Clarveo is a trading coach tool that analyzes your trade history to identify expensive repetitive patterns, assigns them a name and cost, and provides one testable rule to improve. The service costs €39/month after a free trial and focuses on behavioral analysis rather than entry signals or win-rate promises.
An application security program should rest on four foundational legs: security by default (guardrails, tiered SAST rules, dependency management, threat modeling), reactionary security (deep-dive threat modeling for high-risk projects), secure development practices, and metrics-driven oversight. The approach shifts from triaging individual vulnerabilities to removing entire bug classes at scale, using AI tooling to filter false positives and automate routine checks so small teams can focus on systemic risk.
Attestly is a compliance documentation tool that automatically generates EU AI Act Annex IV technical documentation for high-risk AI systems by ingesting operational traces from deployed agents, linking evidence back to specific execution events, and producing audit-ready documentation drafts for human review.
Angelo is a portfolio intelligence workspace designed for angel investors, offering conversational AI assistance, multiple analytics views, performance metrics like DPI and IRR, and exposure tracking tools.
A design document is a planning tool that helps teams coordinate work and avoid costly implementation mistakes by articulating hard problems and key decisions before coding begins. The investment in a design doc should match project complexity, risk, and team coordination needs, with the key question being whether getting a decision wrong would be expensive to fix.
Algo-Trading-Skills is a community project providing 501 structured skills across 16 engineering domains to help AI agents avoid production failure modes in algorithmic trading systems. The skills map to regulatory frameworks (SEC, FINRA, MiFID II, FCA, ASIC, SEBI) and integrate with Claude Code, GitHub Copilot, and other AI tools, backed by over 20,000 unit tests.
Cognitive Debt describes the loss of human understanding of system components, distinct from technical debt. The article proposes a scoring method (1-3 scale for complexity and severity) to estimate the Cost of Cognitive Debt and determine appropriate levels of supervision for agentic workflows in software development.