Article URL: http://www.ft.com/content/8252d574-ae2a-4403-9cf9-031295ba67f5 Comments URL: https://news.ycombinator.com/item?id=49564397 Points: 9 # Comments: 0
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A developer has released Pistachio, an open-source command-line tool that manages PostgreSQL schemas declaratively, similar to how Terraform handles infrastructure. Users define their desired database schema in a single SQL file, and the tool automatically computes and applies the difference against the live database using a plan-then-apply workflow. Pistachio uses PostgreSQL's own parser via the pg_query_go library, keeping it lightweight while supporting a broad range of objects including tables, views, enums, triggers, functions, and row-level security policies. The tool was created after the author found existing alternatives like sqldef and pgschema either lacked SQL compatibility or required a heavier embedded PostgreSQL setup. To adopt it on an existing database, users can run a single dump command to generate the initial schema file and manage all future changes from there.
India's Digital Personal Data Protection (DPDP) Act, 2023 is now in force, carrying penalties of up to ₹250 crore for violations such as loading trackers without user consent or storing personal data unencrypted. A developer has released an open-source CLI tool called @dpdp-india/audit that statically scans JavaScript and TypeScript codebases to flag non-compliant patterns, functioning similarly to ESLint but focused on privacy rules. The tool covers 13 rules, detecting issues ranging from unguarded Google Analytics and Facebook Pixel loads to bulk data exports lacking audit trails. It also ships with a ready-to-use Next.js consent system, including a banner component and a consent-aware script loader, so developers can remediate flagged issues quickly. The package additionally supports SARIF output for integration with GitHub Code Scanning and can be configured to fail CI builds when violations are detected.
A governance guide published on DEV Community by MAREF architect 11-Shao argues that organizations must define their governance boundaries before selecting an AI Agent framework, not the other way around. The guide breaks Agent governance into four layers: identity and permissions, behavioral norms, audit and traceability, and policy evolution, warning that most teams focus only on the first layer. It distinguishes between two framework types — embedded governance, which intercepts Agent actions in real time, and bypass governance, which operates as an external service — recommending each for controlled and open environments respectively. Five evaluation criteria are outlined, including native support for human-in-the-loop approvals, separation of policy from code, causal completeness of audit logs, multi-Agent isolation, and a defined failsafe mechanism. The author notes that MAREF uses LangGraph for its core decision pipeline due to its state-machine model and interrupt mechanism, while supplementing it with an external governance layer for untrusted environments.
A personal essay published on jennywanger.com explores how the author experienced burnout even while working a reduced three-day week. The piece challenges the common assumption that shorter working hours automatically prevent exhaustion or overwork. The author reflects on the factors that contributed to their burnout despite having more free time than a typical full-time worker. The article has gained modest attention on Hacker News, prompting discussion about the nature of burnout beyond just hours worked.
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