AlphaSense

PostgreSQL for Data Engineers: Indexes & Bulk Loads

This technical guide outlines practical PostgreSQL patterns for production data pipelines, focusing on operations that determine whether scheduled jobs succeed. It compares Python-to-Postgres loading methods (pandas.to_sql, psycopg2.execute_values, psycopg2.COPY) and recommends COPY for large backfills and execute_values for incremental writes. The article covers idempotent upserts with ON CONFLICT (including IS DISTINCT FROM to avoid unnecessary updates), index types and when to use B-tree, GIN, BRIN, partial and expression indexes, and how to read EXPLAIN ANALYZE. It also discusses window functions for time-series, CTE inlining behavior, JSONB indexing, pgvector for embedding search (HNSW vs IVFFlat), materialized views, table partitioning, routine maintenance (VACUUM/ANALYZE, autovacuum), practical pipeline schema patterns, and connection-pool settings for robust pipelines.

AI-Powered Competitive Intelligence Playbook

This MarTech article (published 2026-05-29) outlines a practical playbook for using AI to move competitive intelligence from reactive monitoring to proactive strategy. The author argues teams should stop producing rearview reports and instead focus on answering three repeatable questions — What does this mean for us? Where are we exposed? Where’s the opening? — while delegating large-scale data collection to AI. The piece describes a two-layer stack: Layer 1 (monitoring) — dedicated CI platforms such as Crayon, Klue (which acquired Ignition in late 2025), Kompyte, AlphaSense, Contify, Similarweb and Owler — and Layer 2 (synthesis) — general-purpose LLMs and research engines such as Anthropic’s Claude (and Claude Cowork, GA April 2026), Perplexity, and ChatGPT. The article includes recommended workflows, tool pricing ranges for enterprise/mid-market, and step-by-step adoption advice for teams starting with a single competitor.

AI writing tic 'It's not just X — it's Y' surges

TechCrunch reports that the sentence construction “It’s not just this — it’s that” has become a widespread pattern in AI-generated writing and has notably increased in corporate communications. Citing a Barron’s analysis of AlphaSense’s database, mentions of the construction rose from roughly 50 in 2023 to over 200 in 2025. The piece lists corporate examples (Cisco, Accenture, Workday, McKinsey, Microsoft) and notes em-dashes as another stylistic marker associated with generative text. Max Spero, CEO of AI detection firm Pangram, is quoted saying the construction’s base rate is high enough that its presence alone is not definitive proof of AI use. The article, by Amanda Silberling, frames the trend as symptomatic of broader reliance on generative AI in corporate writing while acknowledging uncertainty about whether specific passages were AI-assisted.