Codetown
Codetown ::: a software developer's community
Walt Sellers's Discussions
Happy 10th year, JCertif!
Notes
Welcome to Codetown!
Codetown is a social network. It's got blogs, forums, groups, personal pages and more! You might think of Codetown as a funky camper van with lots of compartments for your stuff and a great multimedia system, too! Best of all, Codetown has room for all of your friends.
Created by Michael Levin Dec 18, 2008 at 6:56pm. Last updated by Michael Levin May 4, 2018.
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InfoQ Reading List
Article: Spec-Driven Development – Adoption at Enterprise Scale
Spec‑Driven Development shifts AI‑augmented software delivery from tactical prompting to collaborative intent articulation. Enterprises face gaps in tooling, workflow integration, multi‑repo coordination, and cross‑functional collaboration. Sustainable adoption requires treating specs as living, shared interfaces, and evolving organizational practices.
By Hari KrishnanGitHub Agentic Workflows Unleash AI-Driven Repository Automation
Recently launched in technical preview, GitHub Agentic Workflows introduce a way to automate complex, repetitive repository tasks using coding agents that understand context and intent, GitHub says. This enables workflows such as automatic issue triage and labeling, documentation updates, CI troubleshooting, test improvements, and reporting.
By Sergio De SimonePresentation: Panel: Modern Data Architectures
The panelists emphasize that data engineering is no longer just about "click-and-drag" UI tools; it is software engineering applied to data.
By Fabiane Nardon, Matthias Niehoff, Adi Polak, Sarah UsherHow Dropbox Built a Scalable Context Engine for Enterprise Knowledge Search
Dropbox engineers have detailed how the company built the context engine behind Dropbox Dash, revealing a shift toward index-based retrieval, knowledge graph-derived context, and continuous evaluation to support enterprise AI at scale
By Matt FosterUber and OpenAI Retool Rate Limiting Systems
Uber and OpenAI are replacing static rate limits with adaptive, infrastructure-level platforms. Uber’s Global Rate Limiter utilizes probabilistic shedding to manage 80M RPS, while OpenAI’s Access Engine implements a credit waterfall to prevent user interruptions. Both architectures utilize distributed enforcement and soft controls to maintain system stability and service continuity at scale.
By Patrick Farry
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