How to Monitor an AI Agent in Production
Your agent can be HTTP-200, fast, and cheap while being completely wrong. The metrics that keep a web app healthy are blind to the ways an agent actually fails.
5 min
How to Load-Test an LLM App: You're Stress-Testing the Rate Limiter, Not the Model
For an app built on a hosted LLM API, the wall you hit under load isn't the model's speed — it's the provider's rate limiter and your own retry policy. Test for the ceiling and the fall, not the throughput.
5 min
How to Handle Tool Errors in an AI Agent: Return the Failure, Don't Raise It
The try/except instinct that keeps a normal program alive is the one that kills an agent. A tool error isn't an exception to catch — it's the next message in the conversation, and where you put it decides whether the agent can recover.
6 min
How to Evaluate a Reranker for RAG: The Number That Caps It Isn't the Reranker's
A reranker can only reorder what your retriever already fetched, so the ceiling on its lift is your stage-one recall — measure that first, then judge the reranker as the latency and dollars you pay to convert recall into precision.
5 min
How to Do RAG Over Tables: When to Embed Rows and When to Generate SQL
Your RAG pipeline works on documents and falls apart on a spreadsheet — because a table's meaning lives in its grid, and an embedding flattens the grid away.
5 min
How to Deploy an AI Agent to Production
An agent isn't a stateless web service — it's a long-running, resumable process. The thing that bites first isn't latency; it's shipping a new version while runs are still in flight.
5 min
GAIA2: The Agent Benchmark Where the Clock Never Stops
Static benchmarks freeze the world while an agent thinks. Meta's GAIA2 lets time run — and the smartest model, GPT-5, turns out to be the one that misses deadlines.
4 min
Does an AGENTS.md File Actually Make Your Coding Agent Better?
The first rigorous benchmark of repository context files is in, and the answer is uncomfortable: the auto-generated ones make agents slightly worse, the hand-written ones barely help, and both raise your bill ~20%.
5 min
Disaggregated LLM Inference: Why Prefill and Decode Are Moving to Separate GPUs
The two halves of every LLM request fight each other on the same GPU. Disaggregated serving splits them onto separate hardware — and the win is real, but only past a certain scale.
4 min
Cost-Aware Agent Evaluation: Why Your Benchmark Needs a Dollar Axis
An agent leaderboard that ranks only on accuracy is secretly ranking on willingness to spend. Add the cost axis and the board's #1 is often not even on the frontier.
5 min
Reward Hacking in AI Agents: When the Eval Becomes the Attack Surface
If your agent's reward is a number it can reach without doing the work, it will eventually reach the number without doing the work — and 2026's research says that habit doesn't stay contained.
5 min
Who Controls MCP Now? Inside the Agentic AI Foundation
For a year the question that stalled enterprise bets on MCP was 'what happens when Anthropic changes its mind?' In December that question got an answer — and the answer reveals what the standards war was really about.
5 min
WebMCP vs MCP: Why Browser Agents Get Their Tools From the Page
A new web standard lets a website hand an AI agent a typed menu of its own functions — no server, no OAuth. The catch is hiding in that 'no OAuth.'
5 min
Vercel eve vs LangGraph: Library You Host, or Harness You Rent
Vercel's new agent framework treats an agent as a directory of files. LangGraph hands you a portable graph. The decision isn't the loop they run — it's who owns the production stack wrapped around it.
5 min
AWS Trainium vs NVIDIA GPU for LLM Inference: The Bill Is Cheaper, the Onramp Isn't
Trainium2 and Inferentia2 sell real price-performance and AWS capacity. NVIDIA sells CUDA. The decision is whether the Neuron SDK supports your model and serving stack — and how much engineering you'll spend finding out.
5 min
Tool-Result Caching for AI Agents: The One Cache That Can Be Wrong
Prompt and semantic caches store the model's work and fail cheaply. Tool-result caching stores the world's — and it forces a question every agent codebase has dodged: which tools are safe to cache?
5 min
τ-bench vs τ²-bench: The Agent Benchmark That Scores Whether You Can Guide a Human
Most agent benchmarks hand the whole task to the model. τ-bench keeps the user in the loop, and τ²-bench gives the user their own hands — which is where frontier agents quietly fall apart.
5 min
SWE-EVO vs SWE-bench: The Long-Horizon Test Coding Agents Fail
A new benchmark drops the same models from ~73% to ~25% — not by making the bugs harder, but by taking away the one thing SWE-bench always handed over: a map to the change.
4 min
SWE-bench Pro vs SWE-bench Verified: Why Top Coding Agents Dropped From 70% to 23%
The same models that ace SWE-bench Verified collapse on its successor. The gap isn't difficulty — it's the size of an illusion, and the only durable fix turned out to be a software license.
5 min
Reflexion vs Self-Refine vs CRITIC vs LATS: Who Verifies the Self-Correction?
Four ways to make an agent fix its own mistakes. Three of them quietly outsource the judgment to the world — and the one that doesn't is the one the research keeps catching in the act.
5 min
Speaker Diarization for Voice Agents: pyannote vs NVIDIA NeMo vs Cloud APIs
Builders keep wiring diarization into the live loop of a one-on-one voice agent. There, it solves a problem you don't have — because you already own one of the two voices.
5 min
NVFP4 vs MXFP4: The Two 4-Bit Floats Fighting Over Your Inference Bill
Both pack weights into the same E2M1 four-bit float. The fight is entirely about the block scale — and that one design choice decides whether you keep your accuracy or hand it to the open standard.
6 min
Microsoft Agent Framework at Build 2026: Agent Harness, Hosted Agents, and CodeAct
Microsoft stopped shipping orchestration patterns and started shipping the runtime underneath them. The three Build 2026 launches are all below the framework — and one of them quietly retires the JSON tool-call loop.
4 min
MCP Server SSRF: How 'Convert This URL' Hands Over Your Cloud Credentials
The most common serious flaw in MCP servers isn't prompt injection. It's SSRF — the boring, pre-AI bug that sank Capital One — and we just installed it by the thousand.
4 min
MCP Apps: When a Tool Stops Returning Text and Starts Returning UI
The first official MCP extension lets a server ship an interactive interface into the chat, not just a string. The clever part is a flag that says who each result is for.
5 min
LLM Rerankers vs Cross-Encoders vs Listwise: Which Reranking Architecture for RAG?
Reranking quietly split into three architectures in the last year. They make the same accuracy-for-latency trade in different places — and the newest, highest-scoring tier is the one you can least afford on a hot path.
5 min
KV Cache Eviction: StreamingLLM vs H2O vs SnapKV vs Quest
Three of these throw tokens away to save memory. One keeps them all and just reads less — and for a long-running agent that revisits its own past, that difference is the whole game.
5 min
Hermes Agent: What 'Self-Improving' Means When the Model Never Changes
Nous Research's Hermes is the agent everyone's calling self-improving. It is — but the part that improves isn't the model. It's the harness writing its own skills.
4 min
Harness Engineering: The Reliability Layer Around an Unreliable Model
Prompt engineering tuned the words. Context engineering managed the window. The discipline that decides whether an agent ships is the deterministic code around the model — and it is older than it looks.
5 min
AI Agent Software Spending Hits $206B in 2026 — and the Cancellation Forecast Explains Why
Gartner says purpose-built agent software more than doubles to $206.5B this year. The same firm says 40%+ of agentic projects get canceled. Both numbers are true, and they're the same story.
3 min