1290 posts · Page 38 of 108. ← Blog
A DSPy signature is the contract that says what goes in and what comes out of a step — and by declaring the transformation instead of writing the prompt, it becomes something the optimizer can improve.
A DSPy signature declares what goes in and what comes out of a step — and by declaring the transformation instead of writing the prompt, it becomes something the optimizer can improve.
AI systems are non-deterministic, so "it looked good in the demo" is not a quality signal — evaluation is the control system for the entire lifecycle, and if it doesn't gate releases, nothing does.
AI is non-deterministic, so 'it looked good in the demo' is not a quality signal. Phase 4: evaluation as the control system that gates every release — measurable and gating, or it's decoration.
Agentic RAG is what you get when retrieval stops being a fixed pipeline step and becomes a set of decisions an agent reasons through — whether to retrieve, what to search for, from where, how many times, and whether to trust the result.
Agentic RAG is what you get when retrieval stops being a fixed pipeline step and becomes a set of decisions an agent reasons through — whether, what, from where, how many times, and whether to trust results.
The single biggest cost lever in most AI systems is not clever prompting — it is not using an expensive model for work a cheap one would do just as well.
The single biggest cost lever in most AI systems is not clever prompting — it is not using an expensive model for work a cheap one would do just as well. Right-sizing and routing models to tasks.
The system prompt is the one piece of context present on every single call, so how you structure its role, rules, and format is the highest-leverage writing in the whole system.
The system prompt is the one piece of context present on every call, so how you structure its role, rules, and format is the highest-leverage writing in the whole system.
Delegating real work between agents is rarely a quick round trip, so A2A makes the task a first-class object with an explicit lifecycle that survives long-running, interruptible, asynchronous collaboration.
Delegated work is rarely a quick round trip, so A2A makes the task a first-class object with an explicit lifecycle that survives long-running, interruptible, asynchronous collaboration.
Tools are the part of the Model Context Protocol that lets a model do things instead of just talk about them, and their design is what separates an agent that helps from one that flails.
Tools are the MCP primitive that lets a model act. How to define them, the tools/list and tools/call methods, results versus errors, and designing tools a model can actually use.
An agent whose action space is fixed can only ever recombine what it was given, but an agent that writes and banks its own skills grows more capable the longer it runs.
An agent that writes and banks its own verified skills grows more capable the longer it runs. Voyager's skill library and how to build a self-extending action space.
Beyond the interactive terminal, Claude Code can run headless in scripts and CI — which unlocks automation, and raises the stakes on permissions, review, and trust.
The capstone: running Claude Code headless in scripts and CI (PR review, batch ops, scheduled jobs) — and the guardrails it demands: least privilege, sandboxing, gating the produced artifact with human review, and the series' layered recap.
The role that puts you closest to real problems and real users also carries the sharpest burnout and career traps — thriving as an FDE means managing both deliberately.
The capstone: building a durable FDE career — the rewards and the hazards (context-switching, emotional labor, the maintenance trap), managing your capacity and boundaries, and growing toward staff engineering, product, leadership, or founding.
A single pre-launch red-team decays the moment your model, prompt, or tools change — turning adversarial testing into a sustained program is what keeps an AI system safe past day one.
The capstone: making red-teaming a sustained program — the remediation loop where findings become regression tests, blending automated/manual/external modes, rules of engagement, ship-blocking severity thresholds, governance evidence, and culture.
The finale of "The Software Architect's Path" — why the non-technical skills decide whether a good design ever ships, and how communication, influence, mentoring, and humility turn a diagram into a system a whole team actually builds.
The capstone: the non-technical skills that make or break an architect — communication tailored to the audience, influence without authority, leading technically while staying hands-on, mentoring, and avoiding the ivory tower.