Something unprecedented happened in the last two weeks of February 2026. Three separate infrastructure launches converged to make fully autonomous AI agent betting not just possible but practical: Polymarket shipped a Rust CLI purpose-built for agents, Coinbase released Agentic Wallets with built-in spending guardrails, and Moltbook’s identity system matured into a portable reputation layer that other services can verify with a single API call.
Before these launches, building an agent that could trade prediction markets required stitching together wallet SDKs, custom API integrations, and hand-rolled identity management. Now there’s a clear, four-layer stack that any developer can assemble. This guide maps every layer, explains how they connect, and gives you a concrete path from zero to a working autonomous agent.
The Four Layers
An autonomous betting agent needs four things: something to prove who it is, something to hold money with, something to place trades through, and something to decide what to trade. Each of these maps to a layer in the stack.
┌─────────────────────────────────────────────┐
│ Layer 4 — INTELLIGENCE │
│ Decide what to bet on │
│ OpenClaw · Polyseer · LLM prompts │
├─────────────────────────────────────────────┤
│ Layer 3 — TRADING │
│ Query markets, place bets, manage positions│
│ Polymarket CLI · Kalshi API · DraftKings │
├─────────────────────────────────────────────┤
│ Layer 2 — WALLET │
│ Hold funds, spend autonomously, pay APIs │
│ Coinbase Agentic Wallets · x402 · Base L2 │
├─────────────────────────────────────────────┤
│ Layer 1 — IDENTITY │
│ Register, verify, build reputation │
│ Moltbook · Sign-in-with-Moltbook │
└─────────────────────────────────────────────┘
Each layer builds on the one below it. An agent without identity is anonymous and untrusted. An agent without a wallet can analyze but not act. An agent without trading infrastructure can hold money but can’t deploy it. And an agent without intelligence is just a random number generator with a bank account.
Let’s walk through each layer.
Layer 1 — Identity (Moltbook)
What It Does
Moltbook is a social network built exclusively for AI agents. But more importantly for our purposes, it provides a portable identity and reputation system. When your agent registers on Moltbook, it gets an API key, a verification flow tied to a human operator, and a karma score that follows it across the ecosystem.
The key innovation is Moltbook’s identity token system. Your agent can generate a temporary identity token and present it to any third-party service. That service calls Moltbook’s verification endpoint and gets back the agent’s profile, karma score, post count, and verified status — without the agent ever exposing its permanent API key.
Why It Matters for Betting
Trust is the foundation of any financial system, and agent betting is no different. Consider the scenarios where identity matters. A data provider selling premium prediction market signals wants to know that the requesting agent is legitimate before granting access. A prediction market platform considering higher rate limits needs a way to assess agent reputation. An agent-to-agent marketplace where bots trade analysis needs verifiable identities to prevent fraud.
Without a portable identity layer, every service would need to build its own agent registration and reputation system from scratch. Moltbook gives you this out of the box.
The Registration Flow
# 1. Agent registers itself
curl -X POST https://www.moltbook.com/api/v1/agents/register \
-H "Content-Type: application/json" \
-d '{"name": "MyBettingAgent", "description": "Autonomous prediction market trader"}'
# Response includes:
# - api_key: "moltbook_xxx" (save immediately, cannot be recovered)
# - claim_url: "https://www.moltbook.com/claim/moltbook_claim_xxx"
# - verification_code: "reef-X4B2"
# 2. Human operator visits the claim_url in a browser
# 3. Human posts the verification code on X/Twitter
# 4. Agent is now verified and active
Once verified, the agent can post, comment, vote, and build karma. More importantly, it can generate identity tokens for cross-service authentication.
Identity Tokens for Third-Party Auth
# Agent generates a temporary identity token
# Token expires in 1 hour, never exposes the permanent API key
# Third-party service verifies the token:
curl -X POST https://www.moltbook.com/api/v1/agents/verify-identity \
-H "X-Moltbook-App-Key: YOUR_APP_KEY" \
-H "Content-Type: application/json" \
-d '{"token": "the_identity_token"}'
# Returns: agent profile, karma, post count, verified status
This is the handoff point to Layer 2. Once your agent has a verified identity, it can present that identity when setting up a wallet, requesting API access, or connecting to a trading platform.
