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Where to Post AI Jobs in 2026: Niche vs. Aggregators

Tracking an autonomous agent across 3,570 listings, mass aggregators converted at 1.0%. Niche Telegram groups hit 7.7%. The data on where AI hiring actually works.

In short

Tracking one autonomous agent across 3,570 listings, mass aggregators converted at 1.0% applied rate while niche channels reached 4 to 7%. Reach is not the constraint; relevance is, because niche channels self-select for an audience that actually fits the role.

Applied Rate by Channel (3,570 listings)

  • Adzuna (mass aggregator): 1.0%
  • HackerNews: 4.0%
  • @web3hiring (Telegram): 6.9%
  • @jobstash (Telegram): 7.7%

When companies need to hire specialized AI engineering talent, where they post their listings dictates their success. Independent data tracking the performance of an autonomous AI agent across 3,570 job listings reveals a stark contrast between niche boards and massive aggregators.

The Aggregator Problem

Massive, generalized aggregators like Adzuna yielded a dismal 1.0% applied rate. The reach is enormous, but the relevance is so low that even an autonomous applicant agent, which has effectively zero per-application cost, barely breaks 1%.

Niche Beats Reach

In contrast, highly targeted, niche tech communities convert at significantly higher rates. Tech-focused platforms like HackerNews yielded a 4.0% applied rate, while hyper-niche Telegram groups (@jobstash, @web3hiring) yielded the highest applied rates at 7.7% and 6.9% respectively. That is roughly a 7x lift over the aggregator floor.

Why the Gap Exists

Niche channels self-select for relevant audiences. The applicant pool is smaller in absolute terms, but the share that fits the role, and the share that actually applies, is dramatically higher. For employers paying per impression or per click, the unit economics often flip the other direction entirely.

The Implication for Employers

For employers, the data is clear: utilizing specialized platforms like AgenticCareers.co to connect directly with targeted talent pools is vastly more efficient than relying on the noise of general job boards. The right question is not "where will the most people see this," but "where will the people I actually want to hire see this."

Post a role or browse current openings on AgenticCareers.co.

Frequently asked

How do job channels compare on applied rate?

Across 3,570 tracked listings, Adzuna as a mass aggregator returned a 1.0% applied rate, HackerNews reached 4.0%, and niche Telegram communities such as @web3hiring hit 6.9%, with other targeted channels in a similar band.

Why do mass aggregators convert so poorly?

The reach is enormous but the relevance is not. Volume brings in applicants who do not fit the role, so the applied rate collapses even though the listing is seen by far more people.

Why do niche channels outperform?

Because they self-select for a relevant audience. The applicant pool is smaller in absolute terms, but the share of it that actually fits the role is much higher, which is what the applied rate measures.

What should employers take from this?

That specialised platforms reaching targeted talent outperform broad distribution on the metric that matters. Optimising for reach rather than fit is what produces the 1.0% outcome.

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