Many drafts like to present big news about 'airdrops, launches, collaborations', but when it comes to business, it is more important to look at engineering side KPIs. Here’s a checklist I used during my research on Lagrange:
1) Proving Side: Single proof generation time (average/P95), aggregation cost, failure retry rate, task queue length; DeepProve-1's GPT-2 has already provided a benchmark, but you need to switch to your own input scale and run a sandbox first.
2) Network Side: Number and distribution of operators on EigenLayer, recent month downtime/downgrade events, task completion rate; looking at '85+ operators' is not just for appearances, but to estimate your peak fault tolerance capability.
3) Economic Side: Can the costs—subsidies—staking flows of LA cover your business peaks and troughs? The foundation specifies that staking/commissioning can be directed to specific provers, guiding emissions to shortage tracks, which determines whether 'the more you use, the lower the cost will be.'
4) Route Side: Does the pace of supporting LLaMA/Gemma/Claude/Gemini match the product roadmap? Do not write 'will support' as a launch time to avoid mismatching the launch window.
5) Market Side: Airdrops and spot listings (15M airdrop, launched on 7/9) are just the starting point for liquidity and exposure, not a guarantee from the 'demand side'; refer back to Binance Research's technical and product analysis to address the root question of 'who is paying for the proofs.'
Run through this checklist, and you will have a clearer understanding of 'whether this is the infrastructure you need.' My suggestion is: start with the sandbox, run the three business lines—'not doing proofs', 'only doing partial proofs', 'full-link proofs'—simultaneously for two weeks, observe the differences in conversion/complaints/cost, and then decide on the production ratio.
Interaction: What type of metrics is your team currently having the hardest time obtaining: A. Proving cost and latency, B. Network stability and failure rate, C. Token economics and subsidy forecasting?
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