Memory Leak
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Memory Leak

Memory Leak — #11

VC Astasia Myers’ perspectives on machine learning, cloud infrastructure, developer tools, open source, and security. Sign up here.

🚀 Products

Github Teases New Copilot Feature That Lets Developers Code With Their Voice

GitHub announced expansions to Copilot, the service that uses AI to help programmers write code. After launching Copilot in GA earlier this year, GitHub is now introducing Copilot for business, enabling whole teams to use the service. GitHub is serving access to the new voice feature via a waitlist that’s open for interested developers now, but essentially it will allow developers to activate Copilot’s ears via the “Hey, GitHub” wake word.

Why does this matter? According to GitHub, its new voice assistant can understand natural language requests for Copilot to suggest a code snippet or summarize what a specific section of code does. It can also help them navigate a codebase by saying something like, “Hey GitHub, go to line 34.” So far, the best application of voice technologies have been in consumer products like Siri and Alexa. Given Copilot has been tried by 1.2 million users, it will be interesting to see if Copilot becomes the first popular enterprise voice application.



Auth.js is an authentication solution for Next.js applications designed to support Next.js and Serverless. It features built-in support for popular services, web standard APIs, and SvelteKit. Auth.js is flexible and it works with any database, or even without one.

Why does this matter? Authentication is a key piece of security infrastructure. According to Gartner, the access management market is expected to reach $19 billion in 2024, up from $13.7 billion in 2021. Since Okta acquired Auth0 for $6.5 billion in 2021 we have seen a handful of developer-centric authentication services come to market. A few in particular have targeted the front-end community like Auth.js and


Hydra is an open source data warehouse built on Postgres. Hydra leverages columnar storage, vectorized execution, and query parallelization to efficiently serve online analytical processing of queries (OLAP). Unlike traditional warehouses, Hydra supports Postgres heap tables, indexing, and native partitioning to process high-throughput transactional writes, quick lookup and operational queries, and hybrid transactional / analytics processing workloads (HTAP).

Why does this matter? Postgres originally became popular as a transactional database. We’ve seen Supabase and Neon improve postgres ease of use. Timescale optimized it for time series and analytics. Now Hydra is evolving it to become a data warehouse for analytics. Teams are trying to get more leverage from postgres since it is a trusted well understood system.


📰 Content

AI-Generated Answers Temporarily Banned on Coding Q&A Site Stack Overflow

Stack Overflow has temporarily banned users from sharing responses generated by AI chatbot ChatGPT. “The primary problem is that while the answers which ChatGPT produces have a high rate of being incorrect, they typically look like they might be good and the answers are very easy to produce,” wrote the mods. “As such, we need the volume of these posts to reduce […] So, for now, the use of ChatGPT to create posts here on Stack Overflow is not permitted. If a user is believed to have used ChatGPT after this temporary policy is posted, sanctions will be imposed to prevent users from continuing to post such content, even if the posts would otherwise be acceptable.”

Why does this matter? Last week we discussed how ChatGPT broke the internet with individuals posting ChatGPT responses across social media. Stack Overflow’s ban underscores that ChatGPT answers are not always accurate and because they are easy to generate, misinformation could become a problem. We expect in the future more platforms will ban ChatGPT and other synthetic content generators to try to minimize misinformation and quality degradation. Perhaps platform will apply verification mechanisms for whether content is human-generated or synthetic.

The State of AI in 2022 — and a Half Decade in Review

McKinsey’s online survey was in the field from May 3 to May 27, 2022, and from August 15 to August 17, 2022, and garnered responses from 1,492 participants. Of those respondents, 744 said their organizations had adopted AI in at least one function and were asked questions about their organizations’ AI use. AI adoption has plateaued at ~50% the last few years. Today 52% of respondents at orgs using AI reported more than 5% their digital budgets, up from 40% in 2018.

Why does this matter? McKinsey’s report underscores that organizations are adopting AI and budgets are increasing. However, adoption isn’t strictly up and to the right. Robotic process automation, computer vision, natural-language text understanding, and virtual agents were the most popular AI capabilities embedded in products of business processes. We similarly hear that ML is more likely to be adopted in workflow automation solutions as compared to engineering teams building ML into end user product experiences.

Kim Maida’s How to Measure the Value of Developer Relations

Kim Maida is a group product manager focused on developer content at Okta. Her piece thoroughly describes how to measure developer relations across Reach, Awareness, Engagement, and DevRel Qualified leads. She encourages teams to pick a keystone metric like signups/registrations.

Why does this matter? I’m constantly asked by founders about developer relations. Maida’s piece does a wonderful job outlining different measurement techniques for developer relations and why each matter. It’s a must read.

💼 Jobs

⭐️Dragonfly — Developer Advocate (fully remote)

⭐️ Hex — Data Analyst

⭐️ Grit — Founding ML Engineer



VC Astasia Myers’ perspectives on machine learning, cloud infrastructure, developer tools, open source and security.

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Astasia Myers

Founding Enterprise Partner @ Quiet Capital, previously Investor @ Redpoint Ventures and Cisco Investments