Schedule tasks on the web

Original Article ↗ Hacker News Discussion ↗

Pricing, Limits, and Throttling

  • Confusion over pricing: some assume per-token; others clarify it’s subscription-based.
  • Users report limits like “3 daily cloud scheduled sessions” even on higher tiers.
  • Concerns about recent/likely throttling and changing usage terms, sometimes announced informally (e.g., via social media), feeding distrust.
  • Some see these limits as rational congestion pricing; others view them as “rug pulls” and erosion of trust.

Future of Agentic Software Development

  • Many describe a near-future loop: user feedback → AI-curated ticket → AI PR → AI review → deployment, plus A/B tests, telemetry, and progressive rollout.
  • Some are already auto-generating PRs from GitHub issues and reviewing in ephemeral environments.
  • Others strongly doubt end-to-end automation for anything beyond simple CRUD/web tasks, especially in safety‑ or finance‑critical domains.

Quality, Reliability, and Maintainability

  • Repeated reports that current models:
    • Handle small, localized changes well.
    • Struggle with complex, unfamiliar, or long‑lived systems.
    • Introduce tech debt: duplicated logic, inconsistent patterns, performance issues.
  • Several engineers say careful AI‑assisted coding is faster than fully autonomous agents, because oversight is still essential.
  • Debate over whether scaling laws and RL will inevitably push coding agents to superhuman performance vs. hitting limits in reasoning, context, and learning.

Inference Cost, Environment, and Energy

  • Inference viewed as the main economic bottleneck; calls for cheaper, more efficient hardware and software.
  • Some argue lower costs will just increase usage (more tokens, more agents); others highlight GPU capacity and environmental concerns.
  • Environmental impact is contested: some say AI’s footprint is overstated; others insist training and energy use must be factored in.

Cron vs. “Scheduled Tasks on the Web”

  • Many note this is essentially “cron + Claude in the cloud.”
  • Proponents: useful for non‑devs, removes need for local infra, integrates with MCP tools (Slack, Sentry, GitHub, etc.).
  • Critics: trivial to replicate with cron + API, potentially expensive, and introduces platform lock‑in and GitHub‑only assumptions.

Example Use Cases

  • Scheduled security/package audits, Sentry triage, and code review reports.
  • Auto‑triaging GitHub issues, generating PRs, and updating documentation.
  • Some want richer capabilities (screenshots, arbitrary HTTP, self‑hosted repos) and turn to alternative “AI cronbox” services.

Security and MCP / Tooling Concerns

  • MCP seen as powerful but also part of recent security incidents; debate over whether it’s inherently risky or just “an API.”
  • Prompt injection framed as analogous to social engineering: no complete technical fix, only mitigations with trade‑offs.

Vendor Lock‑In and Control

  • Strong current of worry about model providers owning memory, workflows, and tooling.
  • Some advocate keeping agents and automation outside proprietary ecosystems, treating models as swappable commodities.
  • Others welcome the convenience of integrated stacks and are less concerned about centralization.