agents Archives

Tech Optimizer

July 30, 2026

Generating Referentially Consistent Synthetic Test Data for PostgreSQL in .NET Application Modernization

Satyajit Gokhale, Aiswaryaa Venugopalan, Ruchi Agarwal, Nits Jeganathan, Khurram Khawaja, Vijay Mandadi, and Luke Huan contributed to this article. AWS Transform offers a .NET application modernization service that allows enterprise customers to migrate from Microsoft SQL Server to Amazon Aurora PostgreSQL Compatible Edition. This migration reduces licensing costs and enhances scalability while utilizing an open-source ecosystem. Schema conversion tools can assist in translating DDL to PostgreSQL-compatible definitions, but correctness must be verified by teams to ensure performance under real-world workloads. Traditional testing methods, such as using production data or manual checks, are not scalable and raise privacy concerns. Therefore, there is a need for realistic synthetic data generated at scale that adheres to the migrated schema's constraints. AWS Transform for SQL Server modernization employs an AI agent to generate constraint-respecting synthetic data at scale during the migration workflow. This process involves loading the PostgreSQL schema into a live database, constructing a dependency graph for data generation, and distributing tasks across multiple sub-agents. The agent validates each generated INSERT against the live database, ensuring compliance with constraints and providing error diagnostics for any violations. The synthetic data generation workflow consists of four stages: schema analysis, establishing generation order, distributing tasks across sub-agents, and validation with error recovery. The agent extracts metadata from the PostgreSQL schema, determines a valid table generation sequence, parallelizes data generation while maintaining referential integrity, and generates and validates data row-by-row against the live database. Each successful insertion enriches the context for subsequent generations, while errors are handled through structured diagnostics and iterative regeneration. The process ensures referential integrity and preserves the generation state, allowing for recovery from interruptions without data loss.

Tech Optimizer

July 30, 2026

EDB Says Postgres AI Tops Enterprise AI Data Platform Benchmarks

EnterpriseDB (EDB) has released benchmark results for its EDB Postgres AI (EDB PG AI), showing superior performance compared to various AI data platforms, including vector databases and managed Postgres platforms. The independent testing by McKnight Consulting Group indicated that EDB PG AI outperformed competitors in all evaluated metrics, including query speed, accuracy, and cost efficiency. Key findings include: - EDB PG AI achieved a median query latency of 50 milliseconds at 50 million vectors, making it the fastest platform tested, 80 times faster than Databricks and 21 times faster than MongoDB Atlas. - It demonstrated the highest accuracy for core vector search with a recall rate of 0.911, outperforming MongoDB by 26% and Databricks by 17%. - In a concurrent agent loop test, EDB PG AI completed tasks in 27 milliseconds, significantly faster than MongoDB Atlas (699 milliseconds) and Databricks (5.1 seconds). - EDB PG AI provided 76 times better price performance than Databricks and 34 times better than MongoDB. - The platform integrates vectors, structured data, and analytics within a single operational database, enhancing efficiency and reducing the risk of data inconsistency. The benchmark study assessed the performance of EDB PG AI against Amazon Aurora PostgreSQL, Databricks, Crunchy Bridge, MongoDB Atlas, and open source PostgreSQL, all standardized on equivalent enterprise hardware.

Tech Optimizer

July 29, 2026

After rewriting SQLite in Rust, Turso turns its sights on Postgres

Cloud database provider Turso is developing a Postgres-compatible implementation based on its SQLite-compatible database, which was created from scratch in Rust. CEO Glauber Costa believes Postgres can benefit from modernization for cloud-native applications. Turso's SQLite reimplementation, now called Turso, uses a virtual machine architecture that may eventually support other database frontends, including MySQL and Redis. The company initially forked SQLite into libSQL but later pivoted to a cloud service named Turso. They focused on a virtual machine architecture for their rewrite, which translates SQL queries into a custom bytecode language. Turso has developed a Postgres-compatible prototype named pgmicro, which aims to run existing applications with minimal modifications. The company is also working on a database-as-a-cloud service that will allow customers to use various database types on the Turso platform.

Tech Optimizer

July 29, 2026

EDB Postgres® AI Outperforms Vector Databases, Lakehouses, and Document Stores for Agentic AI on Speed, Accuracy, and Cost

EDB Postgres AI is a pioneering solution that integrates intelligence and data on a unified sovereign foundation, eliminating the need for ETL processes, data duplication, and separate vector stores. Independent benchmarks show that EDB Postgres AI outperforms competing platforms in speed, accuracy, and cost-effectiveness. A study by McKnight Consulting Group indicates that EDB Postgres AI excels in key performance metrics, including query latency, accuracy, cost, and data freshness, outperforming specialized vector databases and other managed Postgres platforms. EDB Postgres AI achieves median query latencies of 50 milliseconds at a scale of 50 million vectors, making it 80x faster than Databricks, 21x faster than MongoDB Atlas, and up to 2x faster than alternatives like Aurora and Crunchy Bridge. It also delivers the highest recall rates for core vector searches, surpassing competitors like MongoDB and Databricks. In tests involving concurrent retrievals, EDB Postgres AI completed a three-arm agent loop in 27 milliseconds, significantly faster than other platforms. In terms of cost efficiency, EDB Postgres AI offers 76x better price performance than Databricks, 34x better than MongoDB, and 23%–28% better than the nearest managed Postgres competitors when considering query speed. The architecture of EDB Postgres AI allows for the integration of vector, filtered, and full-text retrieval in a single query path, ensuring real-time data access and eliminating the need for separate systems.

