Category guide
AI agent launch context
AI agent launches cover tools that can plan, use tools, browse, code, operate workflows, or complete background tasks with some autonomy.
What belongs here
Browser agents, workflow agents, enterprise agent platforms, coding agents, background task agents, and agent infrastructure with verifiable product or release links.
Why this matters
Agent claims can be noisy, so source links, demos, permissions, API access, and clear human-review boundaries matter more than broad autonomy language.
For AI companies
Turn a launch into source-backed visibility
Kingy AI uses launch records, tool profiles, Daily Launch Radar coverage, creator-fit signals, and ROI tools to help AI companies move from announcement to useful discovery.
Skippr embeddable real-time product agent
Skippr AI launched an embeddable real-time agent that can speak with users, understand an application's context, demonstrate workflows, and operate the product with approval controls.
Skippr AI addresses a concrete need: Skippr represents a product-interface trend in which software companies embed an agent that can demonstrate and operate the…
OpenClaw v2026.7.1
OpenClaw v2026.7.1 shipped major Control UI and onboarding overhauls, major updates to the official iOS, Android, and macOS apps, expanded model and provider support, and stronger Codex and…
OpenClaw v2026.7.1 is a substantive platform release rather than a narrow patch: the interface, onboarding, companion apps, and provider and coding-agent paths move together.…
GitHub Mobile Copilot cloud agent merge-conflict fix
In the latest iOS and Android production builds, GitHub Mobile can prefill a pull-request comment asking Copilot cloud agent to resolve merge conflicts; the user reviews and submits…
The mobile shortcut is useful for starting work, not for proving that a conflict was resolved correctly. GitHub prepopulates a request from the pull-request…
GitHub Copilot in VS Code June 2026 releases
GitHub summarized Copilot changes across Visual Studio Code 1.123 through 1.127, including integrated browser interaction, parallel agent sessions, chat organization, AI-credit visibility, model-provider discovery and Autopilot behavior.
The June roundup shows VS Code becoming an orchestration surface for multiple agents, browser checks and model choices rather than a single coding chat.…
Codex as an agent provider in GitHub Copilot for JetBrains
GitHub added Codex as an optional public-preview agent provider in GitHub Copilot for JetBrains IDEs and shipped related agentic enhancements including hooks support, richer MCP server management and…
Provider choice inside JetBrains can reduce tool switching, but Codex, Claude and Copilot modes should not be treated as equivalent harnesses. The release is…
Katalyst AI
Katalyst appeared on Product Hunt on July 7, 2026 with positioning around an AI agent for Salesforce pipeline work, including AI Resolution, meeting recorder, hygiene scores, and deal…
- Launch readiness
- 6.1 / 10
- Demo evidence
- Not scored yet
- Creator-story fit
- Not scored yet
Score definitions and rubric
These are launch-record readiness heuristics, not product ratings.
Launch readiness
How complete and reviewable the launch record is, not the quality of the product.
Inputs and weights: Launch date 15%; qualifying source 10%; what launched 10%; demo 15%; category 10%; audience 10%; editorial assessment 10%; traction evidence 10%; creator or audience fit 10%.
Evidence inputs: Reviewed launch metadata, public source links, demo links, taxonomy, audience, editorial notes, and recorded traction signals.
Demo evidence
Whether the record contains useful, reviewable demonstration evidence; it is not a rating of product output quality.
Inputs and weights: Working demo URL 45%; video walkthrough 25%; clear description of what launched 10%; audience 10%; editorial assessment 10%.
Evidence inputs: Demo and video URLs plus the reviewed launch description, audience, and editorial notes.
Creator-story fit
Whether a launch has enough demonstrable evidence and audience relevance for a useful creator story; it does not predict views or guarantee coverage.
Inputs and weights: Demo evidence 25%; visual creator category 15%; audience 15%; editorial assessment 15%; traction evidence 10%; pricing clarity 10%; API or open-weight evidence 10%.
