A product discussed on AI Engineer.

Realtime multiplayer, automation, and you! — Idan Gazit, GitHub
Aug 8, 2026 · 21:41
Idan Gazit of GitHub Next presents two prototypes for the future of software development: agentic workflows, which turn plain-English instructions into automated, guardrailed maintenance tasks, and ACE, a cloud-based platform for real-time multiplayer coding. He shows how an agentic workflow upgraded his site from Astro 5 to Astro 7, reading changelogs, fixing breaking changes, verifying the build, and opening exactly one pull request, with permissions, tools, networks, and safe outputs declared in YAML front matter rather than prompts, since prompts can be prompt-injected and are not real guardrails. Secrets stay outside the agent's jail, and agents may "do nothing" to avoid noise. ACE runs sessions in cloud microVMs, looks like Slack, and lets teams edit a shared plan document together before telling the AI to "make the document true." He closes with a study of about 100 developers over thousands of hours showing typing is only about 5% of the job, so AI must help with the other 95%.

We Gave an Agent Production Code Access and Then Tried to Sleep at Night — Moritz Johner, Form3
Jul 20, 2026 · 21:57
Moritz Johner of Form3 explains that giving a coding agent production code access turns it into a supply chain actor, and the blast radius is an architecture decision. His team built PatchPilot to automate CVE patching across thousands of repositories, splitting it into a deterministic Go layer that handles dangerous operations (GitHub write access, CI triggering) and an agent layer that only edits files. The agent remediates vulnerabilities by bumping dependencies, verifying builds, and fixing CI failures, but a prompt injection could escape via the Docker socket, which kept him up at night. To contain that, they moved the agent into a firecracker microVM with its own kernel and separate network policies per layer. Johner argues that where you draw the line between deterministic and agentic code defines your security model, and warns that existing agent sandboxes are worthless when a Docker socket is involved.

GitHub's AI Powered Security Platform: Sarah Khalife
Feb 8, 2025 · 23:45
Sarah Khalife, Principal Solutions Engineer at GitHub, details how the company is weaving generative AI into GitHub Advanced Security (GHAS), focusing on code scanning auto fix (in public beta, with a 70% success rate on vulnerability fixes within pull requests), secret scanning enhancements such as AI-generated custom regex patterns and unstructured password detection (reducing false positives), and supply chain security via Dependabot. She demonstrates how AI enables faster remediation—detecting cross-site scripting and suggesting fixes before merge—and shows the security dashboard’s coverage view, which reveals that secret scanning covers 99% of repositories while code scanning only 57%. The talk emphasizes that AI shifts security from reactive to proactive, bridging the gap between AppSec teams and developers through shared responsibility and community driven improvements.
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