21 days, $5K, 7 AI agents: how a non-programmer built a talent marketplace
Kraig Ward and Mike Martin have launched the Bearhug Network, a marketplace connecting executives with hiring companies. The platform features anonymized profiles and a vetting process to facilitate introductions. Ward, a non-programmer, developed the network over 21 days with the help of AI agents, investing around $5,000 and producing over 75,000 lines of code.
- ▪The Bearhug Network connects hiring companies with executives looking for opportunities.
- ▪Kraig Ward built the platform in 21 days using AI agents and without prior coding experience.
- ▪The network aims to provide a new avenue for executives to explore job opportunities discreetly.
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Story provenance
Attribution is not the same as permission. This drawer separates discovery metadata, excerpts, WeSearch-generated summaries, reuse status, and whether the publisher receives the visit. Nothing here claims a legal grant the publisher has not made.
Record
| Original publisher | Bearhug Recruiting: Executive Search for Human Performance Brands & Environmental Technology Companies. |
| Canonical URL | https://www.bearhugrecruiting.com/startup-recruiting/bearhug-network-origin-story |
| Publication time | Fri, 29 May 2026 23:02:53 +0000 |
| Retrieval time | 2026-05-29T23:10:36.644Z |
| Last seen | 2026-05-29T23:10:36.644Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | MYwjL_IM6l7o |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
Rights status (four layers)
WeSearch handling by dimension
| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
How 10 Years Trying to Improve Executive Search Finally Clicked When I Locked Myself in My Office for 21 Days With 7 AI Agents and Built Something for You That Doesn't Exist Anywhere Else. Strategic Networking May 29 Written By Kraig Ward I need to tell you how this happened. Not the polished version. The real one.The short version is that my partner Mike Martin and I just launched the Bearhug Network, a two-sided marketplace that connects the people who hire executives with the executives who are either actively looking or are open if the right opportunity were to come knocking. Anonymized profiles. Vetted by the Bearhug team.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at Bearhug Recruiting: Executive Search for Human Performance Brands & Environmental Technology Companies..
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