize intentionally.
Step 7: Iterate Continuously
Mining is not deploy-and-forget.
Top competitors:
- Monitor validator updates
- Compare output quality
- Refine prompts
- Improve retrieval precision
- Reduce hallucinations
- Lower response time
If others improve and you do not, your rank falls.
This is a live engineering competition.
Step 8: Develop the Right Skill Set
Strong advantages come from:
- Python async programming
- API orchestration
- Information retrieval design
- Prompt engineering
- Data quality control
- Backend performance tuning
This is backend systems engineering — not speculation.
Step 9: Engage With the Community
If you want to compete seriously:
- Review open issues in the GitHub repo
- Watch for validator updates
- Join the Discord: https://discord.com/invite/eb6DTZNMF5
- Follow subnet announcements
Understanding how validators think improves your edge.
Final Perspective
Engineering a competitive miner means:
- Studying how you are evaluated
- Designing for measurable scoring factors
- Optimizing continuously
- Treating this like a real backend product
The protocol rewards performance, not participation.
If you approach it seriously, you can compete.
Performance determines reward.