Evidence inputs: Reviewed demo, category, audience, editorial, traction, pricing, API, and open-weight fields.
- Scale
- 0.0–10.0. A present qualifying input receives its published weight; a missing input receives zero. Scores are rounded to one decimal.
- Assigned by
- Suggested by the deterministic field-completeness helper and assigned or approved by a Kingy editorial reviewer.
- Rubric and check date
- Rubric version P0-2026-08-10. The record’s “Last verified” date is the score check date. Checked: 2026-07-08.
- Confidence and missing data
- Confidence depends on source completeness. “Not scored yet” means no reviewed value; “Needs review” means the value or score set failed validation.
- Freshness
- Recalculate after a material launch, source, demo, pricing, audience, or traction change and during the record freshness review.
- Disputes
- Use “Suggest a correction” on the record and cite the relevant evidence. Commercial relationships cannot buy or alter a score.
Katalyst launched on Product Hunt with an AI agent for Salesforce pipeline work — AI Resolution, a meeting recorder, hygiene scores, and deal patterns…
Genkit Agents API
Google introduced the Genkit Agents API in preview for TypeScript and Go, with a shared chat interface, streaming, server- or client-managed state, snapshots, human interrupts, detached tasks and…
- Launch readiness
- 7.6 / 10
- Demo evidence
- Not scored yet
- Creator-story fit
- Not scored yet
Score definitions and rubric
These are launch-record readiness heuristics, not product ratings.
Launch readiness
How complete and reviewable the launch record is, not the quality of the product.
Inputs and weights: Launch date 15%; qualifying source 10%; what launched 10%; demo 15%; category 10%; audience 10%; editorial assessment 10%; traction evidence 10%; creator or audience fit 10%.
Evidence inputs: Reviewed launch metadata, public source links, demo links, taxonomy, audience, editorial notes, and recorded traction signals.
Demo evidence
Whether the record contains useful, reviewable demonstration evidence; it is not a rating of product output quality.
Inputs and weights: Working demo URL 45%; video walkthrough 25%; clear description of what launched 10%; audience 10%; editorial assessment 10%.
Evidence inputs: Demo and video URLs plus the reviewed launch description, audience, and editorial notes.
Creator-story fit
Whether a launch has enough demonstrable evidence and audience relevance for a useful creator story; it does not predict views or guarantee coverage.
Inputs and weights: Demo evidence 25%; visual creator category 15%; audience 15%; editorial assessment 15%; traction evidence 10%; pricing clarity 10%; API or open-weight evidence 10%.
Evidence inputs: Reviewed demo, category, audience, editorial, traction, pricing, API, and open-weight fields.
- Scale
- 0.0–10.0. A present qualifying input receives its published weight; a missing input receives zero. Scores are rounded to one decimal.
- Assigned by
- Suggested by the deterministic field-completeness helper and assigned or approved by a Kingy editorial reviewer.
- Rubric and check date
- Rubric version P0-2026-08-10. The record’s “Last verified” date is the score check date. Checked: 2026-07-28.
- Confidence and missing data
- Confidence depends on source completeness. “Not scored yet” means no reviewed value; “Needs review” means the value or score set failed validation.
- Freshness
- Recalculate after a material launch, source, demo, pricing, audience, or traction change and during the record freshness review.
- Disputes
- Use “Suggest a correction” on the record and cite the relevant evidence. Commercial relationships cannot buy or alter a score.
Genkit Agents API removes repeated full-stack agent plumbing while leaving teams in control of runtime and state ownership. The preview can introduce breaking changes…
GitHub Copilot for Jira reaches GA: June 25, 2026 launch record
GitHub Copilot for Jira reached general availability, adding real-time Copilot cloud-agent progress inside Jira, post-session steering and simplified onboarding for connected GitHub repositories.
