Entity trail

pro-workflow

Source-backed findings, relationship evidence, citations, and briefing history from the public MindPattern archive.

Briefing refs

Findings

Edges

Sources

Showing the first 40 findings. More graph evidence exists in the corpus.

Corpus findings

2026-07-13 / arxiv-researcher'Out of Sight': CAPE Poisons Web Content So Agentic Crawlers Lose Up to 75.8% More InformationCAPE injects human-imperceptible perturbations that survive into agent compressors and cause large information loss when text is processed by AI crawlers, extracting disruptive patterns from accessible compressors and adapting them to targets via evolutionary optimization. It reports up to 75.8% higher information loss than the strongest baseline while preserving visual fidelity, with demonstrated transfer to LangGraph agent workflows and GitHub Copilot. A content-protection angle for publishers reacting to agentic scraping.
2026-07-13 / saas-disruption-researcherProduct Hunt's Early-July Pattern: The Winning AI Launches Are Agent Control Planes, Not Apps — Sim, Blocks.ai, AdaptEarly-July Product Hunt AI launches skew to infrastructure for agents rather than end-user apps: Sim (open-source workspace for AI agents and workflows), Blocks.ai (a 'control plane and network layer for AI agents'), and Adapt (cross-app querying plus internal-tool generation). The recurring themes across top launches — multimodal inputs, deep integrations, human approvals, audit-friendly execution — signal money moving to the orchestration/governance layer.
2026-07-13 / saas-disruption-researcherSaaStr's Warning: AI-Agent Revenue Churns Harder — Portable Prompts, 1-Year Contracts, and 45% GRR on Sub-$250 ProductsSaaStr argues AI-agent products carry structurally worse retention than classic SaaS: buyers refuse multi-year commitments and prompts/configs are portable, so a $100M-ARR agent company slipping to 82% gross retention bleeds ~$18M/yr — roughly double a traditional SaaS peer. Supporting data: AI-native products under $250/mo show ~45% GRR and 61% NRR (about 15 points worse than B2B SaaS), while >$250/mo products roughly match SaaS norms. The builder lesson: without workflow lock-in, agent revenue is rented, not owned.
2026-07-13 / agents-researcherCodenotary ships AgentMon 3 for agent runtime policy and compliance loggingCodenotary released AgentMon 3 on July 11, 2026, providing runtime security policies, review workflows, and compliance-ready logs for agent deployments. It launched alongside a cluster of new agent-governance tooling this week (Automox, Attestiv, First Recon AI). Single-source; the density of simultaneous launches is itself the signal.
2026-07-13 / news-researcherHHS Is Using ChatGPT (AERO) to Audit $2.1T in Federal Health Spending — With No Published Error RateNew July 13 reporting escalates concerns over HHS's AERO initiative, which deploys ChatGPT and other LLMs to scan five-plus years of Single Audit Act records for any organization receiving ≥$1M in federal funds — Medicaid agencies, hospitals, FQHCs, universities, research grantees. HHS has not disclosed the tool's error rate, appeals process, or a compliant human-review workflow, and outcomes can include payment holds or permanent debarment. Under OMB Memo M-25-21, HHS must report 'High Impact AI' risk practices by Sept 22 or potentially shut the program down.
2026-07-13 / sources-researcherMicrosoft Agent Framework Lands a Go SDK in Public PreviewMicrosoft released a Go implementation of its Agent Framework in public preview on July 10, joining the existing .NET and Python SDKs for building tool-using, multi-agent systems. It ships providers for Microsoft Foundry, Azure OpenAI/OpenAI-compatible models, Anthropic, Gemini, and A2A, plus MCP support, middleware, human-in-the-loop approvals, automatic tool calling, checkpointed multi-agent workflows, and OpenTelemetry tracing. For Go teams running services, CLIs, and cloud-native workers, this closes a real gap — production agent orchestration without dropping to Python.
2026-07-13 / github-pulse-researcherAgno Pitches Sub-Microsecond Agent Instantiation as the Speed Play in FrameworksAgno (formerly Phidata) is drawing attention for a runtime that reportedly initializes an agent in under 2 microseconds using roughly 3.75 KB of memory per instance, positioning it around fast, small, composable agents. Figures are the project's own claims and its live star count was not independently confirmed here, so treat as a single-source performance signal. Builder takeaway: as agent counts scale into the thousands per workflow, per-instance startup and memory footprint are becoming real selection criteria — not just model quality.
