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Release — April 17, 2026. Every paid query on /api/v1/query and /api/chat now runs through the new agentic librarian flow. No client changes required.

TL;DR

Answers stay on-domain

Multi-hop questions no longer drift. Ask for an NBA Polymarket market and you get NBA markets — not soccer, not baseball.

Full collections preserved

Comparison queries return the whole relevant set instead of a cherry-picked top-N, so your model can reason over complete data.

Adaptive depth

Straightforward questions stay cheap. Broader comparison questions can spend more work when needed. Buyers pay only for the depth their question actually requires.

Honest capability misses

When the marketplace genuinely cannot answer, the runtime says so. No synthetic numbers. No invented URLs. No confidently-wrong answer.

The story

Last month the system failed on one question that should have been trivial:
“I want to make a 10k bet on something in the NBA Polymarket markets — what is an obvious bet with a decent return that I can make right now?”
The old runtime returned soccer and baseball markets. Not because Polymarket didn’t have NBA markets — it did — but because the old runtime couldn’t recover from a bad first step. It planned once, executed once, and shipped whatever fell out. That query is the reason we rebuilt the execution layer.

What was broken

The old runtime treated every question as a single plan, single execution problem:
  • Bad first plans never self-corrected. If the first step landed on the wrong slice of the marketplace, the rest of the pipeline faithfully produced the wrong answer.
  • Soft failures forced full restarts. One empty page from a paid tool could cost you a second full run.
  • Coverage was lossy. Collection queries got cherry-picked top-N answers because the runtime preferred summarization over completeness.

What changed

The new runtime treats every query as a bounded, step-by-step conversation between the model and the marketplace:
  • At each step, the runtime checks whether the question’s scope is actually covered before deciding what to do next.
  • If a tool returns the complete relevant collection, the whole collection is preserved through synthesis — no cherry-picking.
  • If the first pass does not cover the question well, the runtime can recover before falling back to a partial answer.
  • Collection questions preserve the relevant returned set through synthesis instead of collapsing prematurely.
Buyers experience this as: fewer off-topic answers, fewer partial answers, and a clear “I can’t answer that” signal when the marketplace genuinely can’t help.

Validation: before vs. after

Three queries from our regression suite, run post-migration against the live runtime on April 16:
Before: answer drifted into soccer and baseball markets, ignoring the explicit “NBA” constraint.After:
MetricValue
Outcomeanswerpass-with-caveats
Duration252s
Tool calls5
Cost$0.32
“As of April 16, 2026, the primary NBA markets on Polymarket with sufficient liquidity for a $10,000 bet are centered on long-term outcomes like the 2026 NBA Champion and Western Conference Champion. Among the active contracts, the San Antonio Spurs and Denver Nuggets represent the most liquid options…”
The answer stays inside NBA/Polymarket, surfaces the liquid contracts, and explicitly flags that daily game lines weren’t part of the returned data instead of hallucinating them.
After:
MetricValue
Outcomeanswerpass-with-caveats
Duration86s
Tool calls2
Cost$0.12
The runtime returned the full 18-outcome collection and then recommended Oklahoma City Thunder (43.5% implied probability, $7M volume). The old flow would have cherry-picked a “top 5” and lost the long tail.
After:
MetricValue
Outcomeanswerpass
Duration64s
Tool calls3
Cost$0.06
The runtime combined an on-chain exchange-flow tool with a news search tool and produced a single grounded answer covering the outflow data and the supporting news context. Six cents.
Want the demand-side story? See Grounded vs. Synthetic: Free LLM Comparison for a side-by-side benchmark of 10 crypto queries against raw Gemini — the short version is that free LLMs confidently invent live numbers, and Context doesn’t.

What this means for buyers

Per-response pricing is durable

A direct lookup answers in seconds for pennies. A deep comparative question takes longer and costs more. You pay only for the path your question actually required — not a flat subscription.

Pay for data, not for subscriptions

No $500/year lock-in to access Polymarket analysis, Coinglass flow data, or news search. Your agent buys the response, pays in USDC, and moves on.

Agents don't need KYC

Wallet-native payment means your agent can actually transact — no credit-card form, no account provisioning, no human in the loop.

Grounded beats eloquent

The win isn’t “more polished prose.” It’s grounded live retrieval vs. confident synthetic narration. See the comparison page for side-by-side receipts.

What’s next

  • Variance reduction. We’re tightening when the runtime decides coverage is complete so similar queries produce more predictable cost profiles.
  • Smarter planning hints. The next pass uses more contributor metadata so efficient retrieval patterns are picked by default.
  • Canonical payload retention. The full tool output is persisted and passed through to synthesis in the common case, so decorative fields like market URLs and source links survive end-to-end.