Sep 09, 2026

500 Skills, Zero Fine-Tuning: LinkedIn's Playbook for AI Agents — Ajay Prakash, LinkedIn

LinkedIn revolutionized its approach to AI agents by addressing the inherent limitations of LLMs in complex enterprise environments. Facing issues like hallucinations due to a lack of internal context, they developed a system of "playbooks" — structured, self-contained instructions published as tools. To scale beyond typical MCP limitations, they introduced three meta-tools (search, get schema, execute), enabling agents to dynamically discover and utilize thousands of internal tools and playbooks. This self-improving, context-aware infrastructure empowers agents to handle tasks from incident response to code generation, significantly boosting developer productivity and ensuring reliability.

Sep 08, 2026

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.

Sep 04, 2026

Open Models Change The Economics of AI

Ollama Co-founder Jeffrey Morgan discusses the enterprise shift to open models, driven by cost, customization, and coding agents, leading to a 150X token growth. He highlights the dominance of Chinese models in cloud consumption, the hardware renaissance enabling local LLMs, and the rise of ultra-efficient "flash" models. Morgan also shares Ollama's journey, from its YC pivot to its monetization strategy, and reflects on lessons for building AI companies.

Sep 04, 2026

In Case You Missed It in August 2026 (Ep. 1024 with Jon Krohn)

This episode explores the critical gap between AI investment and return, featuring insights from industry leaders. It covers why most organizations fail to see ROI from AI, the crucial role of mathematical optimization in agentic AI to ensure constraint adherence, practical strategies for structuring AI skills in tools like Claude for quality output, and a 10-20-70 budget framework emphasizing upskilling. Additionally, it delves into the growing importance of the semantic layer for analytics agents to ensure consistent data interpretation and efficiency in large enterprises.

Aug 29, 2026

Agents Are Where Microservices Were in 2015 — Roberto Milev & Uday Kanagala, Navan

Roberto Milev and Uday Kanagala from Navan discuss the challenges and emerging best practices in building and operating AI agents, drawing parallels with microservices. They highlight the shift to stateful runtimes, innovative memory and context management using 'skills,' and crucial solutions for observability and testing non-deterministic systems. A central theme is the critical need for robust authorization and guardrails, given the blurring line of agentic action, and a preference for mastering single-agent loops before scaling to complex orchestrations. They conclude by outlining the solved and unsolved problems, with cost and debugging remaining significant hurdles.

Aug 28, 2026

AI-Native Organisations Run on Skills: How to Structure and Scale Them — Imad Touil, QuantumBlack

Imad Touil explores the critical need for governing AI skills within organizations, asserting that skills represent the true repository of enterprise know-how. He contrasts simplified coding agent loops with complex, real-world product lifecycles, demonstrating how ungoverned skills lead to technical debt—including duplication, quality degradation, security risks, and lack of discoverability. Proposing a microservices-inspired approach, Touil outlines a centralized skills platform and human-led governance model essential for achieving deterministic workflows, boosting productivity, and mitigating risks in AI-native enterprises.