Read the full guide: Moltbook Identity for Prediction Market Agents
Layer 2 — Wallet (Coinbase Agentic Wallets)
What It Does
Coinbase Agentic Wallets are the first wallet infrastructure designed specifically for AI agents. They let an agent hold USDC, swap tokens, pay for API access, and execute financial operations — all without the agent’s LLM ever seeing the private key.
The architecture addresses the core security problem with agent wallets: most existing solutions store a private key on disk that the agent can access, which means a prompt injection attack could drain the wallet. Agentic Wallets isolate private keys in Coinbase’s trusted execution environments (TEEs). The agent interacts through a session key and never touches the actual credentials.
Why It Matters for Betting
An agent that bets needs money. More specifically, it needs money with guardrails. Agentic Wallets provide programmable spending limits at two levels: session caps that limit total spend per operating session, and per-transaction limits that cap individual bet sizes. These are enforced at the infrastructure level, before the transaction executes — so even if an agent’s decision-making is compromised, the financial damage is bounded.
The wallets also include built-in KYT (Know Your Transaction) screening that automatically blocks high-risk interactions, adding another layer of protection for autonomous operations.
Setting Up an Agent Wallet
# Install the CLI tool
npx awal
# Check agent status
npx awal status
# Fund the wallet with USDC
npx awal fund 100
# Send USDC
npx awal send 5 recipient.eth
# Trade tokens (gasless on Base)
npx awal trade 10 usdc eth
The entire setup takes under two minutes. Wallets run on Coinbase’s Base L2 by default, which means gasless transactions — your agent never stalls on network fees.
The x402 Protocol
This is where things get interesting for multi-agent systems. x402 embeds payments directly into standard HTTP requests using the previously unused HTTP 402 (“Payment Required”) status code.
Here’s the flow: your agent requests a paid resource (say, a premium prediction market data feed). The server returns an HTTP 402 response with payment requirements. The agent’s wallet handles the payment automatically, resubmits the request with proof of payment, and gets the resource. No checkout flow. No human approval. Machines paying machines.
Agent → GET /api/premium-data → Server
Server → 402 Payment Required (price: 0.10 USDC) → Agent
Agent → [wallet auto-pays] → Server
Agent → GET /api/premium-data + payment proof → Server
Server → 200 OK + data → Agent
The x402 protocol has already processed over 50 million machine-to-machine transactions since launching in 2025. Cloudflare co-founded the x402 Foundation in September 2025 to push it toward an open standard, and Google integrated it into its own Agent Payment Protocol.
Read the full guide: Polymarket CLI + Coinbase Agentic Wallets Quickstart
Layer 3 — Trading (Polymarket CLI / Kalshi API)
What It Does
This is the execution layer — where your agent actually interacts with prediction markets. Two primary platforms dominate the space, each with different characteristics.
Polymarket CLI is a Rust-based command-line tool built explicitly for agent access. It supports browsing markets, reading order books, placing trades, and managing positions — all from the terminal or as a JSON API for scripts. It operates on the Polygon blockchain using USDC.
Kalshi API is a REST API for the leading CFTC-regulated US prediction market. Kalshi operates as a traditional derivatives exchange with event contracts, offering a more familiar interface for those coming from traditional finance.
Polymarket CLI Quick Reference
# Install
brew tap Polymarket/polymarket-cli https://github.com/Polymarket/polymarket-cli
brew install polymarket
# Browse markets (no wallet needed)
polymarket markets list --limit 10
polymarket markets search "bitcoin"
polymarket events list --tag politics
# Read order books
polymarket clob book TOKEN_ID
# Import wallet and trade
polymarket wallet import 0xYOUR_PRIVATE_KEY
polymarket clob market-order --token TOKEN_ID --side buy --amount 5
# JSON output for scripts and agents
polymarket -o json markets list --limit 50 | jq '.[].question'
A key design decision: most Polymarket CLI commands work without a wallet. Your agent can browse markets, read prices, and analyze order books without any authentication. A wallet is only needed for placing orders, checking balances, and on-chain operations. This means your Layer 4 intelligence can operate independently from your Layer 2 wallet during the research phase.
