1046 posts · Page 17 of 88. ← Blog
A system that changes itself can improve itself right off a cliff, so the evaluation and guardrails are not an afterthought to self-evolving agents — they are the thing that makes them safe to run at all.
A system that changes itself can improve right off a cliff. Measuring evolution honestly, reward hacking, drift and collapse, and the guardrails that keep it safe.
Metrics and judges are ingredients; a harness is the kitchen. An evaluation harness is the system that takes a dataset of test cases, runs your LLM system over them, scores the outputs, and reports the results — reproducibly, every time. Building one well is what turns evaluation from a one-off spreadsheet into an engineering asset you run on every change, like a test suite.
Metrics and judges are ingredients; a harness is the kitchen. An eval harness takes a dataset of test cases, runs your system over them, scores the outputs, and reports results — reproducibly, every time. Building one well turns evaluation from a one-off spreadsheet into an engineering asset you run on every change.
TLS is the protocol securing nearly every connection you make, and it's not a single cryptographic trick — it's the whole toolkit orchestrated into one handshake. Key exchange, certificates, signatures, and authenticated encryption each solve one sub-problem, and TLS composes them so that two parties who've never met can establish a private, tamper-proof, authenticated channel over a hostile network. Understanding the handshake is understanding how every earlier piece fits.
TLS secures nearly every connection you make, and it's not a single trick — it's the whole toolkit orchestrated into one handshake. Key exchange, certificates, signatures, and AEAD each solve one sub-problem, and TLS composes them into a private, authenticated channel over a hostile network.
Rust makes a promise that sounds impossible: memory safety without a garbage collector, and fearless concurrency without data races — all checked at compile time, with no runtime cost. The price is a compiler that argues with you until your program is correct. Understanding that bargain is the key to understanding why Rust exists and why people love it.
Rust makes a promise that sounds impossible: memory safety without a garbage collector, and fearless concurrency without data races — all checked at compile time, with no runtime cost. The price is a compiler that argues with you until your program is correct.
Most agent frameworks have the model call tools by emitting JSON. smolagents, Hugging Face's deliberately tiny library, makes the model write Python code instead — "agents that think in code." That one design choice, plus a ruthless commitment to minimalism, is what the whole library is about, and it turns out to matter more than it sounds.
Most agent frameworks have the model call tools by emitting JSON. smolagents, Hugging Face's deliberately tiny library, makes the model write Python code instead — 'agents that think in code.' That one choice, plus ruthless minimalism, is the whole library.
Most agent frameworks ask you to design the workflow — the steps, the branches, the orchestration. Strands Agents, AWS's open-source SDK, makes the opposite bet: give the model a goal and tools, and let it drive. That model-driven philosophy is the whole point, and understanding it is understanding why Strands feels different from everything else.
Most agent frameworks ask you to design the workflow. Strands Agents, AWS's open-source SDK, makes the opposite bet: give the model a goal and tools, and let it drive. That model-driven philosophy is the whole point.
Of every AI cost lever, one dominates the rest, and all the major vendors agree on it: prompt caching. On long prompts and agentic workloads the reported savings are the largest anywhere — because caching attacks the specific way agent costs explode. If you optimize one thing, optimize this.
Of every AI cost lever, one dominates and all the major vendors agree on it: prompt caching. On agentic workloads the reported savings are the largest anywhere — because caching attacks the specific way agent costs explode. If you optimize one thing, optimize this.
Every LangChain application, no matter how elaborate, is built from three humble pieces: a model you call, a prompt you send it, and a parser that turns its reply into something usable. Master these three and the rest of LangChain is just composing them — which is exactly what the framework is designed to let you do.
Every LangChain application, no matter how elaborate, is built from three humble pieces: a model you call, a prompt you send it, and a parser that turns its reply into something usable. Master these three and the rest is just composing them.
The Agent is where everything in Pydantic AI comes together — model, instructions, tools, typed dependencies, and typed output, bundled into one reusable, testable object you define once and run many times. Understanding the Agent as a configured, type-parameterized unit is the key that makes the rest of the framework fall into place.
The Agent is where everything in Pydantic AI comes together — model, instructions, tools, typed dependencies, and typed output, bundled into one reusable, testable object you define once and run many times.
Knowing your customer is the front door; watching what they do is the rest of the house. AML transaction monitoring is the always-on system that scans activity for signs of money laundering — and it's a fascinating engineering problem precisely because the signal is rare, the cost of missing it is severe, and the cost of over-flagging drowns your investigators.
Knowing your customer is the front door; watching what they do is the rest of the house. AML transaction monitoring scans activity for signs of money laundering — a fascinating problem because the signal is rare, misses are severe, and over-flagging drowns investigators.
IP gets packets to a host but promises nothing about whether they arrive, in order, or intact. The transport layer is where that gap is filled — or deliberately left open. TCP builds a reliable, ordered connection on top of unreliable IP; UDP declines to, trading guarantees for speed. Choosing between them, and understanding TCP's costs, is core backend knowledge.
IP gets packets to a host but promises nothing about whether they arrive, in order, or intact. The transport layer fills that gap — or deliberately leaves it open: TCP builds a reliable ordered connection, UDP declines to and stays fast.
Logs are the oldest and most detailed telemetry — the granular record of what actually happened. But the log line you write for a human to read with grep is nearly useless at scale; the one you write as structured data for a machine to query is the one that saves you at 3 a.m. The shift from text logs to structured logs is the single biggest upgrade most teams can make.
Logs are the most detailed telemetry — the record of what actually happened. But the log line you write for a human to grep is nearly useless at scale; the one you write as structured data for a machine to query is the one that saves you at 3 a.m.