Winsage

July 28, 2026

I’m worried that Windows 11 will slowly turn into a subscription-based OS, and AI agents will be to blame

Concerns about Microsoft's future monetization strategy for Windows suggest a potential shift from a one-time payment model to a subscription-based system. This aligns with a broader trend among tech companies favoring recurring revenue. Recent AI developments, such as the transition from the free Deep Research feature to the subscription-based Researcher, indicate a move towards monetizing AI functionalities. Additionally, features like Microsoft Whiteboard and Outlook's Meeting Insight now require paid subscriptions. Microsoft plans to introduce AI agents in Windows 11, which may also be gated behind paywalls, leading to a modular operating system with optional paid features. Speculation exists about a tiered subscription model, including a free version that could become ad-supported. However, uncertainties remain regarding user acceptance and the perceived value of AI features, which could impact the success of such a transition.

Tech Optimizer

July 27, 2026

Hackers are hiding malware behind AI agents that antivirus cannot see

Sergey Lozhkin, head of Kaspersky’s global research and analysis team for the Asia-Pacific, Middle East, Turkey, and Africa, reported an increase in malware injection attacks targeting AI agents, particularly from outside an organization’s network. He noted that traditional signature-based analysis is becoming ineffective as AI skills operate in the cloud, connecting to external resources. Dmitry Galov, leading Kaspersky’s research for Russia and the CIS, emphasized the importance of behavioral analysis and sandboxing AI applications to combat these threats. Lozhkin warned that the rapid growth of skills and plugins requires organizations to adopt innovative security measures, as old models are no longer sufficient.

Tech Optimizer

July 23, 2026

Simplify AI agent orchestration with Lakebase Postgres

The auditing process has traditionally been labor-intensive, requiring extensive document reviews. CLA (CliftonLarsonAllen LLP) partnered with the Databricks Forward Deployed Engineering team to develop a document processing application that reduces extraction time from hours to minutes while maintaining quality. The application is built on the Databricks platform, utilizing technologies like Lakebase Postgres, Databricks Apps, Lakeflow Jobs, MLflow, and Unity Catalog Volumes. The application addresses challenges in document parsing, including unpredictable per-task latency, rate-limit-aware throttling, workload prioritization, cost attribution per task, and real-time progress visibility. It eliminates the need for multiple specialized systems by integrating components such as a web application for user interaction, Lakebase for state management, an orchestrator for task management, and AI agents for document processing. The task queue is supported by two Postgres tables in Lakebase, tracking task status and execution attempts. Concurrency safety is ensured through a locking mechanism, and crash recovery is facilitated by lease-based locking. The orchestrator implements rate-limit-aware throttling and idempotent webhook callbacks to manage task processing effectively. An operator dashboard provides real-time metrics on task status, agent performance, and workload costs, with live updates through Postgres LISTEN/NOTIFY events. Cost attribution is managed at the application level, allowing for detailed monitoring of expenditures. Lakebase enhances the orchestration process with features like autoscaling compute, OAuth-rotated authentication, Unity Catalog integration, and support for branching and snapshots.

AppWizard

July 22, 2026

Feel less bad about firing AI agents, Minecraft creator says vibe coding will replace human developers

Markus ‘Notch’ Persson has announced a shift to "vibe coding," which involves using artificial intelligence tools for code generation. This decision is influenced by difficulties in hiring skilled programmers and a growing comfort with AI solutions. Notch expressed frustration with the job market, stating he has trouble hiring talented programmers and would feel less bad about firing a chatbot. He sold Mojang and Minecraft to Microsoft for .5 billion in 2014 and is now working on a new project, Levers and Chests, at Bitshift Entertainment, which will likely rely on AI tools. This shift occurs amid significant layoffs in the tech industry, including at major companies like Amazon, Oracle, and Microsoft. Notch's previous stance of rejecting AI contrasts with his current acceptance of its inevitability, reflecting a broader industry trend where leaders like Linus Torvalds and Ryan Dahl also acknowledge the transition towards AI-driven development.

AppWizard

July 22, 2026

Unity demonstrates ‘an Unreal character running through a Unity world’ for the first time

Unity has demonstrated a Unity Engine game operating within an Unreal Engine environment at the Unite Seoul keynote. This collaboration with Epic Games aims to allow Unity developers to publish games directly within Fortnite. Epic Games CEO Tim Sweeney expressed support for this integration, highlighting the importance of connectivity among game engines. Unity's Fortnite integration is set to enter early access in 2027, and Unity 7, the next version of its game engine, will be released next year, featuring enhanced rendering, improved monetization options, collaboration tools, and a protocol for integrating generative AI coding agents.

AppWizard

July 21, 2026

Unity 7 to release in 2027, helps devs “ship sharper graphics”

Unity 7 is set to launch after a beta testing phase in December 2026, with a full release expected in the first quarter of 2027. It introduces a public API and various services for better integration without full editor access, aiming to improve workflows in game development. Key features include faster shader builds, a near-instant Play Mode, and an upgrade path for Unity 6 users that requires no rebuilding. Unity 7 will also feature CoreCLR, dynamic global illumination through Surface Cache GI, and neural upscaling, available on all supported devices. Additionally, it will include built-in Vector tools for creating native webshops, allowing direct-to-consumer commerce. Collaboration features will enhance teamwork among developers and coding agents.