{ "artifact": "Product Hunt W20 narrative claim bank", "created_at": "2026-05-18", "status": "draft_for_blog_and_x", "source_packet": "raw/projects/find-similar-startups/distribution/producthunt/weekly-2026-W20-through-2026-05-17", "source_files": { "packet": "raw/projects/find-similar-startups/distribution/producthunt/weekly-2026-W20-through-2026-05-17", "weekly_jsonl": "raw/projects/find-similar-startups/distribution/producthunt/weekly-2026-W20-through-2026-05-17/producthunt/normalized/weekly/2026-W20.jsonl", "run_summary": "raw/projects/find-similar-startups/distribution/producthunt/weekly-2026-W20-through-2026-05-17/run-summary.json", "market_overview": "raw/projects/find-similar-startups/distribution/producthunt/weekly-2026-W20-through-2026-05-17/analysis/weekly-market-distribution/weekly-attention-overview.csv", "market_claim_ledger": "raw/projects/find-similar-startups/distribution/producthunt/weekly-2026-W20-through-2026-05-17/analysis/weekly-market-distribution/weekly-market-claim-ledger.csv", "quintiles": "raw/projects/find-similar-startups/distribution/producthunt/weekly-2026-W20-through-2026-05-17/analysis/weekly-market-distribution/weekly-attention-quintiles.csv", "percentiles": "raw/projects/find-similar-startups/distribution/producthunt/weekly-2026-W20-through-2026-05-17/analysis/weekly-market-distribution/weekly-attention-percentile-buckets.csv", "thresholds": "raw/projects/find-similar-startups/distribution/producthunt/weekly-2026-W20-through-2026-05-17/analysis/weekly-market-distribution/weekly-attention-thresholds.csv", "cluster_summary": "raw/projects/find-similar-startups/distribution/producthunt/weekly-2026-W20-through-2026-05-17/analysis/weekly-cluster-summary.csv", "semantic_clusters": "raw/projects/find-similar-startups/distribution/producthunt/weekly-2026-W20-through-2026-05-17/analysis/semantic-startup-types/semantic-cluster-summary.csv", "semantic_tags": "raw/projects/find-similar-startups/distribution/producthunt/weekly-2026-W20-through-2026-05-17/analysis/semantic-startup-types/semantic-tag-summary.csv", "daily_briefs": "raw/projects/find-similar-startups/distribution/producthunt/weekly-2026-W20-through-2026-05-17/analysis/daily-content-briefs.csv", "top_launches": "raw/projects/find-similar-startups/distribution/producthunt/weekly-2026-W20-through-2026-05-17/analysis/weekly-top-launches.csv", "voice_scan": "raw/projects/find-similar-startups/distribution/producthunt/weekly-2026-W20-through-2026-05-17/analysis/voice-api-market-scan/voice-api-market-scan.md" }, "claim_policy": { "hard_claims": "Use exact numbers from the source files and include caveats.", "interpretive_claims": "Frame as interpretation, market read, or editorial stance, not as measured buyer intent.", "named_examples": "Spot-check named products before public publication or tagging.", "outreach": "Do not tag founders/companies until X handles are verified manually." }, "blog_positioning": { "working_title": "I analyzed 3,826 Product Hunt launches. The market is trying to make work disappear.", "alternate_titles": [ "3,826 Product Hunt launches and one obvious market emotion", "Product Hunt W20: builders are converging on one promise", "The startup market is not exploding into novelty. It is compressing work." ], "core_take": "Use the numbers as proof of a collective emotion: founders are building products that promise to remove the painful part of work without removing the outcome.", "target_reader": "Founders, indie hackers, AI builders, product marketers, and investors who use Product Hunt as a signal surface.", "primary_cta": "Use FSS to understand the competitive landscape before building, launching, or repositioning." }, "strategic_idea_ranking": [ { "id": "W20-N01", "rank": 1, "strategic_score_10": 9.6, "claim_type": "market_psychology", "claim": "The strongest public story is not that Product Hunt had many launches; it is that thousands of launches repeated the same emotional promise: make work disappear.", "tweetable_claim": "I analyzed 3,826 Product Hunt launches. The striking part was not how many new ideas appeared. It was how many products were chasing the same promise: make work disappear.", "why_it_sells": "It turns a spreadsheet into a cultural read founders can feel. It is broader than AI agents but still grounded in the data.", "data_support": [ "3,826 unique launches in one week", "AI agents and automation captured 21.1% of weighted traction from 8.3% of launches", "Semantic ai_agent tag captured 31.34% of weighted traction from 9.04% of launches", "Top semantic examples are workflow-removal products: HasData, Loova Agents, Genpire, Tendem by Toloka, Open Vibe" ], "evidence_files": [ "market_overview", "cluster_summary", "semantic_tags", "semantic_clusters" ], "confidence": "medium_high", "confidence_notes": "The numerical pattern is high-confidence. The emotional interpretation is editorial, so it should be framed as an interpretation rather than a measured survey of founder intent.", "caveat": "Product Hunt launch copy reveals how builders position products, not direct buyer psychology.", "blog_role": "main thesis", "video_role": "opening claim", "outreach_role": "primary tweet hook" }, { "id": "W20-N02", "rank": 2, "strategic_score_10": 9.2, "claim_type": "attention_market", "claim": "Product Hunt is less useful as a scoreboard than as a weekly market sensor for where attention is concentrating.", "tweetable_claim": "Product Hunt is not a verdict machine. It is a weekly sensor for where builder attention is concentrating.", "why_it_sells": "This supports FSS directly: founders need market context before they build, launch, or reposition.", "data_support": [ "Median launch: 1 vote, 1 comment, 3 weighted traction", "Top attention quintile captured 84.1% of weighted traction", "Only 8.8% crossed more than 10 votes" ], "evidence_files": [ "market_overview", "quintiles", "thresholds" ], "confidence": "high", "confidence_notes": "Supported by direct distribution metrics. The sensor framing is editorial but conservative.", "caveat": "Votes and comments are attention proxies, not revenue or product quality.", "blog_role": "framing section", "video_role": "scene 2", "outreach_role": "reply after the main tweet" }, { "id": "W20-N03", "rank": 3, "strategic_score_10": 8.9, "claim_type": "founder_lesson", "claim": "A quiet launch is not automatically a failed product; in W20, quiet was the default state.", "tweetable_claim": "In this dataset, quiet was the default. 