---
title: "Latest reads"
description: "The engineering internet, summarised so you can actually read it."
---

# Latest reads
> The engineering internet, summarised so you can actually read it.

## Articles

### [Tangle: An open-source ML experimentation platform built for scale (2025) - Shopify](https://yomu.fyi/post/tangle-an-open-source-ml-experimentation-platform-built-for-scale-2025.md)
- Company: [Shopify](https://yomu.fyi/company/shopify.md)
- Author: 2023-10-18
- Published: Dec 5, 2025
- Type: Announcement

Shopify introduces Tangle, an open-source, platform-agnostic machine-learning experimentation platform built for Search and Discovery workflows at commerce scale. It targets six stated failure modes, including repeated data preparation, poor reproducibility, slow deployment, unstructured notebooks, manual query tracking, and limited sharing. Users compose visual directed acyclic graph pipelines from reusable YAML components that wrap containerized or inline command-line programs in multiple languages, while file-based execution moves artifacts through storage. Tangle’s content-based caching reuses results when output content hashes remain identical, including artifacts from still-running executions, rather than relying only on lineage changes. Shopify reports a ten-hour pipeline completing in twenty minutes after one component changes, more than a year of compute time savings, and production use across ranking, semantic search, recommendation, and feature engineering workloads.


### [Introducing swift-huggingface: The Complete Swift Client for Hugging Face](https://yomu.fyi/post/introducing-swift-huggingface-the-complete-swift-client-for-hugging-fa.md)
- Company: [Hugging Face](https://yomu.fyi/company/hugging-face.md)
- Author: Mattt
- Published: Dec 5, 2025
- Type: Announcement

Hugging Face released swift-huggingface, a dedicated Swift package offering complete Hub API integration, reliable file downloads, and inference provider access. The library addresses previous limitations in swift-transformers 1.0, where interrupted multi-gigabyte model downloads could not resume and cache structures differed from Python. To resolve cache duplication, swift-huggingface implements a Python-compatible content-addressed storage layout using symlinks and flock file locking. Authentication is standardized through a TokenProvider pattern supporting auto-detection, Keychain integration, static CI/CD tokens, and OAuth 2.0 sign-in with automatic token refresh. The package also provides URLSession-backed snapshot downloads with granular progress tracking and will soon replace the HubApi implementation inside swift-transformers.


### [PaaS + IaaS: Heroku and AWS for Cloud-Native Enterprise Agility](https://yomu.fyi/post/paas-iaas-heroku-and-aws-for-cloud-native-enterprise-agility.md)
- Company: [Heroku](https://yomu.fyi/company/heroku.md)
- Author: Gillian Gual Hinkle
- Published: Dec 4, 2025
- Type: Problem & solution

Modern enterprises can combine AWS IaaS infrastructure scale with Heroku’s managed PaaS to reduce operational work and developer cognitive load while retaining control for specialized workloads. Heroku supports Git-based deployment, managed services including Apache Kafka and Heroku Postgres, polyglot applications, and isolated environments such as Private Spaces and Shield Private Spaces. In Salesforce’s example, five applications serving more than 76,000 employees used Heroku to cut expense approval time from two days to two hours and recover $2 million in unused licenses. The architecture also combines Heroku AppLink, Heroku Connect, Heroku Fir’s OpenTelemetry support, and managed Dynos, while AWS remains the stated choice for highly specialized AI training requiring raw GPU access.


### [Improving Cursor’s agent for OpenAI Codex models](https://yomu.fyi/post/improving-cursor-s-agent-for-openai-codex-models.md)
- Company: [Cursor](https://yomu.fyi/company/cursor.md)
- Author: Cursor
- Published: Dec 4, 2025
- Type: Problem & solution

Cursor describes adapting its agent harness for OpenAI's latest frontier coding model, GPT-5.1-Codex-Max, by pairing model-familiar instructions with Cursor-specific tools and tuning against Cursor Bench. The Codex integration adopts a more shell-forward design, aligns tool names with commands such as rg, explicitly prefers tools over shell commands, and uses sandboxing to limit unauthorized file and network access. It also limits reasoning summaries to one or two sentences, gives literal guidance for invoking read\_lints after substantive edits, removes mid-turn user-communication language, and biases the agent toward taking action unless a plan is requested. Preserving Responses API reasoning items is treated as critical: Cursor reports a 30% performance drop for GPT-5-Codex when traces were removed, compared with OpenAI's observed 3% SWE-bench degradation for GPT-5, while prompt-ordering lessons led it to remove wording that discouraged ambitious work.


