Product Hunt Research — Early July 2026

Searched: July 4, 2026 Products featured: July 1–2, 2026

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1. Scritty — “Shared, searchable memory for every AI coding agent”

• Launch date: July 1, 2026
• Website: https://scritty.dev
• GitHub: https://github.com/scritty-org/scritty
• Tagline: One terminal for every AI agent, one searchable memory.

What it does

Scritty is a terminal emulator that runs any AI CLI agent inside it. It detects the agent (Claude Code, OpenAI Codex CLI, GitHub Copilot CLI, Antigravity CLI, Aider, Ollama), captures every exchange, tags it with the provider, indexes it for search (vector + keyword), and serves that memory back to agents over MCP and to users over the CLI. Captures stay on your machine — no copy-paste or per-vendor silos.

Key Features

• Agent-agnostic capture — runs at the OS terminal boundary so any CLI agent is captured without integration work
• Cross-agent searchable corpus — one vector + keyword index across all agents and sessions
• MCP + CLI access — agents query the memory via MCP protocol; users query via Ctrl+Shift+M in-terminal panel or CLI
• Browser sync — token-secured web server embedded in the desktop terminal, PWA-installable
• Phone pairing — QR code pairing, live session sync to phone via PWA
• Offline-capable — works with local Ollama models on a plane or disconnected environment
• Rules system — prompt.toml for user rules shared across agents; reads native rule files (.claude/CLAUDE.md, copilot-instructions.md, etc.)
• Control plane — operator mode with per-tenant search isolation and audit-logged admin overrides

Pricing

• 4 tiers ($19.99–$2,500/mo)
• Personal Pilot: 14-day free trial (starts via email)
• Exact tiers not publicly listed; schema data shows AggregateOffer from $19.99to$2,500

Target Audience

Developers who use multiple AI coding agents (Claude, Codex, Copilot, etc.) and want a unified, searchable memory across all of them.

Why It’s Notable

Scritty solves the fundamental problem of context fragmentation across AI coding tools — the “What did we decide about auth two weeks ago?” problem where each agent has its own siloed context window. By capturing at the terminal boundary, it’s agent-agnostic and requires no vendor integration. The desktop→browser→phone sync and offline capability are differentiators.

Useful for Developer/AI Agent Workflows?

Yes, absolutely. For developers/agents running Hermes or multi-agent workflows, Scritty provides the persistent shared memory layer that is currently missing. It’s particularly valuable for:

• Multi-agent coding sessions where context needs to survive across agent switches
• Debugging across sessions (“what did Claude decide about the architecture?”)
• Building a retrievable memory of decisions, bugs, and reasoning

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2. Glaze by Raycast — “Create your own Mac apps by chatting with AI”

• Launch date: July 2, 2026
• Website: https://glaze.app
• Made by: Raycast (makers of the popular macOS launcher)
• Tagline: Desktop apps, reimagined by you.

What it does

Glaze lets you build native macOS desktop apps by describing what you want in plain language. An AI agent builds the app, which runs locally on your machine — no server or internet connection required. Apps are native Mac applications with file system access, keyboard shortcuts, menu bar integration, and OS-level integration. You can publish apps to a public store or share privately with teams.

Key Features

• AI-powered app creation — describe what you want, AI builds it
• Local-first — apps run on your machine, no internet required
• OS-integrated — access file system, keyboard shortcuts, menu bar, background processes
• Publishing — public Glaze Store, unlisted sharing (Pro), private team store (Team)
• Credit-based usage — credits consumed proportionally based on AI work needed (quick tweaks cheap, full builds cost more)
• Non-technical friendly — no coding needed; but coders can also dive into the code
• macOS Tahoe + Apple Silicon required (Windows/Linux planned)

Pricing

Credits: Monthly subscription credits roll over 2 months; top-up credits valid 3 months.

Target Audience

Mac users who want custom desktop software without needing to code — from individual power users to teams needing internal tools.

Why It’s Notable

This is a new category from Raycast (a well-established developer tool company). Unlike Lovable, Replit, or v0 which build for the browser, Glaze builds native desktop apps with full OS access. It’s positioning itself as “the opposite of a web app builder” — real software that lives on your machine, respects your privacy, and deeply integrates with macOS. The credit-based pricing model (proportional to AI work done) is also novel.

Useful for Developer/AI Agent Workflows?

Moderate. Glaze is more focused on end-users creating desktop apps than on AI agent tooling. However, developers could use it to:

• Rapidly prototype internal developer tools and utilities
• Build menu bar apps for monitoring dev workflows
• Create custom automation tools that integrate with local file systems and APIs
• Less directly useful for AI agent orchestration itself

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3. Osloq — “An AI agent that reproduces GitHub issues for you”

• Launch date: July 2, 2026
• Website: https://osloq.com
• Tagline: Your issue investigator.

What it does

Osloq is an AI agent that connects to your GitHub repository, reads an issue, traces the relevant code and commits, runs the project in an isolated sandbox to reproduce the bug, and returns a verified report with logs, screenshots, and the exact code path that caused the issue.

Key Features

• GitHub App integration — least-privilege, read-only access (never pushes or modifies code)
• Multi-language support — JavaScript, TypeScript, Python, Go (expanding), and designed to understand any language
• Automated bug reproduction — runs code in isolated sandbox, captures logs, screenshots, errors
• Evidence-backed reports — links findings to specific code paths, commits, and runtime context
• Project secrets support — can use secrets for real-environment reproduction or bypass dependencies without them
• Sandbox destroyed after investigation — code never stored or used for training

Pricing

No credit card required to start. Cancel anytime.

Target Audience

Software developers, engineering teams, QA engineers, and open-source maintainers who need to quickly triage and reproduce bugs from GitHub issues.

Why It’s Notable

Reproducing bugs from issue descriptions is one of the most time-consuming parts of software maintenance. Osloq automates this entire workflow — reading the issue, understanding the codebase, running the code, and verifying the bug — then delivering a report instead of a shrug. The sandbox-isolated execution with ephemeral infrastructure and no code retention addresses the security/privacy concerns that plague similar tools.

Useful for Developer/AI Agent Workflows?

Yes, very useful. Osloq directly complements AI agent workflows:

• An AI coding agent like Claude Code or Codex could use Osloq to verify bugs before fixing them
• Could be integrated into CI/CD pipelines for automated issue triage
• Reduces the human-in-the-loop cost of bug reproduction during development sprints
• The “reproduce first, then fix” workflow aligns perfectly with systematic debugging approaches
• Particularly valuable for open-source maintainers overwhelmed by issue triage

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Summary

Key takeaway: All three products launched within 24 hours of each other and are directly relevant to the AI-assisted development workflow. Scritty and Osloq are particularly complementary — Scritty provides persistent memory for AI agents, while Osloq automates bug reproduction that those agents can then fix.