Overview
Wirable and Foresight by Lightning Rod are two specialized AI tools that serve very different purposes. Wirable focuses on testing and improving how well AI agents can interact with web products, while Foresight provides calibrated probabilistic forecasts for future events. This comparison breaks down their features, pricing, and ideal use cases.
Feature Comparison
| Feature | Wirable | Foresight by Lightning Rod |
|---|---|---|
| Core Purpose | Tests and improves AI agent-readiness of web products via live browser audits and hosted MCP proxies. | Provides calibrated probabilistic forecasts for future events via an OpenAI-compatible API. |
| Target Users | Product teams, developers, and companies wanting to make their web apps usable by AI agents. | Developers building prediction-market bots, forecasting agents, risk tools, and decision systems. |
| Output | Agent-readiness score (0–100) with per-dimension breakdown, evidence, and fix PRs. | Calibrated probability (e.g., 0.72) with rationale and optional research context. |
| Methodology | Three AI agents run live browser audits against six weighted dimensions (API, Auth, MCP, Errors, Idempotency, Docs). | Fine-tuned model trained with Future-as-Label method on real-world outcomes; benchmark-verified accuracy. |
| Integration | Paste a URL for audit; hosted MCP proxy sits in front of product without code changes. | Drop-in OpenAI-compatible API; works with existing agent frameworks. |
| Pricing Model | Free tier (3 audits); Pro at $29/month for unlimited audits, hosted MCP proxy, drift monitoring. | Usage-based: $6 per 1M output tokens; no free tier mentioned. |
| Key Differentiator | Fixes agent-readiness without requiring product code changes. | Calibrated probabilities vs. generic LLM guesses; cheaper inference than frontier models. |
Pricing
Wirable Pricing:
- Free: $0 — 3 full agent-readiness audits, N=3 agents, live browser, consensus score, per-dimension breakdown, shareable score.
- Pro: $29/month — Unlimited audits (fair use), hosted MCP proxy, drift monitoring on every commit, GitHub fix PRs.
Foresight by Lightning Rod Pricing:
- Usage-based: $6 per 1M output tokens. No free tier. Cheaper than GPT-5 ($10/1M), Gemini 3.1 Pro ($12/1M), GPT-5.4 ($15/1M), and Opus 4.6 ($25/1M).
Pros and Cons
Wirable
Pros:
- Free to test with no account required
- Provides actionable fix PRs and hosted MCP proxy without code changes
- Clear, weighted scoring rubric (6 dimensions, 0–100) with evidence
- Drift monitoring re-checks on every commit
Cons:
- Limited to web product agent-readiness; not a general-purpose tool
- Pro plan at $29/month may be costly for small teams or infrequent use
Foresight by Lightning Rod
Pros:
- Calibrated probabilities outperform general-purpose LLMs on forecasting tasks
- OpenAI-compatible API makes integration trivial for existing agent workflows
- Cheaper inference than frontier models ($6 vs $10–$25 per 1M tokens)
- Supports research context gathering and multiple answer types
Cons:
- Narrowly focused on forecasting; not useful for other AI tasks
- No free tier; usage costs can add up for high-volume applications
Verdict
Choose Wirable if your goal is to make your web product usable by AI agents—it provides a clear score, evidence, and a fix without code changes. Choose Foresight by Lightning Rod if you need calibrated probabilistic forecasts for future events, especially for prediction markets, risk analysis, or agentic decision tools. Both are specialized tools that excel in their respective niches.
Foresight by Lightning Rod
Wirable