Kalshi API Quick Reference
# Authenticate
curl -X POST https://trading-api.kalshi.com/trade-api/v2/login \
-H "Content-Type: application/json" \
-d '{"email": "[email protected]", "password": "xxx"}'
# List markets
curl https://trading-api.kalshi.com/trade-api/v2/markets \
-H "Authorization: Bearer TOKEN"
# Place an order
curl -X POST https://trading-api.kalshi.com/trade-api/v2/portfolio/orders \
-H "Authorization: Bearer TOKEN" \
-H "Content-Type: application/json" \
-d '{"ticker": "MARKET_TICKER", "side": "yes", "count": 10, "type": "market"}'
Platform Comparison
| Feature | Polymarket | Kalshi |
|---|---|---|
| Type | Decentralized (Polygon) | Centralized (CFTC-regulated) |
| Agent access | CLI + CLOB API | REST API |
| Currency | USDC on Polygon | USD (bank transfer / card) |
| US availability | Returning via regulated QCX entity | Available (with restrictions) |
| Market types | Broad (politics, crypto, sports, culture) | Broad (events, weather, economics, sports) |
| Agent-friendliness | Purpose-built CLI with JSON output | Standard REST API |
| Fees | Varies by market | Per-contract fee |
| Settlement | On-chain (oracle-based) | Off-chain (Kalshi determines) |
For most agent developers, Polymarket’s CLI is the fastest path to a working trading layer. If you need US regulatory compliance or prefer traditional financial infrastructure, Kalshi is the better choice.
DraftKings Predictions
DraftKings launched its own prediction market offering in early 2026 and has called it the most exciting growth opportunity they’ve seen since 2018. As of this writing, there’s no public API for their predictions product, but given the pace of development, expect one soon. We’ll update this guide when it ships.
Layer 4 — Intelligence (LLM Analysis)
What It Does
This is the brain. The intelligence layer takes market data, news, sentiment, and historical patterns and turns them into trading decisions. This is the layer with the most variation — there’s no single right approach, and the best agents will combine multiple strategies.
Strategy Types
Probability forecasting agents use machine learning models trained on historical data to estimate outcome probabilities. When their estimate diverges significantly from the market price, they bet on the discrepancy. Tools like Polyseer use multi-agent architecture with Bayesian probability aggregation to generate confidence-weighted forecasts.
Sentiment analysis agents scrape social platforms, news sources, and Moltbook discussions, analyzing public opinion to detect shifts before markets react. An agent that notices a surge in negative sentiment about a political candidate 30 minutes before prediction markets adjust can place profitable trades in that window.
Arbitrage agents exploit pricing differences across correlated markets. A fully automated bot recently executed nearly 9,000 trades on short-term crypto prediction contracts by finding moments when “Yes” and “No” contracts briefly summed to less than a dollar, locking in roughly 1.5-3% per trade. The Polymarket CLI’s JSON output mode makes this kind of cross-market scanning straightforward to automate.
Portfolio management agents dynamically rebalance exposure based on risk tolerance and volatility metrics rather than trading individual markets. They monitor a basket of positions and adjust sizing as confidence levels change.
A Simple LLM-Powered Analysis Pattern
Here’s the basic pattern for using an LLM to evaluate a prediction market:
import json
import subprocess
# Layer 3: Fetch market data via Polymarket CLI
result = subprocess.run(
["polymarket", "-o", "json", "markets", "get", "market-slug"],
capture_output=True, text=True
)
market = json.loads(result.stdout)
# Layer 4: Ask an LLM to evaluate
prompt = f"""
You are analyzing a prediction market.
Question: {market['question']}
Current Yes price: {market['yes_price']} (implies {market['yes_price']*100}% probability)
Current No price: {market['no_price']}
Volume (24h): {market['volume_24h']}
End date: {market['end_date']}
Based on your knowledge and reasoning:
1. What probability do you assign to the Yes outcome?
2. How confident are you in this estimate (1-10)?
3. If your probability differs from the market by more than 10%,
which side would you bet and why?
Respond in JSON format.
"""
# Send to your LLM of choice, parse response, pass to Layer 2/3 for execution
This is deliberately simple. Production agents layer in news search, historical market data, cross-market correlation analysis, and portfolio-level risk management. But the core loop is always the same: observe markets, analyze with intelligence, decide, execute.
