Library
Practical reviews, workflow playbooks, comparison frameworks, and resource paths for building AI automation systems.
Latest guides
A practical read of google/agents-cli as an agent lifecycle tool: scaffold, ADK code, eval data, deployment, logs, and the checks I would require before using it.
Fable 5's return, Sonnet 5's arrival, and Claude Science together show Anthropic repositioning Claude across daily work, frontier reasoning, and scientific research.
Bank of England warnings about agentic AI are not only a market story. The harder question is what happens when many AI systems move money in the same direction at once.
AI data centers are no longer a distant infrastructure story. The real question is how power demand, grid upgrades, and utility bills get allocated.
OpenAI's GPT-5.6 Sol, Terra, and Luna preview shows why teams should plan around model access, security review, and fallback routes.
A practical memo for choosing one paid AI subscription across ChatGPT, Claude, Gemini, Perplexity, and Copilot by work location, review effort, and handoff.
AI agents usually fail inside real workflows because the surrounding context, tools, permissions, checks, logs, approvals, and recovery paths are weak.
Choose ChatGPT Images, Gemini, Claude, Midjourney, Firefly, Ideogram, FLUX, Stable Diffusion, Recraft, Canva, and other image tools by the asset you actually need.
A practical Excel AI workflow for ChatGPT, Copilot, and Gemini across CSV cleanup, formulas, report drafts, and human review without breaking the numbers.
A practical take on Notion as an AI agent workspace hub, with boundaries for context records, approvals, MCP tools, and handoff design.
Most bad AI images fail before the prompt. Use this field guide to map ChatGPT, Gemini, Claude, Midjourney, Firefly, Ideogram, FLUX, and Stable Diffusion to real jobs.
AI search is useful, but one confident answer can still be wrong. Use this practical routine to check sources, dates, risk, and claims before you rely on it.
A practical Notion, Slack, and Google Sheets AI automation flow for intake, triage, status tracking, decision records, and human handoff.
AI-generated reports can look finished while pushing fact checks, rewrites, and accountability onto coworkers. Add acceptance rules before the draft moves.
Markdown work instructions make AI automation easier to repeat: scope, inputs, output contract, checks, stop conditions, and update rules in one reusable file.
A practical comparison of ChatGPT, Claude, and Gemini for real work in 2026 across documents, research, writing, review load, automation handoff, and team rollout.
Anthropic says Fable 5 access was limited under U.S. government export-control direction. Here is what that means for real AI operations.
Anthropic's Fable 5 restriction shows why enterprise AI automation needs clearer model routing, fallback paths, review stages, and data boundaries.
Where Codex plugins fit outside coding: documents, PDFs, sheets, browsers, Chrome, Computer Use, Figma, Drive, Slack, and repeatable work.
Codex is still a coding agent, but files, browser checks, Git, skills, MCP, and automations make it useful as a work execution layer.
A detailed look at the PocketOS database deletion incident and what it teaches about AI agent permissions, tokens, backups, approvals, logs, and recovery design.
AI automation can pass a test and still stall in real work. Use concrete examples to judge ownership, exceptions, approval, logs, and failure criteria before rollout.
Anthropic's Fable 5 access block is a model-routing warning for AI automation: security risk, fallback design, data policy, and operator judgment.
A practical review of Hermes Agent for automation teams: persistent memory, skill files, messaging gateways, security risk, cost, and production failure criteria.
MCP and A2A move AI automation from prompt craft to connection design: tools, handoffs, identity, logs, approval paths, and rollback.
Decide whether an AI agent pilot deserves production use by measuring manual baselines, review cost, failure cost, approval gates, and operating metrics.
Set least-privilege scopes, approval gates, audit logs, staged expansion, rollback, and recovery rules before connecting AI agents to real tools.
Compare QuickBooks, Xero, Zoho Books, FreshBooks, and Digits by transaction review, evidence, month-end close, accountant handoff, and exceptions.
Compare Apollo, Instantly, lemlist, Clay, and HubSpot by lead source, personalization depth, deliverability, opt-out, domain reputation, and CRM handoff.
Compare Lovable, Bolt, Replit, and v0 by internal-tool fit, workflow portal needs, data model, permissions, deployment, and handoff.
Compare Asana, ClickUp, monday.com, Notion, and Motion by meeting-to-task handoff, ownership, status, context, calendar execution, and reporting habits.
Use AI to turn survey answers, support tickets, reviews, and sales notes into prioritized actions with evidence, owners, and follow-up rules.
Design an AI email workflow that classifies requests, assigns owners, keeps SLA rules, drafts follow-ups, and escalates exceptions.
Compare Intercom Fin, Zendesk AI, and Help Scout AI by knowledge-base quality, ticket routing, human handoff, pricing model, and support risk.
Compare Zapier, Make, and n8n by ownership, workflow complexity, AI steps, exception handling, cost control, and long-term maintenance.