91.2% of launches had 10 or fewer votes.", "why_it_sells": "Founder-positive, emotionally useful, and easy to distribute. It reduces shame while making the case for positioning and landscape work.", "data_support": [ "91.2% of launches had 10 or fewer votes", "57.1% had one or fewer votes", "Median weighted traction was 3" ], "evidence_files": [ "thresholds", "market_overview" ], "confidence": "high", "confidence_notes": "Directly supported by threshold distribution.", "caveat": "Low Product Hunt attention does not mean the product has no users, revenue, or future.", "blog_role": "founder empathy section", "video_role": "scene 3", "outreach_role": "standalone reply with founder empathy" }, { "id": "W20-N04", "rank": 4, "strategic_score_10": 8.5, "claim_type": "category_contrast", "claim": "The most crowded lane was not the top attention lane: design/media had the most launches, while AI agents and automation captured the most weighted traction.", "tweetable_claim": "The most crowded lane was design/media. The attention lane was AI agents.", "why_it_sells": "A clean chartable contrast. It gives the post analytical substance after the emotional hook.", "data_support": [ "Design, media, and content creation: 559 launches, 11.5% traction share, 0.79x efficiency", "AI agents and automation: 317 launches, 21.1% traction share, 2.54x efficiency" ], "evidence_files": [ "cluster_summary" ], "confidence": "medium_high", "confidence_notes": "Metrics are precise; category assignment is inferred from launch text.", "caveat": "Clusters are heuristic, not official Product Hunt taxonomy.", "blog_role": "data contrast section", "video_role": "scene 4", "outreach_role": "chart reply" }, { "id": "W20-N05", "rank": 5, "strategic_score_10": 8.1, "claim_type": "semantic_pattern", "claim": "The strongest semantic cluster combined AI agents and developer tools, suggesting attention moved toward tools that let builders delegate operational or technical work.", "tweetable_claim": "The top semantic cluster was not just \"AI\". It was AI agents plus developer tools.", "why_it_sells": "More specific than generic AI hype. It speaks to technical founders and explains why agent/devtool products over-indexed.", "data_support": [ "AI agents and assistants / developer tools: 185 launches, 18.0% weighted traction share, 3.72x efficiency", "developer_tools semantic tag: 664 launches, 30.18% weighted traction share, 1.74x efficiency", "ai_agent semantic tag: 346 launches, 31.34% weighted traction share, 3.47x efficiency" ], "evidence_files": [ "semantic_clusters", "semantic_tags" ], "confidence": "medium_high", "confidence_notes": "Strong quantitative pattern; semantic classifier is deterministic but approximate.", "caveat": "Semantic tags are multi-label; one product can count in multiple tags.", "blog_role": "deeper analysis section", "video_role": "optional detail reply, not main video", "outreach_role": "reply for devtools/agent audience" }, { "id": "W20-N06", "rank": 6, "strategic_score_10": 7.7, "claim_type": "voice_market", "claim": "Voice was visible but not the main W20 story: broad voice/audio appeared often, but core voice-to-action agents were still a small subset.", "tweetable_claim": "Voice was not absent. It was early: 439 broad voice/audio candidates, but only 22 core voice-action agent candidates.", "why_it_sells": "Useful follow-up because it connects to OpenAI voice API timing without forcing the whole article into a narrower story.", "data_support": [ "439 broad voice/audio candidates", "22 core voice-action candidates", "Core voice-action candidates represented 5.0% of the voice/audio candidate set by count and 6.0% by voice-scan traction" ], "evidence_files": [ "voice_scan" ], "confidence": "medium", "confidence_notes": "The broad/core split is heuristic and should be used as a follow-up, not the main claim.", "caveat": "Voice classifier uses launch text and may miss products that do not describe voice clearly.", "blog_role": "sidebar or follow-up, not main spine", "video_role": "possible reply video later", "outreach_role": "reply under OpenAI/voice conversations after source-checking" } ], "hard_claims_from_ledger": [ { "claim_id": "W20-MD-C01", "claim_type": "scope", "claim": "The W20 packet contains 3826 unique launches from 2026-05-11 through 2026-05-17.", "evidence": "votes=38134; comments=6621; traction=51376", "supporting_data": "weekly-attention-overview.csv; producthunt/normalized/weekly/2026-W20.jsonl", "confidence": "high", "caveat": "Counts depend on the Product Hunt API day window and one-launch-per-id normalization." }, { "claim_id": "W20-MD-C02", "claim_type": "winner", "claim": "Spellar 3.0 was the weekly winner by both weighted traction and raw votes.", "evidence": "543 votes; 115 comments; score 773", "supporting_data": "weekly-attention-overview.csv; weekly-top-launches.csv", "confidence": "high", "caveat": "Weighted score is votes + 2*comments, not official Product Hunt ranking." }, { "claim_id": "W20-MD-C03", "claim_type": "median", "claim": "The median launch had 1 vote, 1 comment, and 3 weighted traction.", "evidence": "p75 traction=5; p90=12; p95=75; p99=209.75", "supporting_data": "weekly-attention-overview.csv", "confidence": "high", "caveat": "Median describes the normalized Product Hunt packet, not all startups on the internet." }, { "claim_id": "W20-MD-C04", "claim_type": "attention_concentration", "claim": "The top 1% captured 31% of weighted traction; the top 5% captured 63.5%.", "evidence": "top_1pct=39 launches; top_5pct=192 launches", "supporting_data": "weekly-attention-percentile-buckets.csv", "confidence": "high", "caveat": "Attention is measured as votes + 2*comments." }, { "claim_id": "W20-MD-C05", "claim_type": "quintiles", "claim": "The top attention quintile captured 84.1% of weighted traction; the bottom quintile captured 1.6%.", "evidence": "Q1 launches=765; Q5 launches=766", "supporting_data": "weekly-attention-quintiles.csv", "confidence": "high", "caveat": "Quintiles are ranked by weighted traction, not by official Product Hunt position." }, { "claim_id": "W20-MD-C06", "claim_type": "low_attention_floor", "claim": "91.2% of launches had 10 or fewer votes.", "evidence": "3488/3826 launches", "supporting_data": "weekly-attention-thresholds.csv", "confidence": "high", "caveat": "A low Product Hunt vote count is not proof of a bad product." }, { "claim_id": "W20-MD-C07", "claim_type": "cluster_contrast", "claim": "The most crowded lane was Design, media, and content creation, but the top attention lane was AI agents and automation.", "evidence": "Design, media, and content creation: 559 launches, 11.5% traction; AI agents and automation: 317 launches, 21.1% traction", "supporting_data": "weekly-cluster-catalog.csv; weekly-cluster-summary.csv", "confidence": "medium_high", "caveat": "Clusters are heuristic classifications from launch text." }, { "claim_id": "W20-MD-C08", "claim_type": "cluster_efficiency", "claim": "AI agents and automation was the highest-efficiency sizeable lane at 2.54x.", "evidence": "317 launches; 21.1% traction share; 8.3% launch