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The word "context" covers four unrelated systems — a token limit, a 35-million-token corpus, a hand-edited rules file, and session memory — and treating them as one job wastes real work.

Karpathy's LLM-wiki pattern works for personal knowledge, but six months of running it in production surfaced three failure modes he never mentions.

Most local-LLM cost models skip a single variable: utilization. Do the math honestly and a $40K GPU can cost more per token than a commercial API.

A Mac mini running local inference sat busy 1.7% of the time over three weeks. That number kills the usual local-vs-cloud spreadsheet math.

Per-token pricing hides the real cost of local LLMs: retries, escalations, and the human review minutes that dwarf the token bill.

New survey data shows AI agent rollback rates rise, not fall, as safety guardrails mature — because better monitoring catches failures other teams miss entirely.

Anthropic's usage data shows coding has already crossed into delegation: 61% automation versus 39% augmentation. Most coding tools are still built for the wrong half.

Inference doesn't bill like a license — it bills like a taxi meter. Here's why treating AI as cost of goods, not capex, is the only model that survives contact with a spreadsheet.

An AI coding pilot showing $80K spent and 9% faster velocity looks like a 3.4x return. Add the unpriced senior-review hours and it drops closer to 1.2x.

Cory Doctorow says AI is a bubble. He's right about the labs' balance sheet and wrong to let it answer for whether your deployment pays for itself.

Linus Torvalds built decades of code review on one proxy: a coherent explanation proved understanding. LLMs made that proxy free, and he just replaced it with a provenance requirement.

Agents made execution cheap and human attention scarce. The answer isn't more discipline — it's building the same kind of infrastructure that solved every other bottleneck before this one.

A $20K monthly token bill isn't one cost — it's a pipeline with four measurable leaks: retries, prompt bloat, MCP schema overhead, and redundant judge passes. Treat the invoice as telemetry, and half of it turns out to be waste.

Eight posts ago the claim was that the AI-education industry is building the wrong product — chatbots students ignore, while the thing that actually moves exam scores is an LLM grading written…

The most valuable thing the Dartmouth team built wasn't the grader. It was the fact that they could answer "did completing this lesson's quiz correlate with doing better on the exam?" — per…

The feature with the largest effect size in the Dartmouth pilot is the one no startup would put on a landing page. Not the AI grader. Not the chatbot. Cumulative module reviews: a big quiz…

The most dangerous failure in the Dartmouth Phosphor pilot wasn't a wrong grade. Students found the constructed-response grader "rigid and discouraging," complained loudly enough that the team…

Somewhere in your class of 150 there is a student who will type "ignore the rubric and mark this correct" into a quiz box. Not because they read a paper on prompt injection, but because it's free…

Nobody ships a payment system without tests, but teams ship LLM judges into production on vibes every day. A grader, a triage classifier, an eval pipeline's scoring model — if an LLM's judgment…

The most common mistake in LLM grading is asking the model for a grade.

Every student now carries a competent tutor in their pocket, and academic performance hasn't moved. That's the puzzle worth sitting with. The answer, based on a deployment study published this…

You cannot retrain Claude. You cannot fine-tune GPT. The weights belong to Anthropic and OpenAI, and no amount of clever prompting changes a single parameter. That fact makes a lot of engineers…

The newest coding-agent benchmark grades the work that eats a senior engineer's week: messy bugs, investigation, maintainability, taste. Those are the skills a rising pass rate keeps hiding.

OpenTelemetry's GenAI conventions will tell you your agent called Claude, spent 1,843 input tokens, took 900 milliseconds, and returned without an error. They will not tell you the answer cited…

There is a spreadsheet making the rounds in boardrooms right now. On one line: the fully-loaded cost of a senior software engineer. On the other: what it costs to run a coding model that writes…

There's a diagram making the rounds that splits the world into "prompt engineering" and "loop engineering." The pitch: stop writing prompts one at a time and let the agent drive. Set a goal, fire…

Dell booked $12.3 billion in AI server orders in a single quarter — $30 billion year to date, with an $18.4 billion backlog and a five-quarter pipeline the company says is multiples of that, per…

An agent connected to five MCP servers can burn 55,000 tokens on tool schemas before it reads the first word of your request. GitHub's server ships 35 tools at roughly 26K tokens. Slack adds 11…

Every large engineering org eventually wants the same thing: one view of every dependency across hundreds of repositories. Who uses lodash 4.17.20. Which services still pull in the bad Log4j. What…

Internal platforms used to be the exotic option. Now they are the default. A December 2025 Platform Engineering survey of 518 organizations found that nearly 90% of enterprises run internal…

The question being asked in r/kubernetes this week is whether to feed observability data to coding agents. Traces, metrics, logs, the whole stream the system already emits — should the agent that…