The GA release closes useful workflow gaps by returning agent progress and follow-up control to Jira. The integration also moves ticket context into a…
BrowserAct
BrowserAct launched a browser-automation platform spanning an agent CLI and hosted workflow product, with isolated browser sessions, reusable profiles, proxy options, network evidence and human takeover for compatible…
BrowserAct’s launch combines useful session isolation, agent commands and human takeover, but stealth browsers, proxies and reusable profiles increase both capability and misuse risk.…
Kore.ai Agent Blueprint Language
Kore.ai published the launch of Agent Blueprint Language on June 24, 2026, positioning it as the foundation of its Artemis AI-native enterprise agent platform.
- Launch readiness
- 6.1 / 10
- Demo evidence
- Not scored yet
- Creator-story fit
- Not scored yet
Score definitions and rubric
These are launch-record readiness heuristics, not product ratings.
Launch readiness
How complete and reviewable the launch record is, not the quality of the product.
Inputs and weights: Launch date 15%; qualifying source 10%; what launched 10%; demo 15%; category 10%; audience 10%; editorial assessment 10%; traction evidence 10%; creator or audience fit 10%.
Evidence inputs: Reviewed launch metadata, public source links, demo links, taxonomy, audience, editorial notes, and recorded traction signals.
Demo evidence
Whether the record contains useful, reviewable demonstration evidence; it is not a rating of product output quality.
Inputs and weights: Working demo URL 45%; video walkthrough 25%; clear description of what launched 10%; audience 10%; editorial assessment 10%.
Evidence inputs: Demo and video URLs plus the reviewed launch description, audience, and editorial notes.
Creator-story fit
Whether a launch has enough demonstrable evidence and audience relevance for a useful creator story; it does not predict views or guarantee coverage.
Inputs and weights: Demo evidence 25%; visual creator category 15%; audience 15%; editorial assessment 15%; traction evidence 10%; pricing clarity 10%; API or open-weight evidence 10%.
Evidence inputs: Reviewed demo, category, audience, editorial, traction, pricing, API, and open-weight fields.
- Scale
- 0.0–10.0. A present qualifying input receives its published weight; a missing input receives zero. Scores are rounded to one decimal.
- Assigned by
- Suggested by the deterministic field-completeness helper and assigned or approved by a Kingy editorial reviewer.
- Rubric and check date
- Rubric version P0-2026-08-10. The record’s “Last verified” date is the score check date. Checked: 2026-06-25.
- Confidence and missing data
- Confidence depends on source completeness. “Not scored yet” means no reviewed value; “Needs review” means the value or score set failed validation.
- Freshness
- Recalculate after a material launch, source, demo, pricing, audience, or traction change and during the record freshness review.
- Disputes
- Use “Suggest a correction” on the record and cite the relevant evidence. Commercial relationships cannot buy or alter a score.
Kore.ai introduced Agent Blueprint Language on June 24, 2026 as the foundation of its Artemis enterprise agent platform, framing agent behavior as a compiled…
Latitude V2 Agent Monitoring
Latitude launched V2 for AI-agent monitoring, combining production traces, session search, behavior-pattern signals, recurring-failure discovery, alerts and a coding-agent handoff supplied with issue context.
- Launch readiness
- 7.6 / 10
- Demo evidence
- Not scored yet
- Creator-story fit
- Not scored yet
Score definitions and rubric
These are launch-record readiness heuristics, not product ratings.
Launch readiness
How complete and reviewable the launch record is, not the quality of the product.
Inputs and weights: Launch date 15%; qualifying source 10%; what launched 10%; demo 15%; category 10%; audience 10%; editorial assessment 10%; traction evidence 10%; creator or audience fit 10%.
Evidence inputs: Reviewed launch metadata, public source links, demo links, taxonomy, audience, editorial notes, and recorded traction signals.
Demo evidence
Whether the record contains useful, reviewable demonstration evidence; it is not a rating of product output quality.
Inputs and weights: Working demo URL 45%; video walkthrough 25%; clear description of what launched 10%; audience 10%; editorial assessment 10%.
