January 2015 Blog Posts (6)

Phone Software Entrepreneurs? Under 30 Forbes List

Forbes published an under 30 tech list featuring entrepreneurs who've made it big. Read about it …

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Added by Michael Levin on January 27, 2015 at 12:30pm — No Comments

Getting Started With Android

Interested in Android programming? Here's a nice, recent article at Lifehacker outlining good, free resources to get you going. http://lifehacker.com/i-want-to-write-android-apps-where-do-i-start-1643818268 ;

Added by Michael Levin on January 22, 2015 at 11:05am — No Comments

Pay What You Want: Back-End Developer Course Bundle

Pay What You Want: Back-End Developer Course Bundle…

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Added by Michael Levin on January 20, 2015 at 10:23am — No Comments

Speak at OSCON!

Here's a message from O'Relly about OSCON 2015:

We're deep into planning OSCON 2015 and we've got some exciting news: OSCON is changing. We're no longer beating the drum and…

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Added by Michael Levin on January 9, 2015 at 11:47am — No Comments

O'Reilly Solid Conference CFP closes 1/20!

The O'Reilly Solid conference is in San Diego in June and it's all about the merging of HW/SW for the IoT. Want to get involved? The Call for Papers is open and there are loads of benefits in giving a presentation for an O'Reilly conference., Take it from me! It's a great thing to do for the community and you learn a ton…

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Added by Michael Levin on January 9, 2015 at 9:30am — No Comments

How to Use SQL, Hadoop, Drill, REST, JSON, NoSQL, and HBase in a Simple REST Client

Our friend Carol just published this article.

SQL will become one of the most prolific use cases in the Hadoop ecosystem, according to Forrester Research. Apache Drill is an open source SQL query engine for big data exploration. REST services and clients have emerged as popular technologies on the Internet. Apache HBase is a hugely popular Hadoop NoSQL…

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Added by Michael Levin on January 7, 2015 at 1:45pm — No Comments

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InfoQ Reading List

Presentation: Building Evals for AI Adoption: From Principles to Practice

Mallika Rao discusses the hidden risk of evaluation debt in production AI systems, drawing on her experience at Twitter, Walmart, and Netflix. She explains why traditional metrics fail modern architectures, breaks down a five-layer evaluation stack spanning infrastructure and UX, and shares a diagnostic maturity model to help engineering leaders eliminate silent semantic failures.

By Mallika Rao

AI-Assisted Migration Tool Helps Teams Move from ingress-nginx to Higress in Minutes

The Cloud Native Computing Foundation has highlighted a new AI-assisted migration approach that enabled engineers to migrate 60 ingress-nginx resources to Higress in roughly 30 minutes, demonstrating how artificial intelligence is increasingly being applied to modernize Kubernetes networking and gateway infrastructure.

By Craig Risi

GitHub Slashes Agent Workflow Token Spend up to 62% with Daily Audits and MCP Pruning

GitHub reports cutting token costs in agentic CI workflows by up to 62% by pruning unused MCP tools, swapping some MCP calls for gh CLI, and running daily “auditor” and “optimizer” agents. A token-usage.jsonl artefact and an Effective Tokens metric help track spend across models and spot regressions.

By Mark Silvester

Presentation: From Founding Engineer to CTO to CEO – At the Same Startup

Trisha Ballakur discusses her journey from a backend software engineer to CTO and CEO, using her startup Pointz as a case study. She explains how to implement bottom-up customer discovery to find product-market fit, effectively delegate to global contractors to reduce build times, customize open-source repos like Valhalla, and apply engineering test-case models to business development.

By Trisha Ballakur

Accountability is the Goal for AI, with EU Regulations Supporting Transparency

AI bias mirrors human bias; both stem from our language and lived experiences. Ethics and AI are inseparable, but AI changes affordances, making harmful actions easier to carry out. The EU regulations apply to AI, since digital products are products. The ultimate goal is accountability: companies must ensure transparency, and laws should favor using the simplest AI that gets the job done.

By Ben Linders

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