### [Building production-ready Stripe subscriptions using Kiro powers](https://yomu.fyi/post/building-production-ready-stripe-subscriptions-using-kiro-powers.md)
- Company: [Stripe](https://yomu.fyi/company/stripe.md)
- Author: Kalyani Koppisetti
- Published: Dec 4, 2025
- Type: Tutorial

Kiro's Stripe power is presented as a way to build a production-ready SaaS subscription flow while avoiding the fragmented output common with generic coding assistants. Using a natural-language specification for three monthly tiers and a three-month one-time option, Kiro creates a React frontend, Node.js backend API, CDN-hostable static assets, and server-side Stripe Checkout Session creation. The integration includes Stripe-specific steering files, MCP servers, and hooks, while the webhook handler preserves the raw request body, verifies HMAC signatures with stripe.webhooks.constructEvent(), rejects invalid events with HTTP 400, and routes lifecycle events such as checkout completion and subscription cancellation. The post concludes that this provides a secure, scalable foundation while leaving teams to customize business logic, including access provisioning and deprovisioning, instead of building payment infrastructure from scratch.


### [DeepMath: A lightweight math reasoning Agent with smolagents](https://yomu.fyi/post/deepmath-a-lightweight-math-reasoning-agent-with-smolagents.md)
- Company: [Hugging Face](https://yomu.fyi/company/hugging-face.md)
- Author: Daniel Fleischer, Moshe Berchansky, Moshe Wasserblat
- Published: Dec 4, 2025
- Type: Problem & solution

Mathematical reasoning in large language models often suffers from lengthy chain-of-thought traces and frequent arithmetic mistakes. To address these issues, DeepMath pairs a Qwen3-4B Thinking base model with a sandboxed Python execution environment built using the smolagents library and vLLM backend. The system offloads deterministic calculations by emitting concise Python snippets, executing them safely with restricted module imports and no network access, and folding returned values back into the context. Training utilizes Group Relative Policy Optimization on the Tool-Integrated Reasoning subset of OpenMathReasoning with temperature scheduling and length constraints. Across benchmarks including MATH500, AIME, HMMT, and HLE, DeepMath reduces output token lengths by up to 66% while increasing overall problem-solving accuracy.


### [We Got Claude to Fine-Tune an Open Source LLM](https://yomu.fyi/post/we-got-claude-to-fine-tune-an-open-source-llm.md)
- Company: [Hugging Face](https://yomu.fyi/company/hugging-face.md)
- Author: ben burtenshaw, shaun smith
- Published: Dec 4, 2025
- Type: Tutorial

Hugging Face Skills equips coding agents like Claude Code, OpenAI Codex, and Google's Gemini CLI to manage end-to-end language model fine-tuning. Using the hf-llm-trainer skill, an agent validates dataset formats, selects cloud hardware, configures authentication, and submits jobs to Hugging Face Jobs. Supported techniques include Supervised Fine-Tuning (SFT), Direct Preference Optimization (DPO), and Group Relative Policy Optimization (GRPO) for models ranging across various parameter sizes. The integration incorporates Trackio for real-time monitoring and automates LoRA configuration for larger models. Once training completes, the agent pushes artifacts to the Hugging Face Hub and can convert models to GGUF format for local execution.


### [Engineering the right opportunities for Thumbtack Pros.](https://yomu.fyi/post/engineering-the-right-opportunities-for-thumbtack-pros.md)
- Company: [Thumbtack](https://yomu.fyi/company/thumbtack.md)
- Author: Ashmannsyngle
- Published: Dec 3, 2025
- Type: Explainer

Ashmann Syngle, a backend software engineer on Thumbtack's Pricing team, focuses on systems that connect local service professionals with homeowners. To improve matching and revenue operations, the team recently deployed new pricing features, launched experiments, and partnered closely with Data Science and Monetization Experience groups. Current engineering efforts center on infrastructure enhancements, specifically upgrading alerting and monitoring across owned services to raise system reliability and operational efficiency. Because the team maintains complex monetization systems within a codebase that has evolved over many years, engineers conduct deep system analyses to evaluate edge cases before implementing foundational platform modifications. Thumbtack supports these initiatives through a virtual-first operational model complemented by regular in-person offsites.


