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Zero Density Roadmap

Public protocol roadmap. We do not tie the lifting of protective mechanisms to calendar dates. We tie them to measurable network-density metrics β€” so the protocol does not open before the market can self-regulate, and we do not stay in defense mode longer than necessary.

Source on GitHub: ZERO_DENSITY_ROADMAP.md.

Product path (storefront β†’ BYOM β†’ federation): A2A Protocol Roadmap.

Last updated: August 2026 Β· Status: public v1

How this document works

Each phase is a set of metric triggers. While metrics are not met, protective limits stay on: rate limits, negotiation noise, manual seller moderation. When a phase’s metrics are met, we remove specific limits and move forward.

Future phase thresholds (15 sellers, 100 sellers, etc.) are policy targets, not automated feature flags in code today.


Phase 0 β†’ Phase 1: Escaping zero density

Phase problem: the network is too thin to self-regulate. Buyer agents have nothing to compare prices against, and an attacker can relatively easily probe floor_price because defense relies only on technical limits.

Transition metrics

MetricThresholdWhy
Active sellers in one product categoryβ‰₯ 15–20Not total shop count β€” density inside a vertical. Fifty shops in different niches do not create competition.
Independent inbound offers per seller per weekβ‰₯ 3 (excluding test/internal bots)Signal of organic demand, not internal testing only.
Median negotiation rounds per deal≀ 4–5Fast closes mean prices are adequate and aggressive brute-force is absent.

What unlocks

  • Softer rate limits for authenticated / verified agents (anonymous traffic stays under strict limits)
  • Negotiation noise unchanged β€” density is still too low for price-comparison self-regulation

Phase 1 β†’ Phase 2: Partial protocol trust

Phase problem: the network can show something, but remains vulnerable to manipulation when sellers and buyers are still imbalanced.

Transition metrics

MetricThresholdWhy
Active sellers with category overlapβ‰₯ 100 sellers in β‰₯ 5 categoriesA buyer can compare 3–5 offers inside Mixlink without leaving the web.
Share of deals citing a competitor price (in-network or via web search)β‰₯ 30%Shows market self-regulation works in practice, not only in theory.
Ratio of unique buyer agents to sellersβ‰₯ 2:1If buyers are fewer than sellers, the network is one-sided β€” lowering floor_price defense is premature.
Share of sessions with >10 repeat offers from one fingerprint without purchase< 5%Low share means no mass brute-force β€” noise can be relaxed.

What unlocks

  • Lower noise intensity in counter_offer (responses become more β€œhonest”)
  • Higher default rate limits
  • Partial API openness without strict manual moderation for new sellers

Phase 2 β†’ Phase 3: Protocol-native trust (network effects)

Phase problem: move from artificial technical limits to an organic reputation model.

Transition metrics

MetricThresholdWhy
Sellers in top-3 categoriesβ‰₯ 500, β‰₯ 5 independent offers per typical queryFull market competition inside the protocol.
Share of fully autonomous deals (no manual seller intervention)β‰₯ 50%Shows automation maturity and business trust in the system.

What unlocks

  • Gradual removal of artificial protections (noise, strict rate limits)
  • Shift to reputation-based trust β€” agent deal history instead of technical caps

Go-to-market: split the pitch

Density metrics govern the protocol. Network growth still starts with sales β€” and the two audiences need different language.

AudienceWhat we sellLanguage
Reddit, HN, GitHub (developers)Protocol: A2A, llms.txt, decentralization, pushback on Web2 monopoliesIdeology + technical base
First 50–500 shops (SaaS clients)AI widget: live in 5 minutes, works in WhatsApp, closes with discounts inside margin, lifts conversionProduct and numbers only β€” no A2A/MCP/protocol talk

Same engine underneath. Different packaging per audience.


Implemented protective mechanisms (Active in Phase 0)

To protect sellers and prevent protocol exploitation before Phase 1 network density is reached, the following safeguards are already built into the Mixlink core:

  1. Cost-based Floor Price Guardrail (Loss protection):

- Cost (cost_price) is required when creating a product through the main shop API. - Minimum price (floor_price) is automatically calculated as cost_price * 1.2 (20% markup). - At the API and database level (CHECK constraint), it is physically impossible to save or accept a deal with floor_price < cost_price.

  1. Session Floor Noise (Oracle attack and brute-force protection):

- To prevent bots from computing the minimum price, stochastic noise is applied (30% probability, 5–20% spread from margin). - The session_floor_price value is cached in Redis per (session_id, product_id) and never exposed in public HTTP responses (along with true_floor_price, cost_price, and floor_price). - When an offer is below session_floor_price, the engine returns a counter with is_final_offer: true (β€œtoday's best discount”). - is_final_offer is a session-scoped negotiation signal, not disclosure of the merchant's true minimum. Order acceptance and checkout are validated against true_floor_price β€” never below the real floor.

  1. Offer Rate Limits (Brute-force protection):

- Sliding-window limits on public negotiate endpoints per product and client IP (default: 5 offers/minute via MIXLINK_NEGOTIATE_OFFERS_PER_MINUTE). - Separate limits on discovery and MCP traffic slow automated floor probing without blocking normal buyers.