8 min read
Harness Engineering Makes Tokens a Systems Budget
Harness engineering turns tokens into a systems budget. OpenAI's Codex post and Tokenomics research say agent teams need budgets, receipts, and eval loops.
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Page 74 of 100
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Deep dives into AI agents, coding tools, and building with LLMs.
1198 articles844 topics
10 min read
LLM Routers Compared: LiteLLM vs Portkey vs OpenRouter in 2026
LiteLLM vs Portkey vs OpenRouter compared for production AI apps: cost tracking, fallbacks, caching, and load balancing, plus when to use each router.
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8 min read
AI Code Attribution Needs Defect Forensics, Not Vibes
The rsync Claude debate shows why teams need reproducible defect forensics before AI attribution becomes a public blame machine.
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8 min read
Headroom: Compress Agent Tool Output Before It Reaches the LLM
Headroom compresses AI agent tool outputs, logs, and files before they reach the LLM, claiming 60-95% token savings with benchmarked accuracy. How it works.
9 min read
Security Agents Need Repro Harnesses, Not More Scan Prompts
Anthropic's open-source vulnerability harness shows AI security agents need reproducible exploit loops, separate verification agents, and patch receipts.
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9 min read
AI Agent Containment Needs a Capability Ledger
Anthropic's Claude containment writeup points to the next security layer for coding agents: deterministic capability ledgers, not another approval prompt.
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7 min read
MAI-Code-1-Flash Is a Model Routing Signal
MAI-Code-1-Flash, Microsoft's in-house coding model, signals Copilot becoming a routing layer for cost, latency, and review quality. A routing matrix to steal.
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8 min read
AI Agent Memory Needs a Context Ledger
AI agent memory works best as a context ledger: source-linked, scoped, expiring memory that agents can inspect and users can audit, not magic recall.
8 min read
Spreadsheet Agents Need Permission Ledgers
The ChatGPT for Google Sheets exfiltration report shows spreadsheet agents need permission ledgers: action-scoped, logged, revocable, and visible permissions.
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8 min read
Domain Expertise Is the New Agentic Coding Moat
Domain expertise is the agentic coding moat only when it becomes executable: examples, tests, DSLs, and review gates that turn tacit judgment into checks.
8 min read
The Agent Security Checklist I Use Before Connecting Tools
Before an AI agent gets tools, files, APIs, MCP servers, or deployment access, decide what it can read, write, call, log, and roll back.
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9 min read
Build Log: Turning the DevDigest Blog Into an Agent Content System
How the DevDigest blog became an agent content system: posts, tags, RSS, search, llms.txt, and content expansion reports, plus what not to automate blindly.
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