share", "supporting_data": "weekly-cluster-catalog.csv; weekly-cluster-summary.csv", "confidence": "medium_high", "caveat": "Efficiency compares traction share to launch share, not business value." }, { "claim_id": "W20-MD-C09", "claim_type": "daily_rhythm", "claim": "2026-05-12 had the most launches, while 2026-05-14 had the most weighted attention.", "evidence": "2026-05-12: 761 launches; 2026-05-14: 10828 traction", "supporting_data": "weekly-daily-attention-distribution.csv; run-summary.json", "confidence": "high", "caveat": "Daily counts depend on the API date window and deduping by launch ID." }, { "claim_id": "W20-MD-C10", "claim_type": "cataloging", "claim": "For content, catalog each launch by cluster, attention band, and content role rather than only by category.", "evidence": "cluster_role + quintile + threshold buckets expose crowded lanes, attention winners, and long-tail patterns.", "supporting_data": "weekly-cluster-catalog.csv; weekly-attention-quintiles.csv; weekly-attention-thresholds.csv", "confidence": "medium", "caveat": "This is an editorial operating model built on the data, not a direct Product Hunt field." } ], "data_snapshot": { "overview": { "total_launches": { "value": "3826", "note": "Unique normalized Product Hunt launches, 2026-05-11 through 2026-05-17." }, "total_votes": { "value": "38134", "note": "Sum of votes across launches." }, "total_comments": { "value": "6621", "note": "Sum of comments across launches." }, "total_traction_score": { "value": "51376", "note": "votes + 2*comments." }, "median_votes": { "value": "1", "note": "Typical launch vote count." }, "median_comments": { "value": "1", "note": "Typical launch comment count." }, "median_traction": { "value": "3", "note": "Typical weighted attention." }, "p75_traction": { "value": "5", "note": "75th percentile weighted attention." }, "p90_traction": { "value": "12", "note": "90th percentile weighted attention." }, "p95_traction": { "value": "75", "note": "95th percentile weighted attention." }, "p99_traction": { "value": "209.75", "note": "99th percentile weighted attention." }, "weekly_weighted_winner": { "value": "Spellar 3.0 (543v/115c; score 773)", "note": "Highest weighted attention score." }, "weekly_vote_winner": { "value": "Spellar 3.0 (543v/115c; score 773)", "note": "Highest raw votes." }, "weekly_comment_winner": { "value": "Naptick AI (495v/117c; score 729)", "note": "Highest comments." } }, "attention_quintiles": [ { "quintile": "Q1", "attention_rank_band": "top 20%", "rank_range": "1-765", "launches": "765", "min_traction": "5", "max_traction": "773", "votes": "35075", "vote_share_pct": "92", "comments": "4078", "comment_share_pct": "61.6", "traction_score": "43231", "traction_share_pct": "84.1", "avg_traction": "56.5", "median_traction": "12", "top_examples": "Spellar 3.0 (543v/115c; score 773); Naptick AI (495v/117c; score 729); Kelviq (508v/93c; score 694); Memoket Gem (477v/105c; score 687); articuler.ai (505v/87c; score 679)" }, { "quintile": "Q2", "attention_rank_band": "21-40%", "rank_range": "766-1530", "launches": "765", "min_traction": "4", "max_traction": "5", "votes": "1679", "vote_share_pct": "4.4", "comments": "787", "comment_share_pct": "11.9", "traction_score": "3253", "traction_share_pct": "6.3", "avg_traction": "4.3", "median_traction": "4", "top_examples": "FreeViralKit (3v/1c; score 5); WA PingoHub (3v/1c; score 5); Basket List (3v/1c; score 5); Hadoop Windows Manager (3v/1c; score 5); CardPeek (3v/1c; score 5)" }, { "quintile": "Q3", "attention_rank_band": "41-60%", "rank_range": "1531-2295", "launches": "765", "min_traction": "3", "max_traction": "4", "votes": "840", "vote_share_pct": "2.2", "comments": "781", "comment_share_pct": "11.8", "traction_score": "2402", "traction_share_pct": "4.7", "avg_traction": "3.1", "median_traction": "3", "top_examples": "Pixarc (2v/1c; score 4); BibleEasy.app (2v/1c; score 4); World Opex (2v/1c; score 4); Riziva (2v/1c; score 4); Drinkdln (2v/1c; score 4)" }, { "quintile": "Q4", "attention_rank_band": "61-80%", "rank_range": "2296-3060", "launches": "765", "min_traction": "2", "max_traction": "3", "votes": "251", "vote_share_pct": "0.7", "comments": "712", "comment_share_pct": "10.8", "traction_score": "1675", "traction_share_pct": "3.3", "avg_traction": "2.2", "median_traction": "2", "top_examples": "QSME.io (1v/1c; score 3); ShipThatCode (1v/1c; score 3); NoBad (1v/1c; score 3); ConverterBoss (1v/1c; score 3); Orbit (1v/1c; score 3)" }, { "quintile": "Q5", "attention_rank_band": "bottom 20%", "rank_range": "3061-3826", "launches": "766", "min_traction": "0", "max_traction": "2", "votes": "289", "vote_share_pct": "0.8", "comments": "263", "comment_share_pct": "4", "traction_score": "815", "traction_share_pct": "1.6", "avg_traction": "1.1", "median_traction": "1", "top_examples": "TUMB (0v/1c; score 2); RunCabin (0v/1c; score 2); AR-DENT Management (0v/1c; score 2); PermitPal: AI Local Permit Assistant (0v/1c; score 2); FaiirPe (0v/1c; score 2)" } ], "attention_percentiles": [ { "bucket": "top_1pct", "launches": "39", "launch_share_pct": "1", "votes": "11883", "vote_share_pct": "31.2", "comments": "2026", "comment_share_pct": "30.6", "traction_score": "15935", "traction_share_pct": "31", "min_traction_to_enter": "210", "top_examples": "Spellar 3.0 (543v/115c; score 773); Naptick AI (495v/117c; score 729); Kelviq (508v/93c; score 694); Memoket Gem (477v/105c; score 687); articuler.ai (505v/87c; score 679)" }, { "bucket": "top_5pct", "launches": "192", "launch_share_pct": "5", "votes": "26391", "vote_share_pct": "69.2", "comments": "3111", "comment_share_pct": "47", "traction_score": "32613", "traction_share_pct": "63.5", "min_traction_to_enter": "75", "top_examples": "Spellar 3.0 (543v/115c; score 773); Naptick AI (495v/117c; score 729); Kelviq (508v/93c; score 694); Memoket Gem (477v/105c; score 687); articuler.ai (505v/87c; score 679)" }, { "bucket": "top_10pct", "launches": "383", "launch_share_pct": "10", "votes": "33443", "vote_share_pct": "87.7", "comments": "3565", "comment_share_pct": "53.8", "traction_score": "40573", "traction_share_pct": "79", "min_traction_to_enter": "12", "top_examples": "Spellar 3.0 (543v/115c; score 773); Naptick AI (495v/117c; score 729); Kelviq (508v/93c; score 694); Memoket Gem (477v/105c; score 687); articuler.ai (505v/87c; score 679)" }, { "bucket": "top_20pct", "launches": "766", "launch_share_pct": "20", "votes": "35078", "vote_share_pct": "92", "comments": "4079", "comment_share_pct": "61.6", "traction_score": "43236", "traction_share_pct": "84.2", "min_traction_to_enter": "5", "top_examples": "Spellar 3.0 (543v/115c; score 773); Naptick AI (495v/117c; score 729); Kelviq (508v/93c; score 694); Memoket Gem (477v/105c; score 687); articuler.ai (505v/87c; score 