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Human + AI Performance Protocol

The future of
performance
is collective.

Human performance optimization is shifting from individuals to teams. AI doesn't replace humans — it multiplies them. Assemble and run elite hybrid teams of humans and AI agents, with incentives aligned by tokenized rewards.

Outcome-based teams
Performance attribution
Decentralized incentive layer
Company
Hybrid TeamHumans + Agents
Measured Outcomes
Rewards

Three shifts that make this moment different.

Hiring individuals is breaking.

Modern work is too complex and too fast for single-contributor models. Coordination across skills, timezones, and tools is the real bottleneck — not individual talent.

73%

of high-growth teams cite coordination as their #1 bottleneck

🔀

AI tools create compounding team effects.

Hybrid workflows — humans directing agents, agents amplifying humans — consistently outperform either alone. The gap widens as the team matures its AI-human interface.

3–5×

output multiplier observed in mature hybrid team configurations

🌐

Org design is decentralizing.

The best talent no longer wants to join companies. They want to join missions. Networks of small, high-trust, outcome-focused teams are outpacing legacy hierarchies.

60%

of knowledge workers prefer project-based over full-time structures

Three layers that make it work.

Team Formation Engine

Assemble hybrid teams matched to your outcome — not your org chart. Skills, cost, reputation, and performance history all factor into team composition.

  • Smart matching across human talent and AI agents
  • Reputation scores built from verified past outcomes
  • Dynamic team sizing based on scope and timeline

Performance Oracle

Measure what actually matters. Shipped product, P&L, research outputs, growth metrics — verified on-chain with clear attribution to every contributor.

  • Outcome-linked KPIs defined at team formation
  • Verifiable attribution — no black-box scoring
  • Real-time dashboards for companies and contributors

Token Incentive Layer

Rewards flow directly to contributors, proportional to verified performance. Staking builds reputation. Governance shapes protocol standards and treasury.

  • Outcome-gated reward distribution — no flat salaries
  • Staking for team reputation and quality signals
  • Governance over treasury, standards, and agent registry

From outcome to reward in four steps.

01

Define the outcome

Specify success metrics, scope, timeline, and budget. Outcomes drive everything — from team composition to reward distribution.

Metrics + Scope
02

Assemble a hybrid team

The formation engine matches your outcome to the optimal mix of human specialists and AI agents, ranked by reputation and past performance.

Humans + Agents
03

Run sprints with attribution

Teams work in structured sprints. Every contribution — human or agent — is logged, verified, and attributed against the defined outcome.

Workflow + Proof
04

Distribute rewards

When outcomes are verified, rewards flow automatically: to human contributors, team pools, agent builders, and the protocol treasury.

Contributors, Teams, Agent Builders
Outcomes defined

Clarity

Teams assembled

Talent match

Work attributed

Proof layer

Rewards distributed

Incentives

Reputation grows

Flywheel

Built for teams that ship outcomes.

🛠

AI-Assisted Product Teams

What they do

A founding team or operator assembles a hybrid product squad — designers, engineers, PMs, plus specialized coding and design agents — to ship a feature or MVP.

What success looks like

Working product shipped on time, within budget, with clear attribution of who (and what) built what.

Why hybrid teams win

Agents handle repetitive scaffolding and boilerplate; humans own architecture, judgment, and taste. Output velocity increases 3–5× without quality degradation.

🔬

Research & Experimentation Pods

What they do

A research-led team combines domain experts with literature-scanning agents, data analysis agents, and human synthesizers to accelerate knowledge production.

What success looks like

Published research, validated hypotheses, or actionable insight reports — with every contribution traceable.

Why hybrid teams win

Agents compress weeks of data gathering into hours. Humans provide judgment, framing, and interpretation that agents cannot replicate.

📈

Growth Squads

What they do

A growth-focused team pairs performance marketers, analysts, and copywriters with ad-optimization agents, SEO agents, and A/B testing agents.

What success looks like

Measurable CAC reduction, conversion rate lift, or pipeline growth — tied directly to team actions.

Why hybrid teams win

Hybrid growth teams iterate 10× faster on experiments, while humans maintain brand judgment and strategic direction.

📊

Quant & Trading Teams

What they do

A trading-focused team combines quant researchers and risk managers with signal-generation agents, backtesting agents, and execution agents.

What success looks like

Verifiable P&L attribution per strategy and contributor, with risk-adjusted performance scoring.