### [Behind the build: 2025's BFCM globe in a pinball machine 🌎🕹️](https://yomu.fyi/post/behind-the-build-2025-s-bfcm-globe-in-a-pinball-machine.md)
- Company: [Shopify](https://yomu.fyi/company/shopify.md)
- Author: 2023-10-18
- Published: Dec 3, 2025
- Type: Explainer

The 2025 BFCM live globe was implemented inside a browser-based pinball machine to represent real-time merchant sales and celebrate milestones. Built with three.js and react-three-fiber, the experience runs at 120fps, uses Server-Sent Events for order arcs and live metrics, includes a 128x32 shader-driven dot-matrix display, and supports AR through react-three/xr. For performance, the team simulated pinball physics in 2D with Rapier2D and used raycasts for ramps and elevation, reducing the physics step from 2ms to 0.2ms. The scene also includes interactive mini games, infrastructure statistics, Easter eggs, and milestone-triggered reactions, while Apache FlinkSQL pipelines process event streams behind the commerce visualizations. The globe was also displayed on the Exosphere in Las Vegas for the third consecutive year.


### [2026 customer service planning series: Vol. 03](https://yomu.fyi/post/2026-customer-service-planning-series-vol-03.md)
- Company: [Intercom](https://yomu.fyi/company/intercom.md)
- Author: Declan Ivory
- Published: Dec 2, 2025
- Type: Explainer

AI performance in customer support can drift without clear ownership, even when the underlying model is capable. This part of a 2026 planning series presents four roles: AI operations lead, knowledge manager, conversation designer, and support automation specialist. The roles cover monitoring and guardrails, structured and compliant knowledge, conversational tone and flow, and reliable action through backend systems, with the AI operations lead coordinating reporting and improvement. The post describes an operating loop in which performance patterns drive knowledge fixes, interaction changes, and expanded automation, while phased ownership moves from part-time assignments to formal roles and hiring. It says dedicated specialization becomes essential when AI handles 50–70% of incoming volume, and frames these roles as the backbone of an AI-first support organization.


### [How Ramp built an AI operating system for scalable work](https://yomu.fyi/post/how-ramp-built-an-ai-operating-system-for-scalable-work.md)
- Company: [Notion](https://yomu.fyi/company/notion.md)
- Author: Drew Evans
- Published: Dec 2, 2025
- Type: Problem & solution

Ramp spent the last year building what operations and AI product leader Ben Levik calls an “AI operating system” for the company, with the goal of becoming more productive. Rather than waiting for tools to mature, Ramp promotes a “Builder” mindset and organizes adoption around Prompt, Knowledge, and Workflow. Employees refine vague requests by having AI ask clarifying questions, while a Notion knowledge base connected to other tools uses feedback loops in which AI drafts corrections and humans approve them. AI agents and connectors then automate tasks such as summarizing project updates from five sources and researching prospects for review-ready sales emails. About 90% of 1,200 employees use Notion AI monthly, and Ramp reports shipping 270 features in the first half of 2025, more than during all of 2024, shifting the bottleneck toward choosing what to automate next.


### [Streamlining Security Investigations with Agents](https://yomu.fyi/post/streamlining-security-investigations-with-agents.md)
- Company: [Slack](https://yomu.fyi/company/slack.md)
- Author: Dominic Marks
- Published: Dec 1, 2025
- Type: Problem & solution

Slack's Security Engineering team handles billions of daily security events and needed a reliable way to streamline on-call alert triage. An initial prototype relying on a single 300-word prompt produced inconsistent results and frequently reached spurious conclusions without properly challenging assumptions. To gain precise control, the team decomposed the workflow into chained model invocations with structured JSON outputs organized across three agent personas: a Director, four domain experts, and a Critic. Domain experts gather raw evidence through tool calls, the Critic evaluates finding quality and synthesizes a timeline, and the Director steers investigation phases using tiered model costs. The multi-agent system enables engineers to supervise investigations via a real-time dashboard while uncovering emergent issues like credential exposures across process ancestry chains.


