“given everything LLMs can do nowadays and long-horizon AI agents, give me 5 product/startup ideas i can build with all the available tech. criteria: must not have heavy competition already, ACV must be above $100k+, TAM must be pretty good, and the pain addressed must be large.”
Five ranked opportunities backed by 10 evidence rows — two per idea — drawn from 10 distinct sources (government, academic and industry; no source backs more than one row). ACV targets and serviceable-TAM ranges are directional bottom-up founder estimates, not published statistics; competition calls mean low direct competition for the narrow agentic wedge, not absence of adjacent incumbents.
Bubble area is the top of the plausible ACV range ($K); colour is agent-workflow fit (darker blue = better suited to a long-horizon agent). Pain, whitespace and fit are founder judgment scores on a 0–10 scale, not measured data. Hover a bubble for buyer, TAM and evidence.
| # | Documented pain | Quantified evidence | Economic buyer | Quality | Source |
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Method: 10 evidence rows, two per opportunity, from 10 distinct hosts and URLs (government, academic and industry/secondary sources, labelled per row), compiled 2025–2026. Pain, whitespace and agent-fit scores (0–10), ACV targets and serviceable-TAM ranges are directional founder estimates for ranking, not source-reported figures; competition judgments cover direct competition for the narrow agentic wedge only and need a dedicated competitor teardown before commitment. Evidence text lightly truncated for space; full sources linked per row.