No conference panels. No vendor white papers. Real deployments, real numbers, documented week by week.
I see the same pattern across the service businesses I work with: a full calendar this month, an empty one three months out. That gap is what separates the businesses that plateau from the ones that grow 45 percent a year.
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Five research items from the week of July 1, 2026.
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Page speed data shows a direct line between load time and lost revenue. Here is what the research says and what to do about it.
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Andre Cobham did not start in AI systems. He started by assembling a computer on a garage floor, producing a student news show, running fiber at a broadcast station, and spending a decade in data. This is the arc from curiosity to agentic infrastructure.
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WordPress is a strong platform for standard publishing operations. This is why I moved off it when my requirements outgrew what it could support cleanly.
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Most of what businesses believe about LLMs comes from vendor marketing, not production. These five myths are costing teams time, money, and trust in systems that could be working better today.
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Five research items from the week of June 25, 2026.
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Vendors sell 128K context windows. Research shows the effective usable context is a fraction of that, determined by where your data sits inside the window. The numbers from Liu et al. 2023 are specific and actionable.
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I replaced our edge routing and security layer with OPNsense running on FreeBSD. Here are the kernel level network tunables that changed how AI inference traffic, large file transfers, and client pipelines behave under load.
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Five items this week where the gap between research and production narrowed further. Enterprise agents are live, MCP has a structural flaw with real CVEs, and AI is compressing the time between vulnerability disclosure and active exploitation.
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Tokens are the billing unit, the context window unit, and the output quality constraint in every LLM call. Understanding that triple role is the difference between a system that scales and one that produces a billing surprise at month two.
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The Agentic Resource Discovery specification is not a product announcement. It is the missing infrastructure standard that makes multi-agent systems across organizations actually work, and it lands at exactly the right moment.
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Five items where security moved from research to active exploitation this week. Agents are both the new attack tool and the new defense layer, and real exploits are confirming the threat model.
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Most AI projects fail at the planning stage. The spec gets written before a single assumption is validated. Here is the process I actually use and why the order of operations matters more than the plan itself.
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Claude Fable 5 and Mythos 5 launched June 9. OpenAI announced five new Stargate data center sites and a $500B infrastructure buildout. BBVA put 120,000 employees on ChatGPT Enterprise. Cohere shipped North Mini Code. Microsoft patched 206 flaws. And three arXiv papers documented the containment gap in deployed agentic systems. All in one week.
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Five research items from the past 24 hours: agents coordinating at scale, PI-Hunter for prompt injection red-teaming, MiniMax Sparse Attention, fact-checking with RL, and GPT-5.5 in enterprise pipelines.
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Four arXiv papers and one OpenAI product update all landed this week on the same gap. Agents without persistent memory spend 5,000 to 20,000 tokens reconstructing context each session. HORMA cuts that to 22% of baseline. PROJECTMEM blocks repeated failures. The substrate paper shows why a single memory score hides three separate failure modes. Ebby breaks down each finding.
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Opus 4.8 ships with 1M token context, dynamic multiagent workflows, and measurably lower misaligned behavior. I have been testing it. Here is what actually changed and what it means for the businesses I work with.
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I tested Gemini, Imagen, Veo, Flash, and Nano against real client workflows. Google's API stack is the most price-accessible foundation for SMB AI systems available right now. Here is what the numbers showed.
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Anthropic built the most capable vulnerability-finding AI ever created, then refused to release it. Here is what that decision tells us about where cybersecurity is headed.
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Sundar Pichai sat down at Google I/O and laid out a strategy that is less about hype and more about making AI work at scale. Here is what caught my attention.
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Karpathy chose Anthropic over OpenAI to lead a team using Claude to accelerate Claude's own pre-training. I have been on this stack since late 2024. Here is what this hire actually signals for businesses building on AI today.
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A cost and performance comparison of running LLM inference on integrated GPU versus cloud API. Real numbers from actual workloads.
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As of May 13, 2026, Google Analytics 4 automatically classifies ChatGPT, Gemini, Claude, and Perplexity referrals under a new Default Channel Group.
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Intel quietly launched a $949 workstation GPU with 32GB of VRAM in March 2026. Here is what it means for private AI infrastructure and the software gap that is still real.
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Small businesses are splitting into two groups: those that have integrated AI into operations and those still watching. The gap is widening faster than most expect.
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Anthropic signed a compute deal with SpaceX and removed the long-context surcharge. A breakdown of what both moves actually mean for businesses building on Claude.
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Google's Virgo project signals a shift toward network-level AI orchestration. What it means for agentic workflows and enterprise AI infrastructure.
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AI agents are not just automating tasks. They are changing how teams are structured. What that means for businesses deploying agents in 2026.
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A practical comparison of Qwen and Gemma local models for common business automation tasks including extraction, drafting, and classification.
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A client had $87,000 sitting in overdue invoices. We built an automated follow-up sequence. Here is what happened.
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How an automated lead response system brought a home service business from 4-hour average response to under 8 minutes, and what that did to booking rates.
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