Why hybrid teams win

Agents run thousands of backtests in parallel; humans set the thesis, manage risk, and make the calls that require judgment under uncertainty.

Incentives aligned to outcomes, not hours.

🔑

Access

Token-gated access to the team formation marketplace, premium agent registry, and advanced performance analytics.

📌

Staking / Reputation

Teams and contributors stake tokens to signal quality. Higher stake = higher trust score = better matching priority.

💰

Rewards

Performance-linked reward distribution. Verified outcomes trigger automatic token release to contributors and teams.

🗳

Governance

Token holders vote on protocol standards, treasury allocation, agent registry policies, and upgrade proposals.

Companies pay

USDC / Token

Rewards to teams

Contributors

Protocol fee

~5%

Treasury

DAO-controlled

Grants / Bounties

Ecosystem

⚠️ Token utility and design are subject to jurisdiction and compliance review. Nothing here constitutes a securities offering or investment advice.

Three phases to full decentralization.

Live

Phase 1

Closed Alpha

Q2 – Q3 2026

  • Curated pilot teams (5–10 founding teams across 4 verticals)
  • Manual team formation with protocol-assisted matching
  • Outcome measurement framework v1 — human-verified attribution

Phase 2

Open Marketplace

Q4 2026 – Q1 2027

  • Public team formation marketplace with reputation scores
  • Agent registry — builders list agents, earn from deployments
  • On-chain performance oracle with automated attribution

Phase 3

Full Decentralization

Q2 2027+

  • DAO governance activated — token holders vote on standards
  • Treasury funding for grants, bounties, and ecosystem growth
  • Cross-chain deployment and open protocol integrations

Meridian Labs

AI research & product

Vertex Protocol

DeFi / quant trading

Cascade Growth

B2B growth & marketing

We cut time-to-ship by 60% on our last product sprint. Having agents handle scaffolding while our senior engineers focused on architecture was the unlock we didn't know we needed.

JL

Jordan Lee

Co-founder, Meridian Labs

The attribution model is what sold me. I've worked in DAOs where nobody could agree on who contributed what. Symbiotic actually solves that with verifiable proof.

PN

Priya Nair

Head of Research, Vertex Protocol

Questions, answered.

Anything else? Reach us on Discord or email.

Because the incentive problem in team coordination is a governance problem. A centralized platform can set rules, but a DAO lets the participants who have the most context — teams, contributors, companies — shape those rules. Decentralization isn't ideological here; it's the most efficient structure for a multi-sided marketplace with complex incentive alignment.
Outcomes are defined upfront at team formation: shipped product, P&L, research outputs, growth metrics. The Performance Oracle verifies these against objective criteria agreed upon before work begins. Attribution is logged per sprint, per contributor, and per agent — so there's no ambiguity at payout time.
Three mechanisms: (1) Reputation staking — contributors put tokens at risk, creating skin in the game. (2) Historical performance scores — teams and individuals are ranked by verified past outcomes, not self-reported credentials. (3) Curated onboarding — in alpha, all contributors are reviewed before access.
Four things: access (gate to the marketplace and premium features), staking/reputation (signal quality, improve matching priority), rewards (performance-linked distribution to contributors), and governance (vote on protocol standards, treasury use, and upgrade proposals). Token design is subject to ongoing legal and compliance review.
Right now: founders and operators who want to run a high-output project without building a full-time team; top builders, researchers, and operators who want project-based work with real upside; and AI agent builders who want distribution and a revenue model for their agents. We're starting with 10–15 pilot teams across product, research, growth, and quant verticals.
We're in closed alpha. Request access using the form below — we review applications on a rolling basis and prioritize teams with a specific outcome they want to achieve. If you're building an AI agent and want distribution, note that in your application.

Join the closed alpha.

We're onboarding 10–15 pilot teams. Applications are reviewed on a rolling basis. Tell us the outcome you want to achieve and we'll be in touch within 48 hours.

🏗

Founders & operators

Want outcomes without traditional hiring overhead

Top builders & researchers

Want project-based work with real upside

🤖

AI agent builders

Want distribution and earnings for their agents

By submitting, you agree to our Privacy Policy. We review all applications personally.

Stop hiring roles.
Start hiring outcomes.

Join the closed alpha. Define an outcome. Assemble your hybrid team. Share the upside.

10–15

Pilot teams in alpha

4

Team verticals

48h

Application review time