· 4 min read
How to Choose an LLM for Each Task, Not Just the Best One
Stop defaulting to the largest frontier model. Use a cost-latency-quality matrix to route each task to the right LLM and cut spend without hurting output.
All#ai#ai-agents#ai-productivity#applied-ai#automation#calendar#context-switching#deep-work#documents#email#engineering#engineering-leadership#invisible-ai#knowledge-work#llm-evaluation#product-updates#productivity#prompt-engineering#remote-work#search#security#spreadsheets#startups#storage#tamaton#unified-workspace#workflow#workflows
· 5 min read
How to Evaluate an AI Inbox Assistant Before You Trust It
A concrete eval rubric for email AI — measuring intent precision, action safety, and hallucinated commitments — plus test cases you can run today.
· 5 min read
The Quiet Shift to Smaller, Specialized Models in 2025
Frontier models aren't always the answer. For inbox and search work, routing to small fine-tuned models is quietly becoming the default architecture.
· 4 min read
How to Evaluate an AI Agent Before You Trust It With Your Inbox
A concrete eval methodology for action-taking agents: measure task success, failure recovery, and over-action risk before you hand over the keys.
· 4 min read
Designing Memory for AI Agents: What Actually Works
Memory isn't one feature. A practical breakdown of episodic, semantic, and working memory for AI agents — and how to wire them into real workflows.
· 4 min read
Why AI Struggles With Spreadsheets — and How to Fix It
LLMs reason poorly over raw grids because cells lose their meaning. Here's why ai spreadsheet analysis breaks down — and how structure fixes it.
· 4 min read
How to Evaluate an LLM for Your Workflow (Not the Leaderboard)
Public benchmarks rarely predict real performance. Here's how to build a task-specific eval harness from your own emails, docs, and spreadsheets.
· 4 min read
Context Windows Are Not Memory: Designing Agent State
The context window is a scratchpad, not storage. Here's how to architect external memory layers for durable, reliable agent state.
· 4 min read
Why Your RAG Pipeline Retrieves the Wrong Chunks
A diagnostic framework for the quiet retrieval failures that degrade RAG quality — from chunking strategy to embedding mismatch.
· 4 min read
Why Your RAG Pipeline Retrieves the Wrong Chunks
Retrieval failures aren't one bug — they're three. A diagnostic framework for isolating chunking, embedding, and reranking problems instead of guessing.
· 4 min read
Email Triage at Scale: Building Stateful Classification Systems
An architecture guide for AI systems that classify email by learning from patterns over time, rather than judging each message in isolation.
· 4 min read
Choosing an LLM by Task, Not Benchmark
Leaderboard scores rarely predict production performance. Here's a decision framework that maps real workloads to the right model.
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