679)" }, { "bucket": "top_50pct", "launches": "1913", "launch_share_pct": "50", "votes": "37212", "vote_share_pct": "97.6", "comments": "5264", "comment_share_pct": "79.5", "traction_score": "47740", "traction_share_pct": "92.9", "min_traction_to_enter": "3", "top_examples": "Spellar 3.0 (543v/115c; score 773); Naptick AI (495v/117c; score 729); Kelviq (508v/93c; score 694); Memoket Gem (477v/105c; score 687); articuler.ai (505v/87c; score 679)" } ], "attention_thresholds": [ { "bucket": "zero_votes", "launches": "1069", "launch_share_pct": "27.9", "votes": "0", "vote_share_pct": "0", "comments": "883", "comment_share_pct": "13.3", "traction_score": "1766", "traction_share_pct": "3.4" }, { "bucket": "one_or_fewer_votes", "launches": "2185", "launch_share_pct": "57.1", "votes": "1116", "vote_share_pct": "2.9", "comments": "1746", "comment_share_pct": "26.4", "traction_score": "4608", "traction_share_pct": "9" }, { "bucket": "five_or_fewer_votes", "launches": "3368", "launch_share_pct": "88", "votes": "4146", "vote_share_pct": "10.9", "comments": "2973", "comment_share_pct": "44.9", "traction_score": "10092", "traction_share_pct": "19.6" }, { "bucket": "ten_or_fewer_votes", "launches": "3488", "launch_share_pct": "91.2", "votes": "5076", "vote_share_pct": "13.3", "comments": "3194", "comment_share_pct": "48.2", "traction_score": "11464", "traction_share_pct": "22.3" }, { "bucket": "more_than_10_votes", "launches": "338", "launch_share_pct": "8.8", "votes": "33058", "vote_share_pct": "86.7", "comments": "3427", "comment_share_pct": "51.8", "traction_score": "39912", "traction_share_pct": "77.7" }, { "bucket": "at_least_25_votes", "launches": "285", "launch_share_pct": "7.4", "votes": "32291", "vote_share_pct": "84.7", "comments": "3256", "comment_share_pct": "49.2", "traction_score": "38803", "traction_share_pct": "75.5" }, { "bucket": "at_least_50_votes", "launches": "278", "launch_share_pct": "7.3", "votes": "32066", "vote_share_pct": "84.1", "comments": "3187", "comment_share_pct": "48.1", "traction_score": "38440", "traction_share_pct": "74.8" }, { "bucket": "at_least_100_votes", "launches": "82", "launch_share_pct": "2.1", "votes": "17504", "vote_share_pct": "45.9", "comments": "2521", "comment_share_pct": "38.1", "traction_score": "22546", "traction_share_pct": "43.9" }, { "bucket": "at_least_250_votes", "launches": "24", "launch_share_pct": "0.6", "votes": "8989", "vote_share_pct": "23.6", "comments": "1516", "comment_share_pct": "22.9", "traction_score": "12021", "traction_share_pct": "23.4" }, { "bucket": "at_least_500_votes", "launches": "4", "launch_share_pct": "0.1", "votes": "2095", "vote_share_pct": "5.5", "comments": "362", "comment_share_pct": "5.5", "traction_score": "2819", "traction_share_pct": "5.5" } ], "top_heuristic_clusters": [ { "cluster": "AI agents and automation", "launches": "317", "launch_share_pct": "8.3", "traction_score": "10843", "traction_share_pct": "21.1", "attention_efficiency": "2.54", "top_examples": "HasData (423v/111c); Genpire (395v/38c); Fere AI (364v/47c); Vivago Video Agent (342v/42c); Tendem by Toloka (265v/72c)" }, { "cluster": "Developer infrastructure and app-building", "launches": "406", "launch_share_pct": "10.6", "traction_score": "7506", "traction_share_pct": "14.6", "attention_efficiency": "1.38", "top_examples": "OpenHuman (539v/67c); ClawSecure (302v/45c); Frontdesk AI (253v/31c); Hyperswitch Prism (238v/20c); Warp Open-Source (216v/30c)" }, { "cluster": "Operator and vertical workflows", "launches": "488", "launch_share_pct": "12.8", "traction_score": "7367", "traction_share_pct": "14.3", "attention_efficiency": "1.12", "top_examples": "Spellar 3.0 (543v/115c); Memoket Gem (477v/105c); OpenJobs AI (415v/98c); Liminary (150v/48c); Googlebook (211v/8c)" }, { "cluster": "Design, media, and content creation", "launches": "559", "launch_share_pct": "14.6", "traction_score": "5907", "traction_share_pct": "11.5", "attention_efficiency": "0.79", "top_examples": "Loova Agents (354v/78c); SUN-to-Spotify (298v/27c); MiroMiro v2 (181v/16c); Snapseed 4.0 (167v/3c); Instants by Instagram (151v/6c)" }, { "cluster": "Data, analytics, and research", "launches": "420", "launch_share_pct": "11", "traction_score": "5082", "traction_share_pct": "9.9", "attention_efficiency": "0.9", "top_examples": "PHBench (376v/44c); Jotform Claude App (252v/12c); mia (145v/28c); Hoogly.ai (107v/12c); M5Stack PaperColor (117v/5c)" }, { "cluster": "GTM, SEO, sales, and launch intelligence", "launches": "396", "launch_share_pct": "10.4", "traction_score": "4639", "traction_share_pct": "9", "attention_efficiency": "0.87", "top_examples": "articuler.ai (505v/87c); Lensmor (291v/60c); Blaze 2.0 (237v/57c); HeyNews (133v/26c); OptimizeGEO.ai (111v/12c)" }, { "cluster": "Consumer, education, games, and lifestyle", "launches": "519", "launch_share_pct": "13.6", "traction_score": "3738", "traction_share_pct": "7.3", "attention_efficiency": "0.54", "top_examples": "Naptick AI (495v/117c); ChatGPT for Google Sheets (122v/4c); Habitvs (101v/8c); Gluten App (77v/15c); zubhai (79v/6c)" }, { "cluster": "Commerce, finance, and business ops", "launches": "298", "launch_share_pct": "7.8", "traction_score": "2705", "traction_share_pct": "5.3", "attention_efficiency": "0.68", "top_examples": "Kelviq (508v/93c); ChatGPT for Personal Finance (148v/10c); Belli (92v/1c); xyOps (75v/3c); Rhuna (77v/1c)" }, { "cluster": "Security, compliance, and trust", "launches": "258", "launch_share_pct": "6.7", "traction_score": "2508", "traction_share_pct": "4.9", "attention_efficiency": "0.73", "top_examples": "Graphbit PRFlow (384v/99c); knooth (98v/3c); DoDocs inc (81v/9c); PitchDrop.ai (88v/5c); c15t 2.0 (80v/3c)" }, { "cluster": "Other or unclear", "launches": "165", "launch_share_pct": "4.3", "traction_score": "1081", "traction_share_pct": "2.1", "attention_efficiency": "0.49", "top_examples": "Raybeam (190v/5c); Lumox (75v/6c); Termux Lite (75v/1c); Oumua Inc (74v/0c); Tellme (73v/0c)" } ], "top_semantic_clusters": [ { "semantic_cluster_id": "SC19", "suggested_label": "AI agents and assistants / developer tools", "launches": "185", "launch_share_pct": "4.84", "traction_score": "9250", "traction_share_pct": "18.0", "attention_efficiency": "3.72", "top_examples": "HasData (423v/111c); Loova Agents (354v/78c); Genpire (395v/38c); Tendem by Toloka (265v/72c); Open Vibe (317v/43c)", "alignment_status": "aligned" }, { "semantic_cluster_id": "SC01", "suggested_label": "meetings and scheduling / research and knowledge work", "launches": "156", "launch_share_pct": "4.08", "traction_score": "2848", "traction_share_pct": "5.54", "attention_efficiency": "1.36", "top_examples": "Spellar 3.0 (543v/115c); Liminary (150v/48c); Raybeam (190v/5c); SideNotes (137v/17c); Cats Lock (90v/9c)", "alignment_status": "mixed" }, { "semantic_cluster_id": "SC09", "suggested_label": "security, privacy, and compliance / developer tools", "launches": "76", "launch_share_pct": "1.99", "traction_score": "2496", "traction_share_pct": "4.86", "attention_efficiency": "2.44", "top_examples": "OpenHuman (539v/67c); Graphbit PRFlow (384v/99c); ClawSecure (302v/45c); Free AI SEO Auditor (164v/23c); Whisper Internet Infra AI Context (101v/11c)", "alignment_status": "mixed" }, { "semantic_cluster_id": "SC08", "suggested_label": "recruiting and HR / marketing, SEO, and growth", "launches": "181", "launch_share_pct": "4.73", "traction_score": "2480", "traction_share_pct": "4.83", "attention_efficiency": "1.02", "top_examples": "OpenJobs AI (415v/98c); Crustimate (158v/12c); TrustClaw by Composio (139v/18c); TrackTalent (109v/9c); Pressmaster.ai (102v/7c)", "alignment_status": "aligned" }, { "semantic_cluster_id": "SC03", "suggested_label": "finance and accounting / data and analytics", "launches": "171", "launch_share_pct": "4.47", "traction_score": "2314", "traction_share_pct": "4.5", "attention_efficiency": "1.01", "top_examples": "Kelviq (508v/93c); Hyperswitch Prism (238v/20c); ChatGPT for Personal Finance (148v/10c); DoDocs inc (81v/9c); Crade AI (89v/4c)", "alignment_status": "mixed" }, { "semantic_cluster_id": "SC17", "suggested_label": "developer tools / data and analytics", "launches": "118", "launch_share_pct": "3.08", "traction_score": "2240", "traction_share_pct": "4.36", "attention_efficiency": "1.42", "top_examples": "Latitude for Claude Code (360v/23c); Files SDK (201v/4c); mia (145v/28c); Claudy (152v/12c); Wring (130v/5c)", "alignment_status": "aligned" }, { "semantic_cluster_id": "SC29", "suggested_label": "app and website builders / developer tools", "launches": "102", "launch_share_pct": "2.67", "traction_score": "2238", "traction_share_pct": "4.36", "attention_efficiency": "1.63", "top_examples": "Frontdesk AI (253v/31c); Jotform Claude App (252v/12c); Agentic Website Builder 2.0 by Lokuma (180v/48c); Kirki (178v/8c); Whale Starts (145v/15c)", "alignment_status": "aligned" }, { "semantic_cluster_id": "SC32", "suggested_label": "hardware and devices / design and creative production", "launches": "132", "launch_share_pct": "3.45", "traction_score": "1946", "traction_share_pct": "3.79", "attention_efficiency": "1.1", "top_examples": "Googlebook (211v/8c); Snapseed 4.0 (167v/3c); FileFlan (121v/11c); M5Stack PaperColor (117v/5c); MiniCPM-V 4.6 (101v/2c)", "alignment_status": "mixed" }, { "semantic_cluster_id": "SC02", "suggested_label": "health and wellness / data and analytics", "launches": "178", "launch_share_pct": "4.65", "traction_score": "1944", "traction_share_pct": "3.78", "attention_efficiency": "0.81", "top_examples": "Naptick AI (495v/117c); Habitvs (101v/8c); Mnara (78v/5c); c15t 2.0 (80v/3c); Renight (75v/1c)", "alignment_status": "aligned" }, { "semantic_cluster_id": "SC20", "suggested_label": "voice/audio products / design and creative production", "launches": "137", "launch_share_pct": "3.58", "traction_score": "1867", "traction_share_pct": "3.63", "attention_efficiency": "1.01", "top_examples": "SUN-to-Spotify (298v/27c); HeyNews (133v/26c); Keeby for Windows (97v/3c); Picsart MCP (92v/2c); Fileloom (84v/1c)", "alignment_status": "mixed" } ], "top_semantic_tags": [ { "tag": "ai_agent", "label": "AI agents and assistants", "launches": "346", "launch_share_pct": "9.04", "traction_score": "16100", "traction_share_pct": "31.34", "attention_efficiency": "3.47", "top_examples": "OpenHuman (539v/67c); HasData (423v/111c); OpenJobs AI (415v/98c); Graphbit PRFlow (384v/99c); Loova Agents (354v/78c)" }, { "tag": "developer_tools", "label": "developer tools", "launches": "664", "launch_share_pct": "17.35", "traction_score": "15504", "traction_share_pct": "30.18", "attention_efficiency": "1.74", "top_examples": "OpenHuman (539v/67c); HasData (423v/111c); Graphbit PRFlow (384v/99c); PHBench (376v/44c); Latitude for Claude Code (360v/23c)" }, { "tag": "data_analytics", "label": "data and analytics", "launches": "850", "launch_share_pct": "22.22", "traction_score": "12281", "traction_share_pct": "23.9", "attention_efficiency": "1.08", "top_examples": "OpenHuman (539v/67c); HasData (423v/111c); PHBench (376v/44c); Lensmor (291v/60c); Latitude for Claude Code (360v/23c)" }, { "tag": "productivity_ops", "label": "productivity and operations", "launches": "611", "launch_share_pct": "15.97", "traction_score": "11539", "traction_share_pct": "22.46", "attention_efficiency": "1.41", "top_examples": "Spellar 3.0 (543v/115c); Memoket Gem (477v/105c); Graphbit PRFlow (384v/99c); PHBench (376v/44c); Lensmor (291v/60c)" }, { "tag": "design_creative", "label": "design and creative production", "launches": "745", "launch_share_pct": "19.47", "traction_score": "9768", "traction_share_pct": "19.01", "attention_efficiency": "0.98", "top_examples": "Naptick AI (495v/117c); Loova Agents (354v/78c); Vivago Video Agent (342v/42c); Theneo (232v/23c); Agentic Website Builder 2.0 by Lokuma (180v/48c)" }, { "tag": "marketing_seo", "label": "marketing, SEO, and growth", "launches": "619", "launch_share_pct": "16.18", "traction_score": "9227", "traction_share_pct": "17.96", "attention_efficiency": "1.11", "top_examples": "articuler.ai (505v/87c); Loova Agents (354v/78c); PHBench (376v/44c); Vivago Video Agent (342v/42c); Blaze 2.0 (237v/57c)" }, { "tag": "research_knowledge", "label": "research and knowledge work", "launches": "526", "launch_share_pct": "13.75", "traction_score": "7850", "traction_share_pct": "15.28", "attention_efficiency": "1.11", "top_examples": "Spellar 3.0 (543v/115c); Memoket Gem (477v/105c); OpenHuman (539v/67c); Fere AI (364v/47c); Agentmemory (260v/31c)" }, { "tag": "automation_workflow", "label": "workflow automation", "launches": "377", "launch_share_pct": "9.85", "traction_score": "7462", "traction_share_pct": "14.52", "attention_efficiency": "1.47", "top_examples": "Genpire (395v/38c); Fere AI (364v/47c); Weavable (229v/67c); Jotform Claude App (252v/12c); Agentic Website Builder 2.0 by Lokuma (180v/48c)" }, { "tag": "security_privacy", "label": "security, privacy, and compliance", "launches": "404", "launch_share_pct": "10.56", "traction_score": "6010", "traction_share_pct": "11.7", "attention_efficiency": "1.11", "top_examples": "Kelviq (508v/93c); OpenHuman (539v/67c); Graphbit PRFlow (384v/99c); ClawSecure (302v/45c); Apideck MCP Server (162v/33c)" }, { "tag": "meeting_calendar", "label": "meetings and scheduling", "launches": "297", "launch_share_pct": "7.76", "traction_score": "5823", "traction_share_pct": "11.33", "attention_efficiency": "1.46", "top_examples": "Spellar 3.0 (543v/115c); Memoket Gem (477v/105c); OpenJobs AI (415v/98c); Lensmor (291v/60c); Liminary (150v/48c)" }, { "tag": "voice_audio", "label": "voice/audio