AI tool comparison
Agent! vs Kelet
Which one should you ship with? Here is the side-by-side panel verdict, pricing read, reviewer split, and community vote comparison.
Developer Tools
Agent!
Native macOS AI coding agent — no subscriptions, 17 LLMs, full undo
75%
Panel ship
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Community
Free
Entry
Agent! is an open-source, native macOS application that aims to replace subscriptions to Claude Code, Cursor, and Cline — all in one local app. Built with SwiftUI, it connects to 17 LLM providers including Claude, GPT-4o, Gemini, Grok, and Ollama for fully local runs, and taps Apple Intelligence for on-device token compression when context windows overflow. The standout feature is Time Machine-style file backup with one-click undo on any edit — a safety net conspicuously missing from most AI coding tools today. It also controls macOS via the Accessibility API, automates Safari and Playwright for web tasks, executes shell commands, and handles iMessage-triggered commands. Multi-tab support lets you run parallel agent sessions without context bleed. Zero telemetry, bring-your-own-API-keys, MIT licensed. For developers tired of juggling multiple AI coding subscriptions or uncomfortable with code leaving their machine, this is a compelling local-first alternative that's appeared on Hacker News today.
Developer Tools
Kelet
AI agent that diagnoses why your LLM app failed in production
75%
Panel ship
—
Community
Free
Entry
Kelet is a production monitoring platform that automatically diagnoses and fixes failures in LLM applications and AI agents. Rather than requiring engineers to manually sift through thousands of traces, Kelet reads production agent traces, clusters failure patterns across sessions, and surfaces root causes with supporting evidence. The platform's standout feature is credit assignment for multi-agent architectures — when a LangChain, CrewAI, or PydanticAI pipeline fails, Kelet pinpoints exactly which agent in the chain caused the failure rather than returning a vague error message. It then generates targeted prompt patches with measurable before/after reliability improvements, so fixes ship with proof they work. Setup takes approximately five minutes via the Kelet SDK or installer skill, with full OpenTelemetry compliance for teams already running observability infrastructure. Kelet covers the LLM token costs for its own analysis, and a free tier requires no credit card — making it accessible to indie builders before they've committed to paid tooling.
Reviewer scorecard
“The Time Machine undo alone makes this worth trying — every AI coding tool should have this and almost none do. Bring-your-own-keys with 17 providers means you're not locked in. The Accessibility API integration is powerful for automating macOS tasks beyond just code.”
“Kelet solves the specific hell of debugging AI agents in production: thousands of traces, failure patterns scattered across sessions, and no clear signal about which prompt, which agent, or which data caused the issue. The credit assignment for multi-agent chains is the killer feature — knowing exactly which subagent in a CrewAI or LangGraph chain broke is worth the integration cost alone. Five-minute setup via SDK and OpenTelemetry compliance means it plugs into what you're already running.”
“macOS-only by definition, and native apps require significant maintenance across OS updates. The GitHub repo is brand new — no track record, unknown reliability in production codebases. Apple Intelligence compression sounds clever until you realize it adds another dependency and single point of failure.”
“Kelet is an LLM analyzing LLM failures, which is a charming recursion problem. When your agent monitoring agent hallucinates a root cause, you've added a failure mode that's harder to debug than the original. The 'evidence-backed fixes with before/after reliability measurements' pitch sounds airtight, but those measurements depend on the LLM evaluation being correct — which is exactly what you can't assume in production. A solid structured logging + tracing setup with deterministic replay would catch most of these failures without adding another probabilistic layer.”
“Local-first AI coding is the natural endgame for privacy-conscious developers and regulated industries. The Time Machine approach hints at a future where AI edits are fully auditable and reversible — a property that will become legally required in some domains.”
“Observability tooling for AI agents is a category that barely exists and desperately needs to. As agent deployments move from side projects to production infrastructure, teams need the same root cause analysis discipline that SRE culture built for traditional services. Kelet is early in a space that will be massive — expect DataDog, Grafana, and every APM vendor to build versions of this within 18 months.”
“The multi-tab parallel agent feature is genuinely exciting for creative workflows — run one agent exploring a design system while another drafts the implementation. Zero subscriptions means a solo creator can access frontier models without a $200/month tab.”
“For indie builders shipping AI products to paying customers, Kelet is exactly the kind of tooling that turns 'my agent sometimes fails and I don't know why' into a real support workflow. The free tier with no credit card means you can actually test whether it's useful before committing.”
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