Ai agents

Your agents lack context: Here's how to fix "You're absolutely right!" — Brandon Waselnuk, Unblocked

Your agents lack context: Here's how to fix "You're absolutely right!" — Brandon Waselnuk, Unblocked

Brandon Waselnuk of Unblocked discusses the critical need for robust context engines in AI-driven software development. He explains how AI agents' lack of company-specific understanding leads to compounding costs like wasted tokens and rework. Waselnuk outlines common pitfalls in providing context and details six essential characteristics of an effective context engine, demonstrating its impact with a 50% token reduction and significant time savings. He also introduces three open-source tools from Unblocked, including a workshop to build a relational context engine, emphasizing that "access to information is not understanding" and that context, not intelligence, is the current bottleneck for AI effectiveness.

Why won’t AI agents just follow the rules?

Why won’t AI agents just follow the rules?

This podcast episode tackles critical cybersecurity issues in AI, examining why AI agents defy rules and the necessity of deterministic external controls. It highlights the severe lack of security in agentic skill marketplaces (OWASP Top 10), where "natural language is executable" and the "rush to market" overlooks basic hygiene. The discussion also covers how AI disrupts bug bounties, leading to lower payouts and "AI slop" reports, potentially pushing researchers to the dark market. Finally, it introduces ThreatXtension, an AI-powered open-source tool to detect malicious browser extensions.

How we built Grok Bot in a month | Roman Ugarte (SpaceXAI)

How we built Grok Bot in a month | Roman Ugarte (SpaceXAI)

Roman Ugarte, a key figure behind Grok Bot, shares insights into its rapid development, emphasizing the strategic choice to build it as a separate, cloud-first product with bots having their own dedicated 'computers.' The discussion highlights a "colleague-pilled" product philosophy focused on full delegation and constant reinvention, enabling the creation of autonomous AI teammates for both work and personal life.

Inside the Team That Killed Mandatory Code Review — Quinn Slack, AMP

Inside the Team That Killed Mandatory Code Review — Quinn Slack, AMP

Quinn from AMP discusses a paradigm shift towards cloud-native AI agents and remote development, advocating for the end of local development and traditional code review. He details how AMP's 'Orbs' enable parallel, secure, and remote execution, and how agents are transforming internal tools ('jellyware'), diminishing the role of GitHub and traditional CI/CD, and fostering a lean, high-trust company structure.

From coding to Knowledge work agents — Karan Vaidya, Composio

From coding to Knowledge work agents — Karan Vaidya, Composio

Karan Vaidya of Composio explains why AI agents have excelled in software engineering but struggle in other knowledge work domains. He identifies six critical primitives—centralization, history, context, verification, governance, and reversibility—that coding inherently provides but are largely absent in general knowledge work, hindering agent effectiveness and trust. The current bottleneck for AI agents is not the models, but the missing infrastructure around them.

Your company brain will leak secrets: how we stopped it for big banks — Tanmai Gopal, PromptQL

Your company brain will leak secrets: how we stopped it for big banks — Tanmai Gopal, PromptQL

Tanmai Gopal, co-founder of PromptQL and creator of Hasura GraphQL, shares insights on building secure and effective 'company brains' for AI agents. He highlights the surprising metric of a continuously rising edit count as a sign of health, dismisses common pitfalls like siloed knowledge, and proposes a human-in-the-loop, unified wiki approach with granular access control and dynamic credential injection to prevent leaks and foster collaborative knowledge creation.