products", "launches": "366", "launch_share_pct": "9.57", "traction_score": "5586", "traction_share_pct": "10.87", "attention_efficiency": "1.14", "top_examples": "Naptick AI (495v/117c); SUN-to-Spotify (298v/27c); Blaze 2.0 (237v/57c); Gradient Bang (157v/24c); HeyNews (133v/26c)" }, { "tag": "social_community", "label": "social and community", "launches": "417", "launch_share_pct": "10.9", "traction_score": "5423", "traction_share_pct": "10.56", "attention_efficiency": "0.97", "top_examples": "articuler.ai (505v/87c); PHBench (376v/44c); SUN-to-Spotify (298v/27c); Blaze 2.0 (237v/57c); Warp Open-Source (216v/30c)" } ], "daily_briefs": [ { "date": "2026-05-11", "launches": "547", "votes": "7325", "comments": "1100", "traction_score": "9525", "median_votes": "0", "median_traction": "2", "launches_with_10_or_less_votes": "479", "launches_with_10_or_less_votes_pct": "87.6", "top_launch": "articuler.ai (505v/87c; score 679)", "top_cluster_by_launches": "Design, media, and content creation (79 launches; 9.6% traction; 0.67x efficiency)", "top_cluster_by_traction": "AI agents and automation (45 launches; 17.4% traction; 2.12x efficiency)", "top_cluster_by_efficiency": "AI agents and automation (45 launches; 17.4% traction; 2.12x efficiency)", "top_1pct_vote_share_pct": "30.4", "top_5pct_vote_share_pct": "62", "content_angle": "Crowded-vs-attention split: Design, media, and content creation had the most launches, while AI agents and automation captured the most traction.", "caveat": "Clusters are inferred from name, tagline, and description text, not official Product Hunt taxonomy." }, { "date": "2026-05-12", "launches": "761", "votes": "5834", "comments": "1059", "traction_score": "7952", "median_votes": "1", "median_traction": "3", "launches_with_10_or_less_votes": "709", "launches_with_10_or_less_votes_pct": "93.2", "top_launch": "Kelviq (508v/93c; score 694)", "top_cluster_by_launches": "Consumer, education, games, and lifestyle (109 launches; 8.1% traction; 0.57x efficiency)", "top_cluster_by_traction": "AI agents and automation (66 launches; 19% traction; 2.18x efficiency)", "top_cluster_by_efficiency": "AI agents and automation (66 launches; 19% traction; 2.18x efficiency)", "top_1pct_vote_share_pct": "33.3", "top_5pct_vote_share_pct": "76.8", "content_angle": "Crowded-vs-attention split: Consumer, education, games, and lifestyle had the most launches, while AI agents and automation captured the most traction.", "caveat": "Clusters are inferred from name, tagline, and description text, not official Product Hunt taxonomy." }, { "date": "2026-05-13", "launches": "642", "votes": "7081", "comments": "1160", "traction_score": "9401", "median_votes": "2", "median_traction": "4", "launches_with_10_or_less_votes": "582", "launches_with_10_or_less_votes_pct": "90.7", "top_launch": "Memoket Gem (477v/105c; score 687)", "top_cluster_by_launches": "Design, media, and content creation (97 launches; 10.6% traction; 0.7x efficiency)", "top_cluster_by_traction": "Operator and vertical workflows (85 launches; 25.6% traction; 1.94x efficiency)", "top_cluster_by_efficiency": "AI agents and automation (50 launches; 16.9% traction; 2.17x efficiency)", "top_1pct_vote_share_pct": "27.8", "top_5pct_vote_share_pct": "63.5", "content_angle": "Crowded-vs-attention split: Design, media, and content creation had the most launches, while Operator and vertical workflows captured the most traction.", "caveat": "Clusters are inferred from name, tagline, and description text, not official Product Hunt taxonomy." }, { "date": "2026-05-14", "launches": "643", "votes": "8466", "comments": "1181", "traction_score": "10828", "median_votes": "1", "median_traction": "3", "launches_with_10_or_less_votes": "550", "launches_with_10_or_less_votes_pct": "85.5", "top_launch": "Spellar 3.0 (543v/115c; score 773)", "top_cluster_by_launches": "Design, media, and content creation (104 launches; 12.2% traction; 0.75x efficiency)", "top_cluster_by_traction": "AI agents and automation (45 launches; 21.9% traction; 3.13x efficiency)", "top_cluster_by_efficiency": "AI agents and automation (45 launches; 21.9% traction; 3.13x efficiency)", "top_1pct_vote_share_pct": "24.5", "top_5pct_vote_share_pct": "53.5", "content_angle": "Crowded-vs-attention split: Design, media, and content creation had the most launches, while AI agents and automation captured the most traction.", "caveat": "Clusters are inferred from name, tagline, and description text, not official Product Hunt taxonomy." }, { "date": "2026-05-15", "launches": "529", "votes": "6071", "comments": "1189", "traction_score": "8449", "median_votes": "1", "median_traction": "3", "launches_with_10_or_less_votes": "483", "launches_with_10_or_less_votes_pct": "91.3", "top_launch": "OpenHuman (539v/67c; score 673)", "top_cluster_by_launches": "Design, media, and content creation (76 launches; 8.2% traction; 0.57x efficiency)", "top_cluster_by_traction": "AI agents and automation (55 launches; 26% traction; 2.5x efficiency)", "top_cluster_by_efficiency": "AI agents and automation (55 launches; 26% traction; 2.5x efficiency)", "top_1pct_vote_share_pct": "32.4", "top_5pct_vote_share_pct": "67.7", "content_angle": "Crowded-vs-attention split: Design, media, and content creation had the most launches, while AI agents and automation captured the most traction.", "caveat": "Clusters are inferred from name, tagline, and description text, not official Product Hunt taxonomy." }, { "date": "2026-05-16", "launches": "394", "votes": "1682", "comments": "505", "traction_score": "2692", "median_votes": "0", "median_traction": "2", "launches_with_10_or_less_votes": "382", "launches_with_10_or_less_votes_pct": "97", "top_launch": "Loova Agents (354v/78c; score 510)", "top_cluster_by_launches": "Consumer, education, games, and lifestyle (62 launches; 5% traction; 0.32x efficiency)", "top_cluster_by_traction": "Design, media, and content creation (50 launches; 24% traction; 1.89x efficiency)", "top_cluster_by_efficiency": "AI agents and automation (30 launches; 21.3% traction; 2.8x efficiency)", "top_1pct_vote_share_pct": "57.2", "top_5pct_vote_share_pct": "88.9", "content_angle": "Crowded-vs-attention split: Consumer, education, games, and lifestyle had the most launches, while Design, media, and content creation captured the most traction.", "caveat": "Clusters are inferred from name, tagline, and description text, not official Product Hunt taxonomy." }, { "date": "2026-05-17", "launches": "310", "votes": "1675", "comments": "427", "traction_score": "2529", "median_votes": "0", "median_traction": "2", "launches_with_10_or_less_votes": "303", "launches_with_10_or_less_votes_pct": "97.7", "top_launch": "Fere AI (364v/47c; score 458)", "top_cluster_by_launches": "Design, media, and content creation (46 launches; 18.9% traction; 1.28x efficiency)", "top_cluster_by_traction": "AI agents and