Why I’m Moving This Substack From Daily Coverage to Deeper Weekly Work
The host announces a shift in their Substack from daily AI news coverage to a weekly format focused on depth, emphasizing practical building and executive insight. They argue that AI's future hinges on deep understanding rather than breadth, as the technology has matured into usable models, agents, and tools. The new cadence will feature three weekly pillars: a deep dive into the top story, a hands‑on buildable project, and an executive briefing for leaders. While major breakthroughs will still be reported promptly, the overall goal is to foster AI fluency and career growth.
AI Made Your App Teams 10x Faster. Nobody Gave Your Platform Team 10x the Headcount.
In this episode, Emma, who leads OpenAI's data platform infrastructure engineering group, explains how her team builds and maintains the foundational data systems that power OpenAI's products and research. She covers the breadth of their work, from big‑data analytics and...
Exclusive: A Conversation with Tibo From Codex on What Your Company Has to Become when the Model Can Actually Do...
The April release of OpenAI’s Codex and GPT‑5.5 enables the model to build and ship full‑stack applications with little human coding, widening the pool of people who can create software. Tibo, head of Codex, says the bottleneck has moved from...
The 2 Prompts I'd Run Before Any 2026 SaaS Renewal (Especially if You're Deploying Agents)
The SaaS pricing model is shifting from simple seat counts to a hybrid that bills both user logins and AI‑driven work. Salesforce reported $800 million in agent revenue, while Microsoft introduced a $15‑per‑user governance fee alongside its $30 Copilot seat. Vendors...
You Gave Your AI Agent Real Tools. Here's the 4-Part Control Layer It's Missing + the Judge Layer Implementation Guide
In this episode the host examines the growing risk of autonomous AI agents that can take harmful actions, recounting real incidents where agents deleted emails, erased production data, and caused costly mishaps. He introduces a four‑part control layer—authentication, sandboxing, monitoring,...
271 Bugs Found in Firefox, Zero Written by a Human Attacker. What This Means for the Future of Safe Code...
Mozilla’s Mythos AI, built by Anthropic, scanned Firefox and uncovered 271 security‑sensitive bugs, all originating from machine‑generated code. The previous scan with a general model found only 22 issues, highlighting the power of purpose‑built AI for vulnerability research. The findings...
The Anticipation Gap: Why 4 Problems Have to Be Solved Together for Consumer AI to Work
The episode explores why consumer AI has hit an "anticipation gap" in 2026, where powerful software creates more management overhead than value. It argues that chatbots and isolated agents are insufficient, as users are burdened with juggling multiple tabs, prompts,...
55-75% of Your Week Is on Thin Ice. Here Is the Audit that Shows You Which Part.
In this episode the host tackles the unsettling reality that a packed calendar can be the first warning sign that a job is on thin ice, highlighting how work can gradually become less essential even while tasks remain. They explore...
AI Agents Are About to Route Around Every Tool that Can't Pass 5 Structural Tests. Here's the Diagnostic.
The episode explores how issue trackers—tools like JIRA that were never intended for AI—have unexpectedly become critical infrastructure for AI agents in 2026. These systems provide essential features such as state management, ownership, permissions, and historical context, allowing agents to...
The Buying Rule for Your Personal AI Computer (and How to Skip the $5,000 Mistake)
In this episode, the host explains how AI agents are reviving the importance of the personal desktop computer, reversing a 15‑year trend toward cloud‑only workflows. They outline a buying rule for a "personal AI computer," warning listeners to avoid overspending...
ChatGPT 5.5 Scored 87 Where the Next Best Model Scored 67. Here's What that Gap Looks Like in Real Work.
In this episode the host argues that GPT‑5.5, scoring 87 versus the next best model's 67, represents a new performance ceiling for AI, especially in complex work tasks. He demonstrates the model's capabilities through a demanding executive knowledge package, a...
You're Spending Six Figures on AI Models. The Bottleneck Is a 4-Minute CI Pipeline — and Nobody's Fixing the Right...
In this episode, the host explores how the real bottleneck in AI development isn’t the cost of models—often six figures—but a sluggish four‑minute continuous integration (CI) pipeline that slows iteration. They argue that the industry is misallocating resources, focusing on...
Your Agent Needs a SOUL.md You Can't Write From Scratch. I Built a 45-Minute Prompt that Writes It for You.
The episode critiques the hype around AI agents, arguing that merely installing an agent isn’t enough to boost productivity. The host explains that many developers are busy cloning popular frameworks like OpenAI’s agent tools without understanding how to effectively prompt...
GPUs Just Got 6x More Valuable. No New Hardware Required.
The episode dives into Google's newly announced TurboQuant breakthrough, a technique that dramatically improves memory efficiency in large language models (LLMs) without requiring new hardware. By enabling lossless compression of LLM processing, TurboQuant makes GPUs effectively six times more valuable,...
Most of What You're Building Will Be Replaced by a Better Model. Here Are the Five Layers Between You and...
The episode explores the precarious position of AI app builders who risk obsolescence as larger model providers like OpenAI, Anthropic, and Google release ever‑more capable models. It proposes a framework of five protective layers—data ownership, domain expertise, integration depth, user...