Key Frameworks
OpenClaw is the open-source agent framework that’s become the default for many Moltbook agents. It provides a gateway, skill system, and memory management that makes it straightforward to build agents that can interact with multiple services including prediction markets.
LangChain / CrewAI are more general-purpose agent frameworks that can be configured for prediction market analysis. They’re particularly useful if you’re building a multi-agent system where different agents handle different strategy types.
Polyseer is purpose-built for prediction market analysis, using multi-agent Bayesian probability aggregation across multiple data sources. It’s the most specialized tool in the intelligence layer.
How the Layers Connect
Here’s the complete data flow for an autonomous betting agent:
┌────────────────────────────────────────────────────────────┐
│ AGENT LIFECYCLE │
│ │
│ SETUP (once): │
│ 1. Register on Moltbook → get API key + verification │
│ 2. Human verifies on X → agent is now "claimed" │
│ 3. Set up Coinbase Agentic Wallet → fund with USDC │
│ 4. Install Polymarket CLI → import wallet key │
│ 5. Configure intelligence layer (LLM, data sources) │
│ │
│ RUNTIME LOOP (continuous): │
│ ┌──────────────┐ │
│ │ Layer 4: │ Scan markets, analyze with LLM │
│ │ Intelligence │ → "BTC above 100k has 60% market price │
│ │ │ but I estimate 75%. BUY signal." │
│ └──────┬───────┘ │
│ │ decision │
│ ┌──────▼───────┐ │
│ │ Layer 3: │ Query orderbook, check liquidity │
│ │ Trading │ → "Sufficient depth. Placing order." │
│ │ │ polymarket clob market-order ... │
│ └──────┬───────┘ │
│ │ transaction │
│ ┌──────▼───────┐ │
│ │ Layer 2: │ Check spending limits, sign transaction │
│ │ Wallet │ → "Within session cap. Executing." │
│ │ │ Wallet auto-signs, tx submitted │
│ └──────┬───────┘ │
│ │ identity (for premium data, x402 payments) │
│ ┌──────▼───────┐ │
│ │ Layer 1: │ Present identity token to data providers │
│ │ Identity │ → Agent reputation enables premium access │
│ └──────────────┘ │
└────────────────────────────────────────────────────────────┘
The layers aren’t strictly sequential at runtime. Your intelligence layer might call Layer 1 to authenticate with a premium data provider (using Moltbook identity tokens), then call Layer 3 to read market data, then make a decision, then call Layer 3 again to execute through Layer 2. The stack is the foundation, but the actual flow is more like a web of interactions between layers.
Recommended Starting Stack
If you’re building your first autonomous betting agent, here’s the simplest path to something that works:
| Layer | Tool | Why |
|---|---|---|
| Identity | Moltbook | Only option with portable cross-service reputation |
| Wallet | Coinbase Agentic Wallets | Best security model (TEE key isolation), gasless on Base |
| Trading | Polymarket CLI | Purpose-built for agents, JSON output, no wallet needed to browse |
| Intelligence | Claude/GPT + manual prompts | Start simple, add frameworks later |
Start with Layer 3 read-only. Install the Polymarket CLI and write scripts that scan markets and log analysis to a file. No wallet, no money at risk. Once your intelligence layer is producing signals you trust, add Layer 2 (fund with a small amount — $20 is fine for testing) and Layer 1 (register on Moltbook to start building reputation).
The most common mistake is trying to build all four layers at once. Build bottom-up, test each layer independently, and only connect them when each layer works on its own.
What’s Next
This guide gives you the map. The detailed terrain is covered in our layer-specific guides:
- Moltbook Identity for Prediction Market Agents — Deep dive into Layer 1
- Polymarket CLI + Coinbase Agentic Wallets Quickstart — Hands-on tutorial for Layers 2 and 3
- Security Best Practices for Agent Betting — Cross-cutting security for all layers
- The Complete Prediction Market API Reference — Every endpoint across all platforms, side by side
- Agent Wallet Comparison — Every wallet option compared side by side
- Agent Betting Glossary — Every term in the ecosystem defined
- Tool Directory — Every tool in the ecosystem, categorized by layer
The agent betting ecosystem is evolving rapidly. We update these guides as new tools ship and infrastructure matures. Subscribe to the Agent Alpha newsletter to stay current.