automation (26 launches; 37.4% traction; 4.45x efficiency)", "top_cluster_by_efficiency": "AI agents and automation (26 launches; 37.4% traction; 4.45x efficiency)", "top_1pct_vote_share_pct": "71.9", "top_5pct_vote_share_pct": "88.1", "content_angle": "Crowded-vs-attention split: Design, media, and content creation had the most launches, while AI agents and automation captured the most traction.", "caveat": "Clusters are inferred from name, tagline, and description text, not official Product Hunt taxonomy." } ], "top_launches": [ { "date_utc": "2026-05-14", "rank_in_day": "1", "launch_id": "1058199", "name": "Spellar 3.0", "meta": "Operator and vertical workflows", "micro": "Productivity, knowledge, and personal workflow", "votes": "543", "comments": "115", "traction_score": "773", "tagline": "AI Meeting companion with cross-meeting memory", "ph_url": "https://www.producthunt.com/products/spellar?utm_campaign=producthunt-api&utm_medium=api-v2&utm_source=Application%3A+Jorges+APP+%28ID%3A+282484%29" }, { "date_utc": "2026-05-14", "rank_in_day": "2", "launch_id": "1140630", "name": "Naptick AI", "meta": "Consumer, education, games, and lifestyle", "micro": "Health, education, and learning", "votes": "495", "comments": "117", "traction_score": "729", "tagline": "Al sleep companion that helps fall asleep without struggle", "ph_url": "https://www.producthunt.com/products/naptick-ai-sleep-companion?utm_campaign=producthunt-api&utm_medium=api-v2&utm_source=Application%3A+Jorges+APP+%28ID%3A+282484%29" }, { "date_utc": "2026-05-12", "rank_in_day": "1", "launch_id": "1139974", "name": "Kelviq", "meta": "Commerce, finance, and business ops", "micro": "Finance, commerce, and business ops", "votes": "508", "comments": "93", "traction_score": "694", "tagline": "Payments, tax, and billing for SaaS & AI companies", "ph_url": "https://www.producthunt.com/products/kelviq?utm_campaign=producthunt-api&utm_medium=api-v2&utm_source=Application%3A+Jorges+APP+%28ID%3A+282484%29" }, { "date_utc": "2026-05-13", "rank_in_day": "1", "launch_id": "1141013", "name": "Memoket Gem", "meta": "Operator and vertical workflows", "micro": "Productivity, knowledge, and personal workflow", "votes": "477", "comments": "105", "traction_score": "687", "tagline": "An AI wearable that remembers your conversations all day", "ph_url": "https://www.producthunt.com/products/memoket-gem?utm_campaign=producthunt-api&utm_medium=api-v2&utm_source=Application%3A+Jorges+APP+%28ID%3A+282484%29" }, { "date_utc": "2026-05-11", "rank_in_day": "1", "launch_id": "1138927", "name": "articuler.ai", "meta": "GTM, SEO, sales, and launch intelligence", "micro": "GTM, sales, and outbound", "votes": "505", "comments": "87", "traction_score": "679", "tagline": "Describe your goal. Meet the right professional.", "ph_url": "https://www.producthunt.com/products/articuler-ai?utm_campaign=producthunt-api&utm_medium=api-v2&utm_source=Application%3A+Jorges+APP+%28ID%3A+282484%29" }, { "date_utc": "2026-05-15", "rank_in_day": "1", "launch_id": "1136902", "name": "OpenHuman", "meta": "Developer infrastructure and app-building", "micro": "Developer infrastructure and coding", "votes": "539", "comments": "67", "traction_score": "673", "tagline": "An open source AI harness built with the human in mind", "ph_url": "https://www.producthunt.com/products/openhuman?utm_campaign=producthunt-api&utm_medium=api-v2&utm_source=Application%3A+Jorges+APP+%28ID%3A+282484%29" }, { "date_utc": "2026-05-15", "rank_in_day": "2", "launch_id": "1141227", "name": "HasData", "meta": "AI agents and automation", "micro": "AI agents and assistants", "votes": "423", "comments": "111", "traction_score": "645", "tagline": "Web scraping service for AI agents", "ph_url": "https://www.producthunt.com/products/hasdata?utm_campaign=producthunt-api&utm_medium=api-v2&utm_source=Application%3A+Jorges+APP+%28ID%3A+282484%29" }, { "date_utc": "2026-05-11", "rank_in_day": "2", "launch_id": "1137008", "name": "OpenJobs AI", "meta": "Operator and vertical workflows", "micro": "Hiring, career, and recruiting", "votes": "415", "comments": "98", "traction_score": "611", "tagline": "End-to-End Autonomous AI Recruiter", "ph_url": "https://www.producthunt.com/products/openjobs-ai?utm_campaign=producthunt-api&utm_medium=api-v2&utm_source=Application%3A+Jorges+APP+%28ID%3A+282484%29" }, { "date_utc": "2026-05-11", "rank_in_day": "4", "launch_id": "1052099", "name": "Graphbit PRFlow", "meta": "Security, compliance, and trust", "micro": "Security, privacy, compliance, and legal", "votes": "384", "comments": "99", "traction_score": "582", "tagline": "AI code reviewer that catches what others miss", "ph_url": "https://www.producthunt.com/products/graphbit?utm_campaign=producthunt-api&utm_medium=api-v2&utm_source=Application%3A+Jorges+APP+%28ID%3A+282484%29" }, { "date_utc": "2026-05-16", "rank_in_day": "1", "launch_id": "1143406", "name": "Loova Agents", "meta": "Design, media, and content creation", "micro": "Design, media, and creative production", "votes": "354", "comments": "78", "traction_score": "510", "tagline": "Your AI director for creating cinematic videos with ease", "ph_url": "https://www.producthunt.com/products/loova-agents?utm_campaign=producthunt-api&utm_medium=api-v2&utm_source=Application%3A+Jorges+APP+%28ID%3A+282484%29" }, { "date_utc": "2026-05-11", "rank_in_day": "3", "launch_id": "1050396", "name": "Genpire", "meta": "AI agents and automation", "micro": "AI agents and assistants", "votes": "395", "comments": "38", "traction_score": "471", "tagline": "Make Real Products with AI, literally.", "ph_url": "https://www.producthunt.com/products/genpire-ai?utm_campaign=producthunt-api&utm_medium=api-v2&utm_source=Application%3A+Jorges+APP+%28ID%3A+282484%29" }, { "date_utc": "2026-05-15", "rank_in_day": "3", "launch_id": "1144544", "name": "PHBench", "meta": "Data, analytics, and research", "micro": "Data, analytics, and research", "votes": "376", "comments": "44", "traction_score": "464", "tagline": "Predict the next Series A from a ProductHunt launch", "ph_url": "https://www.producthunt.com/products/vela-terminal?utm_campaign=producthunt-api&utm_medium=api-v2&utm_source=Application%3A+Jorges+APP+%28ID%3A+282484%29" } ], "voice_moat_fit": [ { "scope": "weekly", "bucket_type": "moat_fit", "bucket": "adjacent", "products": "356", "product_share_pct": "81.1", "votes": "4728", "comments": "795", "traction_score": "6318", "traction_share_pct": "67.6", "avg_traction": "17.7", "top_examples": "Spellar 3.0 (543v/115c); Memoket Gem (477v/105c); SUN-to-Spotify (298v/27c); Jotform Claude App (252v/12c); Liminary (150v/48c); Wowable (98v/32c); FileFlan (121v/11c); Relay (110v/15c)" }, { "scope": "weekly", "bucket_type": "moat_fit", "bucket": "action_without_clear_voice_loop", "products": "27", "product_share_pct": "6.2", "votes": "980", "comments": "203", "traction_score": "1386", "traction_share_pct": "14.8", "avg_traction": "51.3", "top_examples": "OpenJobs