### [A Decade of Defense: Celebrating Grab's 10th Year Bug Bounty Program](https://yomu.fyi/post/a-decade-of-defense-celebrating-grab-s-10th-year-bug-bounty-program.md)
- Company: [Grab](https://yomu.fyi/company/grab.md)
- Author: Pei Shan Yap
- Published: Dec 1, 2025
- Type: Announcement

Grab marks the tenth anniversary of its bug bounty program, launched with HackerOne and initially involving 23 researchers. Over the decade, it grew into a global community, partnering with more than 850 active HackerOne researchers to help protect over 187 million users across Southeast Asia. The program broadened its scope in 2023–2024, adding assets that included Indonesian financial services and AI systems, while introducing a mobile-specific bounty table and experimenting with campaigns and reward methods. Grab says it now ranks among HackerOne’s top 20 programs worldwide and top three in Asia, and credits live hacking events and regional club campaigns with expanding testing coverage and researcher relationships. Anniversary activities included invite-only campaigns in Germany, Morocco, and India, plus a broader campaign that received 461 submissions, with xchopath receiving the Best Hacker Bonus.


### [Transformers v5: Simple model definitions powering the AI ecosystem](https://yomu.fyi/post/transformers-v5-simple-model-definitions-powering-the-ai-ecosystem.md)
- Company: [Hugging Face](https://yomu.fyi/company/hugging-face.md)
- Author: Lysandre, Arthur Zucker, Cyril Vallez, Vaibhav Srivastav
- Published: Dec 1, 2025
- Type: Announcement

Transformers v5.0.0rc-0 introduces major architectural updates focused on simplicity, training, inference, and ecosystem interoperability across modern AI workflows. The release adopts a modular modeling approach and centralizes attention implementations into a unified AttentionInterface abstraction to reduce contribution and code review overhead. Support for Flax and TensorFlow is officially sunset in favor of focusing on PyTorch as the primary backend, while tokenization is standardized around the tokenizers library. For execution workloads, v5 adds native continuous batching, paged attention mechanisms, and a dedicated transformers serve OpenAI-compatible serving system. Finally, weight loading is refactored to make low-precision quantization a first-class citizen alongside broad interoperability with formats such as GGUF, MLX, and TorchAO.


### [Social Media Posting Schedule: 9-Step Guide](https://yomu.fyi/post/social-media-posting-schedule-9-step-guide.md)
- Company: [Brandwatch](https://yomu.fyi/company/brandwatch.md)
- Author: Sandra Busch
- Published: Nov 27, 2025
- Type: Tutorial

Managing multiple social accounts makes consistency, timing, content mix, and collaboration difficult, so the guide presents a nine-step scheduling process. It recommends auditing active and dormant channels, defining goals and KPIs, studying audience behavior and platform differences, selecting a tool, and building a calendar around content pillars, campaigns, roles, and a two-to-four-week planning horizon. The process then covers batch creation, reusable assets, platform-specific captions, approval workflows, analytics, time zones, and flexibility for timely content; Brandwatch Publish is presented as an example supporting TikTok, Instagram, Facebook, X, LinkedIn, and Pinterest. It concludes that scheduling should create capacity for engagement and strategy without sacrificing authenticity, and advises regular audits, experimentation, and readiness to pause or adapt queued posts. The guidance also warns against excessive promotion, ignoring engagement, identical cross-platform posts, weak visuals, and over-reliance on automation.


### [More context, more confidence: The new CX Score explained](https://yomu.fyi/post/more-context-more-confidence-the-new-cx-score-explained.md)
- Company: [Intercom](https://yomu.fyi/company/intercom.md)
- Author: Christine Zdelar
- Published: Nov 26, 2025
- Type: Announcement

CX Score was created to give support teams a broader view of customer experience than survey-based measures such as CSAT and NPS, which capture only a subset of interactions. Its latest iteration evaluates more of each conversation, combining answer quality for Fin and human teammates with customer effort, strong emotion, product or service feedback, and policy feedback. The update also expands scoring to shorter and more transactional threads, adds reasons behind individual ratings, and enriches summaries with the issue, handling, and drivers of the score. The stated goal is to help teams identify operational problems, route conversations for review or follow-up, and move from measurement toward continuous improvement. The new version is rolling out gradually to all customers and is scheduled to be in workspaces by December 3rd.


