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Major 2026 Tech Layoffs Citing AI

TechCrunch compiles a running list of major 2026 tech company layoffs where executives cited AI as a factor. The roundup notes roughly 120,000 tech roles cut in 2026 (according to Layoffs.fyi) and details large reductions at multiple large employers: Microsoft eliminated about 4,800 roles, Oracle disclosed a 21,000-headcount reduction over 12 months tied in part to AI, Meta cut ~8,000 roles while moving ~7,000 into AI-focused jobs, and Amazon cut 16,000 corporate positions. Other companies including GitLab, Intuit, Cisco, Cloudflare, Coinbase, PayPal, Snap, IBM, Atlassian, Dell, Block and Salesforce are listed with layoffs or restructurings explicitly linked to AI adoption, infrastructure shifts or organizational simplification. The piece highlights a broader industry pattern of rising revenues alongside workforce reductions attributed to AI-driven efficiency and role rebalancing.

Dirora: e-commerce platform with 68+ built-in features

Dirora is a multi-tenant e-commerce platform built around the principle that common merchant features should be included by default rather than sold as paid add-ons. The team designed a composable, API-first system composed of 40+ Go microservices, using PostgreSQL (system of record), Redis, and an S3-compatible object store, fronted by Traefik. Dirora offers a visual theme editor, headless/API-first capabilities, and a long list of native features (reviews, loyalty, subscriptions, multi-currency, B2B quotes, manufacturing, help desk, etc.). The platform charges no transaction fees and applies a declining platform fee (1.5% Starter → 0% Enterprise) across plans priced at £0, £19, £59 and £299/month. A live integrations directory includes accounting, fulfillment, analytics, social pixels and messaging tools; payments are processed via Stripe with support for Apple Pay, Google Pay, Klarna, Clearpay and PayPal.

Enterprise vs Startup AI APIs: Which Wins?

An engineer who built LLM pipelines and later joined Global API argues that the optimal AI API strategy depends on an organization's failure tolerance and cost profile. Startups typically benefit from a single aggregator (one key, predictable pricing, sandboxing) to avoid account friction, multiple MSAs, single-region risk and rate-limit cliffs; the author cites a 97.5% token-cost gap in a published example. Enterprises with >$5K/month inference spend should prioritise contractual SLAs, dedicated capacity, custom DPAs, Net-30 invoicing and multi-region deployment. The post describes a hybrid routing architecture (cheap default, mid-tier fallback, premium reserved routes), reliability metrics to monitor (p50/p95/p99, token throughput, 429/529 errors) and a decision framework mapping spend and operational needs to tiers (standard vs Pro Channel).