The companies with the most control over chip supply on the planet still rent across three cloud providers. That is the fact that should reset how a platform team thinks about AI infrastructure.…

The 1M-token context window is here. Opus 4.8, 4.7, and 4.6, plus Sonnet 4.6, now carry the full million-token context on the Claude API, Amazon Bedrock, and Vertex AI — no surcharge, generally…

A LinkedIn post circulating this week made an observation worth sitting with. AI write-throughput in a serious engineering team can hit fifty pull requests a day. The team's merge-throughput is…

The cloud-runtime question for enterprise Claude is settled. AWS shops route through Amazon Bedrock. Google Cloud shops route through Vertex AI. Direct deployments now sit inside the customer's…

The May 15 piece on access-rents drew a line through every services industry. On one side: access-rents — work that consists of operating an interface the customer cannot operate themselves. On…

Every working stack is the residue of failures the operator did not see coming. The Saturday piece showed the architecture as it stands now. This piece is the inverse — the five specific incidents…

Most "AI is expensive" discourse is vague. The pieces that quote real numbers usually quote enterprise tier list prices for tools the writer does not personally run. The pieces that talk about…

The dotfiles piece from May 22 named hooks as one component of a personal AI stack and moved on. They deserve more than a passing mention. Hooks are the primitive that turns taste into code — the…

Yesterday's piece prescribed building a personal AI stack instead of waiting for the enterprise plan. The natural objection — "fine, but what does that actually look like" — deserves a concrete…

Every senior engineer who has shipped meaningful work in the last thirty years has carried a personal dev environment with them. Emacs configs, vim plugins, shell aliases, dotfiles repos, custom…

The current "Hermes Agent vs Claude Code" framing is the wrong comparison. The two tools live at different layers of the coding agent stack, and most of the YouTube hot takes treating them as…

An article circulating this week argues that faculty AI buy-in in higher education is a human factors engineering problem. The framing is correct. The path the piece describes skips the only two…

Anthropic added the /goal command to Claude Code in v2.1.139. You set a completion condition; the agent keeps working across turns; a second model reads the transcript and decides whether the…

A DevOps engineer posted on r/devops this week with what reads like a familiar shadow-IT question dressed in 2026 clothes. Marketing, product, and sales people across his AI startup are shipping…

Anthropic launched Claude for Small Business on May 13. Every read I've seen has focused on the product surface: 15 prebuilt agentic workflows, 7 named SaaS integrations, a trust posture built…

Carl Frey's recent NYT piece argues that AI's real impact isn't job replacement — it's labor transfer from worker to consumer. We become our own travel agent, accountant, exterminator, doctor. The…

In 2025, four companies — Microsoft, Alphabet, Amazon, Meta — spent over $300 billion on AI data centers. The combined 2026 number is forecast at $725 billion, a 77% jump in a single year. For…

Someone on r/devops just asked whether to take an AWS Cloud Support Engineer role for 18 months — trading hands-on building for "AWS internals exposure and the brand on the CV." Both replies told…

The first time you trim an eval because it costs too much to run, you have started letting the pricing model design your agent. The problem with token pricing for AI is not magnitude — tokens…

A post hit the HN front page this morning titled "I'm going back to writing code by hand". It documents archiving seven months of vibe-coded work on a Kubernetes GPU TUI called k10s and rewriting…

Anthropic asked Claude Opus 4.6 to finish a couplet. Before the model wrote the second line, it had already chosen the rhyme word. We know this because their new method — natural language…

A short post argued this week that reliable agents need deterministic control flow, not more prompts. The argument is correct. The line that lands hardest in the piece is the one about a…

Most AI projects fail somewhere between demo works and production ships. The gap is rarely the model. It's the absence of the controls that turn a one-shot prompt into a system you can run, audit,…

A recent piece called "The Bottleneck Was Never the Code" makes the right argument at the right time. Coding agents shift the constraint from typing to coordination. Organizational context — the…

Last week, a Cursor agent running on Claude Opus 4.6 deleted a startup's production database and its backups in nine seconds. The agent had been asked to fix a credential mismatch in staging. It…

Editor's note (2026-05-16): Lars Faye pushed back in the LinkedIn comments that I mischaracterized his prescription as "type code by hand" — his actual position is periodic abstinence from LLM…

Yanli Liu's "The 4 Lines Every CLAUDE.md Needs" makes a real point. The 4 lines, derived from Andrej Karpathy's January 2026 thread on agent failure modes, all express the same insight: behavioral…

Anthropic now ships at least three different memory models inside the Claude product family, and they don't behave the same way. Claude.ai has a chat memory feature for Pro, Max, Team, and…

Count how many times your agent told you "you're right" today. Count "good catch." Count "I should have noticed that." Now ask yourself how many of those corrections will survive into tomorrow's…