Evidence inputs: Demo and video URLs plus the reviewed launch description, audience, and editorial notes.
Creator-story fit
Whether a launch has enough demonstrable evidence and audience relevance for a useful creator story; it does not predict views or guarantee coverage.
Inputs and weights: Demo evidence 25%; visual creator category 15%; audience 15%; editorial assessment 15%; traction evidence 10%; pricing clarity 10%; API or open-weight evidence 10%.
Evidence inputs: Reviewed demo, category, audience, editorial, traction, pricing, API, and open-weight fields.
- Scale
- 0.0–10.0. A present qualifying input receives its published weight; a missing input receives zero. Scores are rounded to one decimal.
- Assigned by
- Suggested by the deterministic field-completeness helper and assigned or approved by a Kingy editorial reviewer.
- Rubric and check date
- Rubric version P0-2026-08-10. The record’s “Last verified” date is the score check date. Checked: 2026-07-28.
- Confidence and missing data
- Confidence depends on source completeness. “Not scored yet” means no reviewed value; “Needs review” means the value or score set failed validation.
- Freshness
- Recalculate after a material launch, source, demo, pricing, audience, or traction change and during the record freshness review.
- Disputes
- Use “Suggest a correction” on the record and cite the relevant evidence. Commercial relationships cannot buy or alter a score.
Latitude V2 creates a useful closed loop from production traces to recurring-failure signals and a proposed repair. Kingy did not connect telemetry, measure cluster…
AgentX Agent Evaluation Framework
AgentX launched an AI-agent evaluation workflow for building test suites, tracing failures, comparing models on quality, cost, and latency, and suggesting fixes before production deployment.
- Launch readiness
- 7.2 / 10
- Demo evidence
- Not scored yet
- Creator-story fit
- Not scored yet
Score definitions and rubric
These are launch-record readiness heuristics, not product ratings.
Launch readiness
How complete and reviewable the launch record is, not the quality of the product.
Inputs and weights: Launch date 15%; qualifying source 10%; what launched 10%; demo 15%; category 10%; audience 10%; editorial assessment 10%; traction evidence 10%; creator or audience fit 10%.
Evidence inputs: Reviewed launch metadata, public source links, demo links, taxonomy, audience, editorial notes, and recorded traction signals.
Demo evidence
Whether the record contains useful, reviewable demonstration evidence; it is not a rating of product output quality.
Inputs and weights: Working demo URL 45%; video walkthrough 25%; clear description of what launched 10%; audience 10%; editorial assessment 10%.
Evidence inputs: Demo and video URLs plus the reviewed launch description, audience, and editorial notes.
Creator-story fit
Whether a launch has enough demonstrable evidence and audience relevance for a useful creator story; it does not predict views or guarantee coverage.
Inputs and weights: Demo evidence 25%; visual creator category 15%; audience 15%; editorial assessment 15%; traction evidence 10%; pricing clarity 10%; API or open-weight evidence 10%.
Evidence inputs: Reviewed demo, category, audience, editorial, traction, pricing, API, and open-weight fields.
- Scale
- 0.0–10.0. A present qualifying input receives its published weight; a missing input receives zero. Scores are rounded to one decimal.
- Assigned by
- Suggested by the deterministic field-completeness helper and assigned or approved by a Kingy editorial reviewer.
- Rubric and check date
- Rubric version P0-2026-08-10. The record’s “Last verified” date is the score check date. Checked: 2026-07-16.
- Confidence and missing data
- Confidence depends on source completeness. “Not scored yet” means no reviewed value; “Needs review” means the value or score set failed validation.
- Freshness
- Recalculate after a material launch, source, demo, pricing, audience, or traction change and during the record freshness review.
- Disputes
- Use “Suggest a correction” on the record and cite the relevant evidence. Commercial relationships cannot buy or alter a score.
AgentX launched an agent-evaluation framework that builds test suites, traces failures, compares models on quality, cost, and latency, and suggests fixes before deployment, shipping…