
Agent Strategy Decks Are Everywhere. Working Agents Aren't.
Every vendor shipped a 2026 AI agent strategy framework this quarter. The agents that survive real work share three unglamorous traits — and break in predictable ways without them.

Every vendor shipped a 2026 AI agent strategy framework this quarter. The agents that survive real work share three unglamorous traits — and break in predictable ways without them.

Folders and filters were a workaround for bad search. In an AI-native stack, your inbox is a messy index — and treating it that way changes triage, search, and follow-up.

A hallucinated sentence is awkward. A hallucinated formula is expensive. Here's a taxonomy of where generative AI fails in structured work — and the guardrails that catch each type.

Public policy researchers are arguing about whether LLM-assisted coding counts as method. Their objections — bias, reproducibility, opaque provenance — apply to your Tuesday afternoon analysis too.

A practical eval playbook — golden sets, LLM-as-judge with guardrails, and regression tracking — for teams shipping AI, not writing papers.

New research suggests generative AI speeds work up while quietly reducing what people actually learn. Here's how to restructure AI-assisted work so speed doesn't cost you understanding.

Demo RAG retrieves from one clean corpus. Real work means retrieving across email, docs, spreadsheets, and calendar — where context is stale, duplicated, and contradictory.

AI agents can already do the work. The bottleneck is authorization — and most teams are quietly lending agents a human's credentials and hoping for the best.

You don't need an ML platform to measure AI quality. A well-structured sheet turns vibes-based prompting into something you can actually score and improve.

New adoption data shows the biggest productivity gains go to people using purpose-built AI tools, not general chatbots. The difference isn't model quality — it's context and integration.

A field guide to choosing between deterministic automation and goal-seeking agents — with a decision tree, cost math, and the honest cases where a plain script still wins.

Model quality isn't your bottleneck anymore — context portability is. We map where the time actually goes in AI-assisted work, and what to fix first.
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