Aperture vs Spectrum

Aperture replaces the keyword-matching stage of hiring with autonomous AI-conducted behavioral interviews and comparative candidate ranking. Rather than filtering resumes by whether they contain the word 'Kubernetes' or 'Series B experience,' Aperture schedules and conducts structured situational interviews with every applicant, evaluates responses against custom rubrics, and ranks candidates against each other — all before a human recruiter sees a single name. The product targets the worst-known failure mode in early-stage hiring: resume screening filters out qualified candidates who describe their experience differently while passing through keyword-stuffers who know how to optimize for ATS systems. Behavioral interviewing surfaces actual competency patterns rather than self-reported credentials. The AI evaluator applies a consistent rubric regardless of which recruiter reads the response, addressing a source of structured bias that's hard to fix with human screeners alone. Launched on Product Hunt today, Aperture enters a crowded but unsolved space. The differentiation is the full-stack approach — conducting the interview autonomously rather than just scoring human-conducted interviews, which compresses the screening timeline from weeks to hours.

Spectrum, from Photon, launched on Product Hunt today with 105 upvotes and a simple but sharp premise: your users don't want to learn a new AI interface—they want AI to show up in Slack, Teams, email, and every other tool they already use. Spectrum is an agent deployment layer that routes your AI agents to wherever your users are, with no per-integration custom dev work. The core product is an abstraction layer that handles the connector plumbing: authenticate once, and your agent can receive messages and send responses across all connected channels. Built-in conversation management means agents maintain context across channels—a user can start a request in Slack, continue it in Teams, and finish in email without losing thread. The platform also handles rate limiting, authentication, and error handling for each channel. For teams building internal AI tools or customer-facing AI assistants, this solves real integration pain. Building a Slack bot, Teams integration, email handler, and web widget separately takes weeks per channel. Spectrum reduces that to a single agent definition deployed everywhere. The question is pricing and lock-in: if Photon becomes the integration layer, they sit in a strategically critical position.