### [Real-time data quality monitoring: Kafka stream contracts with syntactic and semantic test](https://yomu.fyi/post/real-time-data-quality-monitoring-kafka-stream-contracts-with-syntacti.md)
- Company: [Grab](https://yomu.fyi/company/grab.md)
- Author: Yuanzhe Liu
- Published: Nov 26, 2025
- Type: Problem & solution

Kafka stream data can fail syntactically when actual records do not match expected schemas, or semantically when fields violate agreed patterns, ranges, or constants. The described platform addresses this gap with user-defined data contracts covering schema agreements, field-level semantic rules, stream configuration, and ownership metadata. An LLM recommends semantic rules from schemas and anonymized samples, while a transformation engine converts them into Test Runner configurations and inverse SQL queries. A long-running FlinkSQL Test Runner reads Kafka with its own consumer group, publishes issue events and stores them in AWS S3; Genchi sends Slack alerts and Coban shows violating fields and sample records. Deployed across 100+ critical topics, the solution provides real-time detection, alerting, and visibility, with future work targeting producer tracing, cross-field tests, completeness, freshness, and DTO change detection.


### [Reducing experiment duration with predicted control variates](https://yomu.fyi/post/reducing-experiment-duration-with-predicted-control-variates.md)
- Company: [Etsy](https://yomu.fyi/company/etsy.md)
- Author: Kelly McManus
- Published: Nov 25, 2025
- Type: Explainer

Etsy describes how its experimentation platform evolved from CUPED to CUPAC to shorten the time needed to reach statistically powered results. CUPED uses pre-experiment visitor data as covariates in linear regression, while CUPAC first uses a nonlinear model to predict the outcome and then uses that prediction in the variance-reduction correction. Etsy trained and tuned LightGBM models on more than 100 pre-experiment features in Vertex AI, generating predictions through parallel Dataflow jobs and applying the correction with Spark within an Airflow-orchestrated pipeline. CUPED reduced variance by 7% on average, whereas CUPAC achieved 27%, shortening average experiment duration by almost three additional days, although results ranged from 2% to 77% depending on the metric and experiment; Etsy is balancing CUPAC’s impact against its training and maintenance costs.


### [2026 customer service planning series: Vol. 02](https://yomu.fyi/post/2026-customer-service-planning-series-vol-02.md)
- Company: [Intercom](https://yomu.fyi/company/intercom.md)
- Author: Declan Ivory
- Published: Nov 25, 2025
- Type: Explainer

When AI Agents resolve most customer conversations, support organizations need to move beyond tiered models centered on queues, handoffs, and volume-based productivity. The proposed AI-first operating model distributes four foundational responsibilities: an AI operations lead monitors and improves performance, a knowledge manager maintains structured content, a conversation designer shapes communication and handoffs, and a support automation specialist builds executable workflows. Existing enablement, QA, workforce management, and leadership roles also evolve, with player-coach leaders managing both AI performance and people. Examples from Dotdigital, Clay, Lightspeed, and Intercom illustrate dedicated roles and an Intercom structure organized around Human Support, AI Support, and Support Operations and Optimization.


### [200+ Social Media Holidays 2026: Monthly Calendar](https://yomu.fyi/post/200-social-media-holidays-2026-monthly-calendar.md)
- Company: [Brandwatch](https://yomu.fyi/company/brandwatch.md)
- Author: Gemma Joyce
- Published: Nov 25, 2025
- Type: Explainer

The calendar assembles more than 200 social media holidays, events, and suggested hashtags for 2026, giving content teams prompts to use throughout the year. It organizes occasions month by month, from New Year’s Day, Science Fiction Day, and Data Privacy Day in January to Halloween, Cyber Monday, and New Year’s Eve later in the year. Entries span awareness observances, cultural and religious dates, seasonal milestones, and lighter themes such as National Pizza Day, World Emoji Day, and National Cookie Day. The list is intended to add variety to social media strategies, and the post points readers to separate monthly roundups with examples of brand posts and additional ideas. Its conclusion presents the calendar as a source of content inspiration for increasing marketing activity in 2026.


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