infinit.dev
partial
Claude Code
intent
What does infinit.dev do and who is it for? Explain it back to me.
20steps
124.6sduration
$1.5898cost
202,460tokens
32 steps12 reasoning steps12 searches
home
search
search
docs
/services
docs
search
industry.home
search
search
/company/infinit-s-r-o-
search
search
search
/infinit/pricing
search
search
search
docs
search
62%
on-site discovery
50%
reliability
50%
link following
path origin
- previous resource50%
- web search38%
- prior knowledge13%
insight
The agent assembled a partial picture of infinit.dev by combining fragments from the homepage, a subdomain, LinkedIn, and an external pricing review site. The site itself proved minimally navigable—core pages returned 404s, there was no published pricing, and key information was either sparse or absent. The agent had to rely heavily on web search and external sources to fill gaps.
- ›Step [1] (homepage fetch) provided basic positioning ('flexible developer outsourcing company') but no detail on services, pricing, or engagement models.
- ›Steps [6–8, 11] revealed that /pricing, /services, /about, and /blog all return 404 errors, indicating a skeletal website structure.
- ›Step [13] (industry.infinit.dev) added a secondary product line (industrial/hardware focus) but only confirmed what was already known from the main domain.
- ›Step [19] (LinkedIn) returned data-heavy markup but required external parsing; it provided employee count and company basics but limited operational detail.
- ›Step [28] (ITQlick review site, external to infinit.dev) was the agent's only source for concrete pricing context, yet the response was truncated and the agent acknowledged not actually finding specific rates.
- ›The agent relied on web search (38%) and previous artifacts (50%) because the site itself exposed almost no actionable structure. Direct guesses and prior knowledge accounted for only 13%.
- ›No case studies, client testimonials, engagement process documentation, or service descriptions were publicly accessible on infinit.dev.
- ›The site lacks machine-readable signals (structured data, schema markup, or clear navigation) that would help an agent self-serve discovery.
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