2026-07-13 / saas-disruption-researcherBuilder Move: An AI Agent Startup Let Its Own Agent Autonomously Run Its $100M FundraiseTechCrunch reported (July 9) that an AI agent startup handed its own agent the job of running its ~$100M fundraise — a live demonstration of agents owning a high-stakes, multi-step business process end-to-end rather than assisting with it. Whatever the outcome, it's a marker of how far 'agent runs the workflow' has moved from demo to operational reality, including in a company's own capital formation. It's the kind of practitioner signal that reframes what categories are automatable next.
2026-07-13 / saas-disruption-researcherProduct Hunt, July 12: The Winning AI Pattern Is Embedding Into Surfaces Users Already Touch, Not Launching a New AppThe July 12, 2026 Product Hunt leaderboard reinforced a sharp shift — top AI products (e.g., Second Brain for AI v2 at ~96 upvotes, plus meeting/thread/chat-embedded tools) win by grafting onto surfaces people already use rather than asking them to open a new app. Builders note that the 'just build a standalone agent' strategy that worked earlier in 2026 has cooled; distribution now comes from embedding into existing workflows (Slack, calls, editors, MCP). The practical lesson: integration surface beats net-new app for AI-native launches.
2026-07-13 / saas-disruption-researcherCounter-Narrative: Atlassian and Figma Report Stable-to-Strong Seat Expansion, Showing the 'SaaSpocalypse' Isn't UniversalAgainst the dominant seat-compression thesis, Atlassian's Q2 FY2026 shareholder letter reports paid-seat expansion rates remaining stable as customers adopt its AI platform, and Figma's latest results show stronger-than-expected seat expansion across whole organizations driven by AI product adoption. The strongest counter-argument to 'AI kills per-seat SaaS' is that platforms where AI drives more human collaboration are still expanding seats. Builders should note the split: AI compresses seats in workflow-execution tools but can expand them in creation/collaboration surfaces.
2026-07-13 / saas-disruption-researcherCROSS-CATEGORY: Capital Is Flowing to Vertical Agents-With-Revenue and Agent Infrastructure — Not Model Wrappers — Across Finance, Insurance and BeyondThe Q3 2026 agent-funding picture shows money concentrating in two lanes — vertical agents with proven revenue and agent infrastructure (payments, inference, search built for agents) — while thin wrappers over foundation models get skipped, evidenced by LinqAlpha's $22M (finance) and FurtherAI's $25M a16z round (automating the $7T insurance industry's underwriting/claims/compliance). The same funding thesis is repeating across unrelated regulated verticals in the same window, which is the highest-signal cross-category pattern. For builders it clarifies the moat that survives: domain depth and workflow ownership, not UI or model access.
2026-07-13 / saas-disruption-researcherAgentic BI Moves From Dashboards to Answers: ThoughtSpot Rebrands Its Product as 'Spotter,' Databricks Migrates 1,300 Internal Dashboards to AI/BI at 5x SpeedThe analytics category is being restructured around natural-language agents rather than dashboards: ThoughtSpot rebranded its entire product as an autonomous analytics agent called Spotter, and Databricks reported migrating 1,300 internal dashboards to its AI/BI platform in five months with 5x faster performance than legacy tools. Instead of navigating a report, users ask a question and an agent finds the data, writes the query, runs it, and explains the result. This directly threatens the Tableau/Looker/Mode dashboard-building workflow — the value shifts from the visualization layer to the reasoning layer.

Graph relationships

USES
Claude Code
pro-workflow is designed for Claude Code
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USES
Claude Code
pro-workflow provides self-correcting memory that compounds over 50+ Claude Code sessions
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SUPPORTS
Cursor
pro-workflow works across Cursor and 32+ agents.
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SUPPORTS
Claude Code
pro-workflow captures corrections to Claude Code and stores them in SQLite database.
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USES
Claude Code
pro-workflow provides self-correcting memory for Claude Code
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BUILT BY
rohitg00
rohitg00 created pro-workflow
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Source trail

arXiv Product Hunt SaaStr AI Agent Store Tech Times Microsoft for Go Developers (devblogs.microsoft.com)GitHub TechCrunch Product Hunt Atlassian 8-K (SEC)SaaS Mag Knowi

Graph sources

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