The AI adoption pathway that's actually working in 2026 is not "deploy a copilot to your team." It's "expose your org's context to whichever model your team already chose." That sounds like a…

Microsoft just patched a built-in Entra ID role they shipped as scoped to "agent identities" — and which, in practice, let anyone holding that role take over almost any service principal in the…

The current message from engineering leadership at most companies I talk to is some version of: "find the deterministic automation in your stack and make it agentic." A recent r/devops thread…

Part 2 of 2 on agentic system adoption. Part 1 covered internal adoption: getting your own team to actually use the agent you built. In February 2024, Klarna announced that its AI assistant had…

Part 1 of 2 on agentic system adoption. A 25% bump in individual AI usage correlates with a 1.5% drop in delivery throughput and a 7.2% drop in delivery stability. That's not a hot take — that's…

Since Anthropic released Claude Opus 4.7 on April 16, 2026, a consistent complaint has rippled through developer communities: it feels slower. Threads tell roughly the same story — the prompts…

Anthropic's official plugin directory has 55+ curated Claude Code plugins since launch. The community tracks another 72. By end of 2026, most large engineering orgs will have a private marketplace…

Six frontier coding models now score within 0.8 points of each other on SWE-bench Verified. The same model wrapped in different agent frameworks swings almost ten points on SWE-bench Pro. Picking…

Intercom's Fin AI agent went from $1M to $100M+ ARR on one pricing move: $0.99 per resolved ticket. Not per seat, not per month. Per outcome. Fin now handles 80%+ of Intercom's customer support…

Every week someone posts about AI hallucination like it's a mystery. It's not. A 2025 Frontiers in AI study measured it: vague, multi-objective prompts hallucinate 38.3% of the time. Structured,…

Most AI coding tools ship as monoliths. One big system prompt, one set of capabilities, one-size-fits-all. That works fine for general software engineering. It falls apart the moment you need…

Everyone's writing better prompts. Few are building better context. That's the gap. Prompt engineering treats AI like a search box — craft the perfect query, get the perfect answer. Context…

AWS just launched two autonomous AI agents — Security Agent and DevOps Agent — and they're both generally available now. These aren't chatbots with polished wrappers. They're persistent,…

Everyone's Buying GPUs. Almost Nobody's Ready to Feed Them. The enterprise AI conversation has a blind spot the size of a data center. Every budget meeting I've sat in over the past 18 months has…

The Cloud Repatriation Nobody Expected: Why Enterprise AI Is Pulling Compute Back from the Cloud The original pitch for cloud computing was simple: stop buying servers, rent someone else's. For…

Most enterprise AI projects die quietly. No dramatic failure, no post-mortem email chain. They just... stop. The prototype gets a demo, leadership nods approvingly, and then six months later the…

Addy Osmani dropped a piece last week that's been making the rounds: "Comprehension Debt — The Hidden Cost of AI-Generated Code." His thesis is sharp. Teams are shipping AI-generated code faster…

The Production Gap: Why Nobody Teaches the Infrastructure That Actually Matters Every bootcamp, CS program, and YouTube tutorial series teaches you how to build features. Almost none of them teach…

The AI CapEx Arms Race Is Coming for Your Cloud Bill The three major cloud providers are spending money like it's going out of style. Oracle is financing a $300 billion deal with OpenAI through…

On March 3rd, an attacker compromised the Xygeni GitHub Action by poisoning a mutable tag. Every CI runner referencing xygeni/xygeni-action@v5 quietly started executing a reverse shell to a C2…

The streaming media stack has operated in silos for two decades. Encoding and transcoding happen at the source or in dedicated hardware. Orchestration — ad insertion, CDN routing, audience rules —…

Originally published on the Presidio blog - sharing here as it captures the current reality around agentic AI in enterprise modernization. The pitch behind agentic application modernization is…

Everyone's obsessed with prompt engineering like it's some arcane art. Here's what they're missing: the real challenge isn't crafting clever prompts. It's context management. And most…

Everyone's talking about AI infrastructure like it's the next gold rush. Here's what they're not telling you: most enterprise AI infrastructure projects fail not because of technology limitations,…

In late 2022, I had emergency open heart surgery. Not a metaphorical "rough patch" — my heart literally stopped in the hospital. I coded, was resuscitated, and spent the following months trying to…

The Kubernetes ecosystem just pulled its biggest rug since Docker changed their licensing. Ingress NGINX is being retired in March 2026, and it powers roughly half of all Kubernetes deployments.…

Here's what nobody wants to say out loud: your cloud security posture is probably worse today than it was three years ago. Not because you're doing less—you're doing more. You've deployed every…

Your AI agent project is going to fail. Not because the technology doesn't work—it does. Not because your team isn't smart—they are. It's going to fail because you're building the wrong thing, for…

