From theory to the systems that demand real understanding.
Long-form pieces on how production-AI teams orchestrate agents, serve models, and build the stack, plus GATE DA essays that turn probability, linear algebra, DBMS, ML, and AI into durable concepts.
'40% fear AI will take their job': what the data actually says
Four in ten workers fear AI will take their job, and some cuts are real — but they rarely pay off, and the forecast still points to a net job gain.
The $8.9 trillion problem: inside the global engagement crisis
Only a fifth of the world's workers are engaged, and the lost productivity runs to $8.9 trillion — but the headline hides what engaged even means.
The four-day week, backed by the biggest trial yet
The largest four-day-week trial found burnout falling sharply and output holding — but only because firms redesigned the work first. The evidence.
The thinning bottom rung: AI and the vanishing entry-level job
AI is best at the repetitive work juniors once learned the craft on, so the entry-level rung is wearing thin. What the data shows and how to stay hireable.
The collapsing middle: why managers are cracking first
The clearest signal in 2025 workplace data is not that employees are struggling — it is that managers are cracking faster, and the damage flows downhill.
The two-minute interruption: focus, surveillance, and always-on work
For coding and data work, focus is the scarce resource — yet the workday shreds it every two minutes with pings, overtime, and monitoring.
Money on the brain: how financial stress steals focus at work
Financial stress is the quiet undercurrent beneath much of what we call burnout, following people to work as distraction and lost sleep. What helps, in order.
Boreout: the burnout that comes from too little
Boreout is burnout's overlooked twin — chronic under-stimulation that breeds the same fatigue and cynicism, and quietly hits skilled people hardest.
The lonely org chart: workplace loneliness in the hybrid era
Workplace loneliness carries real health and retention costs, and remote work dismantled the job's social fabric — hitting early-career staff hardest.
The agent harness — the code around the model that actually makes an agent
The LLM is the engine, but the harness is the car. Most of an agent product's real value lives in the scaffolding wrapped around the model — the loop runner, tool dispatcher, context manager, permission gate, and the dozen other things that turn a stateless completion API into something that can work for twenty minutes unsupervised.
Conscious unbossing: why Gen Z is turning down the promotion
Gen Z is declining the step into management, and the data says conscious unbossing is less a failure of ambition than a rational read of a quietly broken job.
Denial of wallet: the attack that bankrupts your AI app
Classic DoS tries to take you down. Denial-of-wallet keeps you up and runs your token bill to five figures by lunch. Why request limits don't save you.
Sleep: the performance lever nobody optimizes
For coding, analysis, and exam prep, sleep quietly sets the ceiling on everything else — yet always-on work erodes it first, and the fix is workload design.
The supervisor-worker pattern: when one agent isn't enough
Anthropic's orchestrator-worker pattern is the only multi-agent topology that consistently ships. Here's how to recognise when you actually need it, what the LangGraph supervisor implementation looks like in practice, and the failure modes nobody warns you about.
Operator, Claude Computer Use, and Project Mariner: the browser agent shootout
Three browser agents shipped within twelve months — each with a different abstraction over the browser. Here's how the screenshot-and-click, DOM-and-accessibility-tree, and Chrome-extension approaches stack up on WebVoyager, OSWorld, latency, cost, and real-world reliability.
996 and the fetishization of overwork
996 — nine to nine, six days a week — is lionized again in startups, but the hours data and WHO death toll check the urge to confuse long with serious.
Surviving 10,000 concurrent requests to your LLM API
An LLM request spends 99% of its life waiting. Design around that one fact and 10k concurrent users stops being scary.
The Big Stay: why nobody's quitting, and why that's worse
A falling quit rate looks like loyalty, but the Big Stay can mean the opposite — people who want out but feel trapped, fraying quietly at their desks.
The three kinds of memory production agents actually use
Working memory, episodic memory, semantic memory — the cognitive science taxonomy that every agent memory startup borrows from. Here's what each one means in practice, what Letta, Mem0, and Zep actually ship, and why most production agents only need the cheapest one.
Cache the question, not just the bytes
Your embedding API answers the same query a thousand times a day. Three caches cut LLM cost and latency — and one of them can hand back a confidently wrong answer.
The recognition gap: the highest-ROI lever teams ignore
Managers think they give feedback and praise constantly; reports barely feel it. That recognition gap is the cheapest, highest-return lever most teams ignore.
What actually re-engages people when the perks don't
Ping-pong tables and meditation apps do not move engagement. What the evidence says re-engages people, ranked by leverage, for data and engineering leads.
50,000 documents, one summarization pipeline
You can't loop 50k LLM calls inside a request. The shape that works — a queue, a pool of workers, and the boring reliability details that decide whether it finishes.
The five patterns that ship real agents in 2026
Anthropic's December 2024 paper became the production reference for agent design. Two years on, here's which patterns actually survived contact with shipped products — and why the simple ones won.