AI (415v/98c); Lensmor (291v/60c); AI meeting notes by Snaply (108v/20c); SurfBuddy (74v/1c); SUN (61v/0c); The Wrong List (2v/3c); Elokencia (4v/1c); Rayqua RAE (3v/1c)" }, { "scope": "weekly", "bucket_type": "moat_fit", "bucket": "talk_back_without_action", "products": "34", "product_share_pct": "7.7", "votes": "777", "comments": "155", "traction_score": "1087", "traction_share_pct": "11.6", "avg_traction": "32", "top_examples": "Naptick AI (495v/117c); Atter AI (71v/2c); Tellme (73v/0c); Stella (61v/3c); Shellular (19v/6c); ChatView (21v/3c); KText (9v/2c); Professional Resume Builder (4v/1c)" }, { "scope": "weekly", "bucket_type": "moat_fit", "bucket": "core_moat_candidate", "products": "22", "product_share_pct": "5", "votes": "453", "comments": "53", "traction_score": "559", "traction_share_pct": "6", "avg_traction": "25.4", "top_examples": "Frontdesk AI (253v/31c); bellboy (70v/3c); Mimin (71v/0c); RaykoLabs (17v/3c); VOXEA (17v/0c); FlynnAI (5v/1c); Nova (5v/1c); Support Oasis (4v/1c)" } ], "voice_by_type": [ { "scope": "weekly", "bucket_type": "voice_type", "bucket": "audio_or_meeting_adjacent", "products": "223", "product_share_pct": "50.8", "votes": "3500", "comments": "579", "traction_score": "4658", "traction_share_pct": "49.8", "avg_traction": "20.9", "top_examples": "OpenJobs AI (415v/98c); Lensmor (291v/60c); SUN-to-Spotify (298v/27c); Jotform Claude App (252v/12c); Liminary (150v/48c); Wowable (98v/32c); Relay (110v/15c); Hoogly.ai (107v/12c)" }, { "scope": "weekly", "bucket_type": "voice_type", "bucket": "transcription_meeting_memory", "products": "29", "product_share_pct": "6.6", "votes": "1377", "comments": "273", "traction_score": "1923", "traction_share_pct": "20.6", "avg_traction": "66.3", "top_examples": "Spellar 3.0 (543v/115c); Memoket Gem (477v/105c); AI meeting notes by Snaply (108v/20c); Noeth (74v/4c); YM.dat (59v/3c); Ace (57v/1c); Carbon Voice (19v/7c); Smart Noter (15v/1c)" }, { "scope": "weekly", "bucket_type": "voice_type", "bucket": "voice_interface_or_generation", "products": "131", "product_share_pct": "29.8", "votes": "728", "comments": "130", "traction_score": "988", "traction_share_pct": "10.6", "avg_traction": "7.5", "top_examples": "FileFlan (121v/11c); Atter AI (71v/2c); Whisper Island by Coddo (72v/1c); Tellme (73v/0c); VueMotion (69v/1c); AIFORPET (65v/1c); MobileCLI (63v/1c); Farao (17v/2c)" }, { "scope": "weekly", "bucket_type": "voice_type", "bucket": "voice_agent_no_clear_action", "products": "13", "product_share_pct": "3", "votes": "613", "comments": "137", "traction_score": "887", "traction_share_pct": "9.5", "avg_traction": "68.2", "top_examples": "Naptick AI (495v/117c); Stella (61v/3c); Shellular (19v/6c); ChatView (21v/3c); KText (9v/2c); Roundz AI (3v/1c); Scowld - AI Voice Companion (3v/1c); InterviewCandy (1v/1c)" }, { "scope": "weekly", "bucket_type": "voice_type", "bucket": "voice_action_agent", "products": "19", "product_share_pct": "4.3", "votes": "361", "comments": "52", "traction_score": "465", "traction_share_pct": "5", "avg_traction": "24.5", "top_examples": "Frontdesk AI (253v/31c); bellboy (70v/3c); RaykoLabs (17v/3c); FlynnAI (5v/1c); Nova (5v/1c); Mercvox (2v/1c); catch.ai (2v/1c); ClarioScope AI= (2v/1c)" }, { "scope": "weekly", "bucket_type": "voice_type", "bucket": "audio_generation_or_translation", "products": "15", "product_share_pct": "3.4", "votes": "260", "comments": "27", "traction_score": "314", "traction_share_pct": "3.4", "avg_traction": "20.9", "top_examples": "Yeta AI (82v/10c); Synci (73v/3c); Wubble.ai (69v/0c); Pianify (19v/1c); homecrate (4v/2c); SonicFlow Mac App (3v/2c); Professional Resume Builder (4v/1c); AI Video Studio for YouTube Creators (2v/1c)" }, { "scope": "weekly", "bucket_type": "voice_type", "bucket": "voice_workflow_action", "products": "9", "product_share_pct": "2.1", "votes": "99", "comments": "8", "traction_score": "115", "traction_share_pct": "1.2", "avg_traction": "12.8", "top_examples": "Mimin (71v/0c); VOXEA (17v/0c); Support Oasis (4v/1c); Swishr Desk (1v/2c); Pharmacy Store Management System (2v/1c); labTRACK - Lab Inventory Management (2v/1c); BizContact (1v/1c); WA-Instant (1v/1c)" } ] }, "recommended_public_spine": [ { "section": "Hook", "job": "Open with the emotion: the market is trying to make work disappear.", "claims": [ "W20-N01", "W20-MD-C01" ] }, { "section": "Receipt", "job": "Show the exact weekly dataset and attention distribution.", "claims": [ "W20-MD-C01", "W20-MD-C03", "W20-MD-C05", "W20-MD-C06" ] }, { "section": "Interpretation", "job": "Turn concentration and repetition into a founder-facing market psychology read.", "claims": [ "W20-N01", "W20-N02", "W20-N03" ] }, { "section": "Where attention went", "job": "Use crowded-vs-attention contrast to make the analysis concrete.", "claims": [ "W20-MD-C07", "W20-MD-C08", "W20-N05" ] }, { "section": "Founder takeaway", "job": "Position FSS as the way to understand what market a product is entering.", "claims": [ "W20-N02", "W20-N03" ] }, { "section": "Follow-up hooks", "job": "Use voice and category detail in replies, not in the main spine.", "claims": [ "W20-N06" ] } ], "tweet_first_distribution": { "main_post": "I analyzed 3,826 Product Hunt launches.\n\nThe striking part was not how many new ideas appeared.\n\nIt was how many products were chasing the same promise:\n\nmake work disappear.\n\nThe numbers are not the story.\nThey are evidence of a collective emotion.", "video_claim": "3,826 launches. One repeated promise: make work disappear.", "reply_sequence": [ { "reply": "The median launch had 1 vote, 1 comment, and 3 weighted traction points. Quiet was not the exception. Quiet was the default.", "claims": [ "W20-MD-C03", "W20-N03" ] }, { "reply": "The top attention quintile captured 84.1% of weighted traction. That is why launch day is not distribution. It is where distribution gets tested.", "claims": [ "W20-MD-C05", "W20-N02" ] }, { "reply": "The most crowded lane was design/media. The top attention lane was AI agents and automation. Crowded markets and attention markets are not always the same.", "claims": [ "W20-MD-C07", "W20-MD-C08" ] }, { "reply": "The strongest semantic cluster was AI agents + developer tools: 185 launches, 18.0% of weighted traction, 3.72x attention efficiency.", "claims": [ "W20-N05" ] }, { "reply": "Voice is a follow-up, not the headline: 439 broad voice/audio candidates, but only 22 core voice-to-action agent candidates.", "claims": [ "W20-N06" ] } ], "tagging_candidates_need_verification": [ "Spellar 3.0", "HasData", "Loova Agents", "Genpire", "Fere AI", "Vivago Video Agent", "Tendem by Toloka", "Open Vibe", "Frontdesk AI", "Free AI SEO Auditor" ] } }