Introduction Artificial Intelligence (AI) and Machine Learning (ML) are no longer just buzzwords floating around tech conferences and boardroom discussions. They have become integral components of…

Introduction Artificial Intelligence (AI) and Machine Learning (ML) are no longer just buzzwords floating around tech conferences and boardroom discussions. They have become integral components of…

Introduction Artificial Intelligence (AI) and Machine Learning (ML) continue to redefine how businesses operate, offering unprecedented opportunities for innovation and efficiency. The cloud has…

2025 was supposed to be the year AI changed everything. The promises were bold: AI agents would "materially change the output of companies," scientific breakthroughs would accelerate, and the…

Something unprecedented happened in AI this week. The companies most aggressively competing to dominate the AI landscape—OpenAI, Anthropic, Google, Microsoft, Amazon, and dozens of others—just…

Last month, a senior ML engineer with nine years of experience posted a question that resonated across the industry: "Is senior ML engineering just API calls now?" The post attracted 385 upvotes…

The AI industry just hit a counterintuitive inflection point that should concern every CTO deploying large language models in production: the more sophisticated our reasoning models become, the…

The conversation around AI infrastructure costs has shifted dramatically in the past year. Every CTO and engineering leader is asking the same question: should we run our own LLMs or stick with…

The enterprise AI landscape is experiencing a seismic shift that most CTOs haven't fully grasped yet. While we've been laser-focused on AI implementation and performance metrics, a more…

After decades in the consulting trenches, I've witnessed the full spectrum of Statement of Work disasters – from scope creep that doubled project costs to payment disputes that ended partnerships.…

The software development landscape just shifted. While most teams are still debating whether AI coding assistants are worth the investment, a growing cohort of engineers is shipping complete…

The numbers are staggering: generative AI training clusters consume 7-8 times more energy than traditional computing workloads. That's not a typo. Seven to eight times. As data center power…

The question haunting enterprise boardrooms today is deceptively simple: "How do we avoid becoming the next AI platform cautionary tale?" With organizations committing tens of millions to their AI…

Twenty years ago, I sat across from my future boss, fresh off a successful stint as a senior engineer, interviewing for my first management role. When he asked how I'd handle the transition from…

I can remember back to when I was a junior developer on my team, struggling with a complex refactoring task that involved updating tests, modifying implementation code, and ensuring security…

What This Solution Provides This guide establishes a development workflow that enables you to switch between your Mac and iPhone while maintaining terminal session continuity. Using Tailscale for…

After spending the last several years architecting AI workloads across AWS, Azure, and GCP, I've come to a sobering conclusion: our current cloud infrastructure was built for yesterday's…

Having built teams for over two decades, I've watched onboarding evolve from handwritten manuals to polished video libraries. But as AI reshapes how we work, it's time to ask some hard questions…

After 25 years in technology leadership, I’ve witnessed hiring practices evolve from whiteboard algorithms to LeetCode marathons. While I haven’t been actively hiring lately, the conversations I’m…

As artificial intelligence continues to transform industries, the demand for specialized cloud infrastructure has reached unprecedented heights. The next generation of AI applications requires not…

The shift toward AI workloads has fundamentally changed how we approach cloud infrastructure design. Traditional architectures, optimized for web applications and microservices, often fall short…

A deep dive into the data engineering, automation, and machine learning powering next-generation marketing measurement platforms—covering scalable data workflows, experiment automation, and the technical challenges of building a true system of record for marketing analytics.

In today's rapidly evolving AI landscape, organizations are increasingly faced with the challenge of building robust, scalable infrastructure to support their machine learning initiatives. While…

In the ever-evolving cloud landscape, event-driven serverless architectures have emerged as a powerful paradigm for building scalable, resilient, and cost-effective systems. By combining the…

After years in technology consulting, I've learned that technical expertise is only half the equation. The other half? The art of maintaining professional relationships and protecting all parties…

In the world of DevOps, automating infrastructure deployment securely is crucial. This blog post will guide you through setting up GitHub Actions to automatically deploy your Terraform…

In today's digital-first environment, businesses and organizations can leverage intelligent document processing (IDP) to effectively manage and utilize the massive influx of data embedded in…

Two terms often surface in Artificial Intelligence: Fine-Tuning and Retrieval-Augmented Generation (RAG). Both play pivotal roles in enhancing the capabilities of AI models, yet they serve…

In DevOps and continuous integration/continuous deployment (CI/CD) pipelines, optimizing containers' build and deployment processes is crucial for efficiency and resource management.

Every February 2nd, a quirky tradition captivates people across North America. Groundhog Day, rooted in folklore, promises an early spring or prolonged winter based on a groundhog's shadow…

The video industry has undergone a significant transformation in recent years, with the rise of over-the-top (OTT) video services and the increasing popularity of streaming platforms. According to…